BHSOAC
CompilingCSSDataToProducePriorityIndicators 2FPhase2 121812
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Mental Health Services Act Evaluation:
Compiling Community Services and Supports (CSS) Data
to Produce All Priority Indicators
Contract Deliverable 2F, Phase II
UCLA Center for Healthier Children, Youth and Families
EMT Associates, Inc.
Submitted on September 30, 2012
Revised version submitted on October 30, 2012
Version with county-specific outcomes submitted on December 18, 2012
The following report was funded by the
Mental Health Services Oversight and Accountability Commission.
The following report was revised in partnership with stakeholders who provided important
historical context, data consultation, and revisions to ensure this report is accurate and accessible
to the broadest audience possible. Feedback, collected prior to, during, and following report
development, was crucial to developing this report. The UCLA-‐EMT Evaluation Team would like to
express sincere appreciation to the research analysts, advocates, consumers and family members,
agency representatives, service providers, and MHSOAC representatives who contributed
invaluable insights to this document and previous versions.
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Table of Contents
Purpose ........................................................................................................................................................................................... 3
Background ................................................................................................................................................................................... 3
Stakeholder (Consumer/Client) Feedback ..................................................................................................................... 5
Review of Existing Data ........................................................................................................................................................... 5
Data Sources ................................................................................................................................................................................. 6
Priority Indicators Evaluated ............................................................................................................................................. 10
Report Organization .............................................................................................................................................................. 11
Priority Indicator 1: School Attendance ........................................................................................................................ 13
Priority Indicator 2: Employment ................................................................................................................................... 17
Priority Indicator 3: Homelessness and Housing Rates ........................................................................................ 21
Priority Indicator 4: Arrest Rates ................................................................................................................................... 25
Discussion: Consumer Indicators ..................................................................................................................................... 31
Priority Indicator 5: Demographic Profile of Consumers Served ..................................................................... 32
Priority Indicator 6: Demographic Profile of New Consumers ........................................................................... 36
Priority Indicator 7: Penetration of Mental Health Services ............................................................................... 42
Priority Indicator 8: Access to a Primary Care Physician ..................................................................................... 46
Priority Indicator 9: Perceptions of Access to Services ......................................................................................... 49
Priority Indicator 10: Involuntary Status .................................................................................................................... 52
Priority Indicator 11: Consumer Perceptions of Improvement in Well-‐Being as a Result of Services
......................................................................................................................................................................................................... 54
Priority Indicator 12: Satisfaction With Services ..................................................................................................... 58
Discussion: Community Mental Health System Indicators ................................................................................... 61
Stakeholder Engagement and Feedback ....................................................................................................................... 63
Next Steps ................................................................................................................................................................................... 63
Appendix A – California Mental Health Planning Council’s Proposed Indicators and Definitions ...... 64
Appendix B – Priority Indicator Updates ...................................................................................................................... 65
Appendix C – Stakeholder (Consumer/Client) Webinar Feedback ................................................................... 69
Appendix D – Recoding Pre-‐DIG Race Data to Post-‐DIG Format ........................................................................ 71
Appendix E – Counties Responding to Data Quality Assurance Reports, Comparison to Declined/
Non-‐Respondents .................................................................................................................................................................... 72
Appendix F – Summary of Stakeholder Feedback to the Previous Version of This Report .................... 76
Appendix G – County-‐Level Outcomes ........................................................................................................................... 87
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Purpose
The Mental Health Services Act Oversight and Accountability Commission (MHSOAC) charged the
UCLA-‐EMT Evaluation Team with tracking the Mental Health Services Act’s (MHSA) impact on
mental health service consumers and the community mental health service system. The current
report details the initial effort toward this goal.
Here, we provide a snapshot of consumer outcomes and community mental health system
performance—a first step toward developing a set of indicators that can help stakeholders with
ongoing quality improvement. This report is the first in a series designed to update stakeholders
about mental health consumer outcomes and service system progress. Tracking performance on
particular outcomes over time, across programs, and/or in comparison to other counties can
provide useful information to those planning, operating and monitoring services. Indicators are
intended to be used for planning, quality improvement, and other applications that stakeholders
deem important. In this way, among many others, stakeholders can play a vital role in a continuous
quality improvement process.
Background
What are Priority Indicators and what are they intended to do?
Two concerns of public mental health system stakeholders are accountability and the ability to
conduct continuous quality improvement activities. One strategy is to use a set of indicators to
measure performance. The California Mental Health Planning Council proposed and defined a set of
performance indicators, referred to as priority indicators, designed to assess how the MHSA has
impacted mental health consumers and the mental health system in target areas that should be
most changed through MHSA implementation. Indicators will help track progress among
consumers and across community mental health systems. At the consumer level, outcomes such as
education and employment will be followed, while outcomes including mental health service
penetration and consumer demographics are examined at the broader system level. This report
examines the core set of priority indicators vetted by the MHSOAC.
Previous work of the UCLA-‐EMT Evaluation Team leading to this report
The evaluation team began its work using the California Mental Health Planning Council’s
definitions –its collective vision of how indicators might best be measured. (These fundamental
definitions are located in Appendix A and are discussed in preceding reports available at
http://healthychild.ucla.edu/MHSA_evaluation.asp.) Priority indicator development was a joint
effort among the MHSOAC, stakeholders, and the evaluation team. The evaluation team facilitated
discussions among interested stakeholders to create the strongest, most comprehensive
representations of priority indicators that aligned with both early conceptualizations and feedback
using the data that were already collected across the state with some regularity. Where gaps
existed, the evaluation team proposed new data collection that will improve future evaluation but is
beyond the team’s current scope of work.
The evaluation team adapted advice from stakeholders, and this report examines whether these
adapted indicators provide meaningful information. Although stakeholders proposed additional
indicators, these measures have not yet been vetted by the MHSOAC to determine whether they add
useful and crucial information that aligns with the need. The MHSOAC has yet to decide whether to
change the previously approved priority indicators. Thus, the evaluation team explored the first
proposed priority indicators in this report, which serves as a fundamental step in the ongoing
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process to refine and expand priority indicators that are not only measurable but also useful to the
range of stakeholders invested in this work.
The evaluation team completed extensive groundwork before arriving at the conclusions contained
in this report. To date, the team has documented evaluation planning in four reports:
Report title: Defining Priority Indicators
Report version: Draft for stakeholder review
Here, the evaluation team began to refine the core set of priority indicators proposed by the
California Mental Health Planning Council to assess target outcomes of mental health
consumers and the performance of the mental health system. The evaluation team and the
MHSOAC made this report version available to the public through mass e-‐mail
announcements and online at UCLA and MHSOAC websites. A guidance document that
included specific questions regarding the initial report’s content and accessibility was also
included with the report to aid review. The evaluation team requested that readers alert
their peers and clients to the report to broaden the diversity of feedback. The team also
hosted two webinars, or online orientations to the report, with stakeholder groups that
provided an overview of the report’s purpose and the type of feedback sought. The call for
feedback was open for one month.
Report title: Defining Priority Indicators
Report version: Final, revised with stakeholder input
In the revised report, the evaluation team illustrated how stakeholder feedback was integral
to indicator development. This report incorporated changes driven by stakeholders’
comments about the comprehensiveness and appropriateness of the indicators.
Report title: Compiling Data to Produce All Priority Indicators
Report version: Draft for stakeholder review
In this report, the evaluation team proposed how priority indicators could be calculated
using existing statewide data. The report also detailed all possible data sources and specific
variables or data fields that might be used to build comprehensive priority indicators. The
evaluation team made this draft widely available for feedback using a strategy similar to
that of the Defining Priority Indicators-‐Draft report; the report’s availability and a call for
feedback were announced online. Readers could download the report and an accompanying
guidance document from the UCLA or MHSOAC websites and respond with comments
within the month-‐long feedback period.
Report title: Compiling Data to Produce All Priority Indicators
Report version: Final, revised with stakeholder input
The initial report was revised to include information regarding measurement methods and
the adequacy of existing data sources, gathered through a stakeholder feedback process
similar to that used for the final Defining Priority Indicators report.
This report is the next step in documenting priority indicator development. The evaluation team
reviewed data from 2005 through 2011 in search of one fiscal year in which data cells were largely
filled where expected. Two such fiscal years were identified – FYs 2008-‐09 and 2009-‐10. Through
analysis, some proposed data sources or methods of indicator calculation, suggested in previous
reports by stakeholders and the evaluation team, were found to not be possible or to not produce
meaningful outcomes due to data limitations. Decisions made about previously proposed
indicators, based on data limitations, are summarized in Appendix B.
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Stakeholder (Consumer/Client) Feedback
It should be noted that the following report was shaped by the input of stakeholders who have
engaged the mental health services system. The evaluation team facilitated a webinar on September
17, 2012, during which several report segments (e.g., executive summary, priority indicators
definition, priority indicator summary page, and illustrations) were reviewed and discussed at
length. The goal of this review was to ensure that language was widely accessible to all readers and
that concepts, including those statistical in nature, were clear. A few suggestions included the
following:
1. Simplify language such as changing “utilize” to “use.”
2. Define statistical terms (e.g., “n” refers to the number of consumer/clients within a
particular population).
3. Explain the importance of data deemed “missing” from calculations.
4. Refer to consumers as “consumers/clients.”
To the extent possible and where revisions enhance understanding, these suggestions are
incorporated throughout the following report. To note, the team refers to “consumers” throughout
the document for brevity and to match terms used by those who designed this project. However, we
do recognize the ongoing conversation about stakeholders’ engagement in mental health services
as consumers and clients. Stakeholder comments about concepts beyond the scope of this report
are noted (see Appendix C) but not addressed in this document.
Review of Existing Data
As directed by the MHSOAC, priority indicators were built upon existing data sources that are
systematically collected by California counties and reported to the California Department of Health
Care Services (DHCS).1 To accomplish this, existing data systems were reviewed to assess their
suitability for supporting outcome and performance monitoring through priority indicators. Several
criteria were used to evaluate the suitability of existing data sources, including:
• Available – Data accessible in an analyzable format
• Complete – Levels of missing information within key data fields did not prevent meaningful
analysis and interpretation
• Sustained – Data sources is likely to continue to exist in the foreseeable future
• Relevant – Data relevant to populations of interest (e.g., all mental health consumers and
Full Service Partnerships
• Longitudinal – Data available for multiple service years
• Multilevel – Data can be analyzed at multiple levels (e.g., state, county, and individual)
The application of these criteria to each key data source and important considerations and
limitations regarding each data source overall are summarized in the Data Sources table below.
These criteria were also applied to the specific data fields used to build each priority indicator.
Review of indicator-‐specific data fields is summarized within the tables that introduce the analysis
and findings of each priority indicator (see Priority Indicator Analysis and Findings section below).
1 Previously the Department of Mental Health (DMH); The DHCS abbreviation will be used to refer to work
completed by DMH.
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Data Sources
Client & Service Information (CSI)
Summary: The CSI system is a repository of county, client (e.g., age, gender, preferred language, education,
employment status, living arrangement, etc.), and service information (type, number and length of service
contact). The data are collected from all consumers who receive mental health services, including consumers
involved in the Full Service Partnership.
Review Findings:
Available ü Complete ü Sustained ü Relevant ü Longitudinal ü Multilevel ü
Considerations and Limitations: Stakeholder feedback to previous evaluation team reports suggested that
inconsistency and potential inaccuracy among race and ethnicity data fields may be due in part to changes in the
format of these fields in the CSI data system (see DMH Information Notice: 06-‐02). For details regarding the Race
and Ethnicity data field changes and procedures employed by the evaluation team to improve data quality, see
Appendix D.
Additionally, the completeness of data fields used to calculate indicators varies greatly across fiscal years and
among counties (e.g., greater than 50% in some cases). Thus the representativeness and interpretability of such
data fields is in doubt. Proportions of missing or unknown information are noted within each indicator section
throughout the report.
Data Collection and Reporting (DCR) System
Summary: The DCR system houses data for consumers who are served through Full Service Partnership programs.
Data from assessments – the Partnership Assessment Form (PAF), Key Event Tracking (KET), and Quarterly
Assessment (3M) – are collected for consumers in specific age categories. The PAF reflects consumer history and
baseline information, including consumer education and/or employment, housing situation, legal issues, health
status, and substance use. The KET reflects any important changes in the consumer’s life, such as housing,
education and/or employment, and legal issues during FSP. The 3M is used to collect information on a quarterly
basis, regarding key areas such as education, health status, substance use, and legal issues.
Review Findings:
Available ü Complete ü Sustained ü Relevant ü Longitudinal ü Multilevel ü
Considerations and Limitations: Race and ethnicity information in the DCR system is imported from the CSI system
by DHCS. As such, the limitations of this information noted for the CSI system also apply here. Specifically,
stakeholder feedback to previous evaluation team reports suggested that inconsistency and potential inaccuracy
among race and ethnicity data fields may be due in part to changes in the format of these fields in the DCR data
system (see DMH Information Notice: 06-‐02 ). For details regarding race and ethnicity data field changes and
procedures employed by the evaluation team to improve data quality, see Appendix D.
Additionally, representatives from seven counties or municipalities that currently do not have data contained in
the DCR database for FYs 2008-‐09 or 2009-‐10 were given the opportunity to provide data to the evaluation team
for DCR fields used to calculate indicators. Of the counties not captured in the DCR database for various reasons
(e.g., county data incompatibly formatted DHCS database), four representatives provided data within eight weeks
of receiving the data quality assurance report. This information was considered in analyses and preparation of this
report. The DCR data that other county representatives provided or may provide directly to the evaluation team
after June 8, 2012, will be considered for future reports.
Performance Outcomes and Quality Improvement (POQI) – Consumer Perception Surveys (CPS)
Summary: These consumer surveys are customized for consumer groups (e.g., family members/caregivers, youth,
adults, and older adults) receiving mental health services. Instruments are composed of widely validated measures
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of several domains, including satisfaction, access, quality / appropriateness of services, outcomes, functioning, and
social connectedness. The data, designed to inform treatment planning and service management, are collected
from a sample of individuals with “serious, persistent” mental illness who have received services for 60 days or
more and are not categorized as “medication only.”
Review Findings:
Available ü Complete ü Sustained ü Relevant ü Longitudinal ü
Considerations and Limitations: For FY 2008-‐09 and prior years, a convenience sampling approach was used in
which county-‐level mental health service providers administered surveys twice a year for a two-‐week period, in
early May and November. Investigation of the convenience sampling methodology revealed the resulting
information was not representative of the larger mental health service population.2 Beginning with FY 2009-‐10, a
random sampling methodology was employed to produce data that are more representative of the perceptions of
the mental health service population. As such, comparisons involving CPS data collected in FY 2008-‐09 and FY
2009-‐10 cannot be made.
Note – The smaller sample generated by the random sampling method employed in FY 2009-‐10 does not allow for
consumer perception analyses at the county levels for this fiscal year.
Note – The sampling methods that have been employed to date do not capture specific mental health service
populations, such as those in institutions for mental disease or prison.
Other Sources
Estimates of Need for Mental Health Services
To achieve a standardized rate for penetration of services across all counties, the evaluation team contracted with
Dr. Charles Holzer for statewide and county mental health service need estimates. Dr. Holzer previously developed
penetration rate estimates for the California DHCS. He estimated the proportion of persons with serious mental
illness among those whose income falls within 200% of the federal poverty level, using data from the most up-‐to-‐
date National Comorbidity Survey Replication and generated prevalence estimates for several Census years. (For
additional information regarding prevalence estimate methodology, see Dr. Holzer’s website at
http://66.140.7.155/estimation/3_Synthetic/synthetic.htm).
Review Findings:
Available ü Complete ü Relevant ü Longitudinal ü
Involuntary Status
Involuntary status information (FY 2008-‐09) was provided by DHCS for the following service categories: 72 hour
Evaluation and Treatment (adults, children); 14-‐ and 30-‐day Intensive Treatment; 180-‐day Post Certification
Treatment; and Temporary and Permanent Conservatorships. Involuntary status data for FY 2009-‐10 were not
available from DHCS as this report was being prepared.
Review Findings:
Available ü Complete ü Sustained ü Relevant ü Longitudinal ü
2 Cowles, E. L., Harris, K., Larsen, C., and Prince, A. (2010). Assessing Representativeness of the Mental Health
Services Consumer Perception Survey.
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Procedures for handling missing / unknown data
The quantity of missing or unknown data (e.g., values) was found to vary considerably across data
sources, data fields, and fiscal years. For data fields determined to be necessary for the construction
of priority performance indicators (detailed in priority indicator summary tables, see Priority
Indicator Analysis and Findings section below), if the amount of missing or unknown data was
substantial (i.e., greater than 10% of cases), the evaluation team communicated with DHCS analysts
and requested input from counties via a data verification process (detailed below) regarding
context and interpretation of such data fields. Where adequate information was received to
interpret missing or unknown values (i.e., see Appendix D), the evaluation team was able to analyze
and interpret such data fields according to current protocols specified in the data dictionaries
relevant to each data system. The proportion of missing and unknown information relevant to each
priority indicator is noted throughout the report, in footnotes immediately below the relevant table
or figure. Accordingly, the frequencies and percentages included in all data displays do not include
missing cases.
Summary of data “verification” process
In a first attempt to calculate priority indicators, the evaluation team asked county representatives
to weigh in on the quality of select data. The evaluation team narrowed a pool of possible
calculations to one practical calculation for each priority indicator. The selection was based on
predetermined criteria (see Compiling Data to Produce All Priority Indicators, November 2, 2011),
an extensive review of the available data, and discussions within the evaluation team about
whether proposed calculations could be meaningfully extrapolated to mental health consumer
populations. This process revealed the need for a more thorough data quality review. Closer
examination of the data needed for each calculation revealed that substantial variation (values and
reporting patterns) existed among counties/municipalities, within CSI and DCR data fields
identified for constructing priority indicators, during FYs 2008-‐09 and 2009-‐10. The variation, in
addition to stakeholder feedback to our previous report, demonstrated a need for county
representatives to indicate the quality of key data and contextual information needed for analysis,
interpretation, and decisions based on this data.
At the direction of the MHSOAC ad-‐hoc committee, the evaluation team provided representatives
from all counties/municipalities the opportunity to review and comment on their data quality. The
team sought feedback from county MHSA coordinators and mental health service directors who
were most familiar with local mental health data about the accuracy of particular data (i.e., if the
demographic distribution pulled from the state datasets for their particular county seemed
correct).
The evaluation team developed an outcomes report for targeted data that was distributed to
representatives in each county. The committee revised the document for brevity such that
representatives would note only whether data were “accurate” or “inaccurate.” A text field was
included for any explanation of why data was deemed “inaccurate.” County representatives were
asked to respond to non-‐missing data; “unknown,” “missing,” and blank fields were grouped into
one category.3
3 Cowles, E. L., Harris, K., Larsen, C., and Prince, A. (2010). Assessing Representativeness of the Mental Health
Services Consumer Perception Survey.
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Recruitment
County representatives received an e-‐mail alert about the incoming report and the evaluation
team’s goals. Subsequently, the team distributed county-‐specific reports via e-‐mail with an
invitation to complete the review by May 4, 2012. The evaluation team distributed .pdf versions of
the reports for representatives to review with their data teams but asked representatives to enter
their final responses online at a link provided in the report. Counties that were not enrolled in
statewide reporting were asked to provide a download of specific data for the years specified.
Although the importance of county-‐level feedback was stressed, neither the MHSOAC ad-‐hoc
committee nor the evaluation team mandated participation. Instead, the consequences of spotty
participation from county representatives were noted in the invitation. The text included in the
report introduction is as follows:
We hope to get responses from all counties. At the very least we hope to get responses from a
sufficient number and variety of counties so that the data in the statewide report is
representative. To determine that a sufficient representation is achieved, participating
counties must commit to participation by April 16, 2012. If we do not get a representative
sample of counties, we have been asked to move forward with the statewide report using all
the data available from both CSI and DCR (confirmed and unconfirmed). We will also be
producing county level reports and will use available confirmed and unconfirmed DCR and CSI
data. Again we are hoping every county participates and returns this profile indicating the
quality of the data they submitted to the state system.
Data Quality Assurance Report Outcomes
Twenty-‐nine of 59 total counties and municipalities provided responses within six weeks of
receiving their Data Quality Assurance Report. Responding counties represented a broad cross-‐
section of the state population, accounted for substantial proportions of most MHSA regions, and
represented the state’s racial and ethnic diversity. (For descriptive analysis of
counties/municipalities represented in the quality assurance exercise, see Appendix E.)
Stakeholder feedback to previous reports identifying data sources for the statewide MHSA
evaluation and feedback to the county-‐specific Data Quality Assurance Reports were generally
consistent. Responses across counties indicated that the majority of fields were accurate. However,
a few fields, such as race and ethnicity, received much more inconsistent evaluations of accuracy.
Feedback about data quality was a factor in final decisions about what to use from state databases.
Strategy Assessment
The data quality assurance exercise was an effort by the ad-‐hoc committee and the evaluation team
to identify data that could provide accurate insight about priority indicators. The process was
important as the group attempted the first round of calculations; data deemed “accurate” by county
representatives, and ultimately used in the draft priority indicators report, was vital to refining
calculations. Although the method was well-‐intentioned, it could not be fully realized because of
limited participation from counties; counties that did not participate could not be authentically
represented.
As a result, the MHSOAC ad-‐hoc committee redirected the evaluation team to incorporate all data in
state databases needed to calculate priority indicators based on the participation rate of counties
during the data quality assurance exercise. Without means to ensure that all counties participate,
this particular exercise will not be involved in future report development.
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Priority Indicators Evaluated4
The set of priority performance indicators evaluated in this report were arrived at through the
following processes:
• The careful consideration of the California Mental Health Planning Council and approval of
the MHSOAC;5
• Consideration of the MHSOAC goal of developing a comprehensive outcome and
performance monitoring system built upon existing data systems;
• Consideration of consumer feedback to previous evaluation team reports regarding
proposed priority indicators (e.g., “Defining Priority Indicators”);
• Review of existing data sources to assess their suitability for supporting outcome and
performance monitoring through priority indicators (see Review of Existing Data, above);
and
• County feedback regarding the quality and completeness of key data fields necessary to
calculate priority performance indicators (see Summary of data “verification” process,
above).
Through these evaluation processes and careful deliberation of the MHSOAC in collaboration with
the evaluation team, a set of 12 priority performance indicators was developed. These indicators
can be categorized as those intended to provide insight into the outcomes of mental health
consumers (“Consumer Indicators”) and those intended for monitoring the performance of the
community mental health system more broadly (“System Indicators”). Consumer and system
indicators, and the consumer groups they assess, are summarized in the table below.
Priority Indicators
CONSUMERS EVALUATED
SERVICE OLDER
CHILDREN TAY ADULTS
POPULATION ADULTS
CONSUMER INDICATORS
Indicator 1 – Average School Attendance Per Year All/FSP Consumers x x
Indicator 2 – Employed Consumers All/FSP Consumers x x x
Indicator 3 – Homelessness and Housing Rates All/FSP Consumers x x x x
Indicator 4 – Arrest Rate All/FSP Consumers x x x x
SYSTEM INDICATORS
Indicator 5 – Demographic Profile of Consumers Served All/FSP Consumers x x x x
Indicator 6 – Demographic Profile of New Consumers All/FSP Consumers x x x x
Indicator 7 – Penetration of Mental Health Services All Consumers x x x x
Indicator 8 – Access to a Primary Care Physician FSP Consumers x x x x
Indicator 9 – Perceptions of Access to Services All Consumers x x x x
Indicator 10 – Involuntary Status All Consumers x x x x
Indicator 11 – Consumer Well-‐Being All Consumers x x x x
Indicator 12 – Satisfaction All Consumers x x x x
4 Although we received strong indicator suggestions from stakeholders, this report helps vet the
appropriateness of the original set proposed by the California Mental Health Planning Council. If the MHSOAC
chooses, it may vet additional indicators, particularly those proposed by stakeholders, when revising the pool.
5 California Mental Health Planning Council (January, 2010). Performance Indicators for Evaluating the Mental
Health System.
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Criteria used to evaluate priority indicators
Specific criteria, developed in collaboration with the MHSOAC, were established to evaluate priority
performance indicators. These criteria, outlined for consumer and system indicators below, reflect
the goals of the MHSOAC for monitoring consumer outcomes and community mental health system
performance at multiple levels (i.e., state and county) for the purposes of planning and quality
improvement. These criteria may include:
Consumer Indicator Evaluation Criteria:
• Indicator can describe changes in consumer outcomes (e.g., change since initiation of
services) or describe the current status of consumers.6
• Indicator can provide meaningful and relevant insight into the outcomes of service
populations of interest (e.g., all mental health consumers, FSP consumers, and demographic
groups).
• Indicator can provide meaningful and relevant insight into the outcomes of consumers
statewide and at the county level.
• Indicator provides “actionable” insight, which stakeholders can use to identify areas for
service improvement.
System Indicator Evaluation Criteria:
• Indicator can describe meaningful changes in system performance over time.
• Indicator can provide meaningful and relevant insight regarding the extent and quality of
services provided to populations of interest (e.g., all mental health consumers, FSP
consumers, and demographic groups).
• Indicator can provide meaningful and relevant insight into the performance of the
community mental health system at the statewide and county levels.
• Indicator provides “actionable” insight, which stakeholders can use to identify areas for
improving the performance of the mental health system.
The application of consumer and system indicator evaluation criteria to each priority indicator is
detailed in the Priority Indicator Analysis and Findings section below.
Report Organization
The remainder of the report summarizes each indicator and its outcomes, calculated using select
statewide data from FYs 2008-‐09 and 2009-‐10. First, the evaluation team presents individual-‐level
priority indicators (those specific to consumers), followed by a discussion and summary of these
indicators. The team then does the same for system-‐level priority indicators (pertaining to
community mental health systems throughout the state). A summary table precedes each indicator
and its outcomes to orient the reader to what the indicator measures, how it was calculated, and its
usefulness. Following a review of all indicators, the evaluation team describes stakeholder feedback
and considerations. The report ends with an outline of the team’s next steps in the evaluation. An
overview of county-‐specific outcomes is included as an appendix.
6 Calculations for employment, education, and arrests in this report were created using intake data.
Calculations in subsequent reports will incorporate post-‐enrollment data.
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Indicator summary tables
Each priority indicator is introduced and summarized in a concise and organized table in the
Priority Indicator Analysis and Findings section below. Indicator summary tables are organized into
the following sections:
• Indicator Summary – Provides a brief definition of the indicator
• Indicator Calculation – Details the computation used to produce the indicator
• Data Sources – Specifies the data sources and relevant data fields (variables) used to
compute the indicator
• Review of Existing Data – Review of data quality criteria (specified in the Review of Existing
Data section above) as applied to indicator-‐specific data fields
• Analytic Potential of Indicator – Review of indicator evaluation criteria (specified in the
section on Criteria used to evaluate priority indicators above)
Note regarding indicator data displays
Each indicator is presented through one or more graphical displays of information. These displays
include figures (e.g., bar graphs) and tables of frequencies and percentages. The symbol “n” within
the displays stands for the number of consumers included in the analysis. For ease of viewing and
interpreting data displays specific to a service population, figures that display indicator information
relevant to all mental health consumers are presented in blue, and those relevant to FSP consumers
are presented in green.
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Priority Indicators Analysis and Findings: Consumer Indicators
Priority Indicator 1: School Attendance
1.1 Expulsions and Suspensions Per Year (CPS)
Indicator Summary
This indicator provides the proportion of children and TAY who reported being suspended/expelled 12 months
prior to receiving services and the proportion of children and TAY who reported being suspended/expelled since
beginning services. This indicator includes only children and TAY who reported receiving services for 6 to 12
months and responded to a consumer perception survey. This indicator provides information regarding whether
the proportion of suspended/expelled clients has increased or decreased after 6 to 12 months of service. This
indicator does not measure school attendance, but it provides just one measure of why children or TAY would not
attend school.
Indicator Calculation
• The number of reported suspensions/expulsions 12 months prior to services divided by the total number of
children and TAY for who we have data
• The number of reported suspensions/expulsions since beginning services divided by the total number of
children and TAY for who we have data
Note: Clients were surveyed multiple times during the 2008 – 2009 fiscal year. However, only the first survey
administration was used to get the proportion of children and TAY who reported being suspended/expelled 12
months prior to beginning services and since beginning services as it had the most complete data.
Additionally, the TAY age group was revised to include only the ages of 16 – 18 (rather than 16 – 25) because
attendance variables are less clear or less relevant to clients older than 18.
Data Sources
Consumer Perception Survey (CPS) for Youth Data Fields: HowLong, LES12EXPSUS, LES12PSTEXPSUS
Review of Existing Data
• Data sources likely to be sustained
• Data relevant to populations of interest (youth and TAY)
• Approximately 17.5% missing or unknown values
Analytic Potential of Existing Data
• Analysis across time possible
• Analysis among specific service populations not possible
• State and county level analysis possible
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Figure 1.1-‐1– Proportion of Children Expelled/Suspended 12 Months Prior to Services and Since
Beginning Services, FY 2008-‐09
100%&
90%&
80%&
70.2%& 70.7%&
70%&
60%&
Yes&
50%&
No&
40%&
29.8%& 29.3%&
30%&
20%&
10%&
0%&
Expelled&or&suspended&& Expelled&or&suspended&&
12&months&prior&to&services&&&&&&&&&&&&&&&&& since&beginning&services&&&&&
(n&=&1,925)& &(n&=&1,944)&
Unknown/missing for Expelled/Suspended 12 month prior to services = 18.7% (n = 444); Unknown/missing for
Expelled/Suspended since beginning services = 18.0% (n = 435)
Figure 1.1-‐2 – Proportion of TAY Expelled/Suspended 12 Months Prior to Services and Since
Beginning Services, FY 20098-‐09
100%&
90%& 82.7%&
76.1%&
80%&
70%&
60%&
50%&
Yes&
40%&
No&
30%& 23.9%&
17.3%&
20%&
10%&
0%&
Expelled&or&suspended&& Expelled&or&suspended&&
12&months&prior&to&services&&& since&beginning&services&&&&&&&&&&
(n&=&1,159)& (n&=&1,171)&
Unknown/missing for Expelled/Suspended 12 month prior to services = 17.4% (n = 245); Unknown/missing for
Expelled/Suspended since beginning services = 16.8% (n = 230)
During FY 2008-‐09, expulsion/suspension rates were higher for children than those for TAY. Thirty
percent of children reported being expelled or suspended 12 months prior to services compared to
24% of TAY. Twenty-‐nine percent of children were expelled or suspended since beginning services
compared to 17% of TAY.
14
1.2 Average School Attendance Per Year (FSP)
Indicator Summary
This indicator provides descriptive information regarding the frequency for which Full Service Partnership
consumers (children and TAY) attended school during the 2008-‐09 and 2009-‐10 fiscal years. Outcomes are a
summary of admission data.
Indicator Calculation
• The number of children who attended school always, mostly, sometimes, infrequently, and never divided by
the number of children for which there were data
• The number of TAY who attended school always, mostly, sometimes, infrequently, and never divided by the
number of TAY for which there were data
Note: Age groupings were revised such that:
Child ages = 1-‐15 (same as previously)
TAY ages = 16-‐18 (16-‐25 previously)
The TAY age group was revised because education variables would be less clear for clients older than 18.
Data Sources
DCR (PAF -‐ NONRES) Data Field: AttendanceCurr
Review of Existing Data
• Data sources likely to be sustained
• Data relevant to populations of interest (FSPs)
• Amount of missing data for child age group is approximately 6%
• Amount of missing data for TAY age group is approximately 46%
Analytic Potential of Indicator
• Analysis across time possible
• Analysis among specific service populations possible
• State-‐ and county-‐level analysis possible
15
Figure 1.2-‐1 –The frequency with which children and TAY attended school, FY 2008-‐09 admission
data (DCR)
100%
90%
80%
70%
60%
49.1%
50% Child (n = 4,655)
40% 32.6% 34.4%
31.6% TAY (n = 2,033)
30%
20% 13.5%
8.5% 10.4% 9.0%
10% 6.0% 4.7%
0%
Always Mostly Somemmes Infrequently Never Alends
Alends Alends Alends Alends
Child % missing data = 6.4% (n = 299), TAY % missing data = 47.5% (n = 966)
Figure 1.2-‐2 –The frequency with which children and TAY attended school, FY 2009-‐10 admission
data (DCR)
100%
90%
80%
70%
60%
48.4%
50%
Child (n = 4,655)
36.6%
40%
31.9% 31.3%
TAY (n = 2,033)
30%
20%
12.2% 10.7%
8.5% 8.7%
10% 6.4% 5.3%
0%
Always Mostly Somemmes Infrequently Never Alends
Alends Alends Alends Alends
Child % missing data = 5.8% (n = 390), TAY % missing data = 44.4% (n = 1,327)
Trends are similar across FY 2008-‐09 and 2009-‐10. Most children and TAY consumers are
categorized as “always” or “mostly” attending school. Smaller proportions report attending
“sometimes,” “infrequently,” and “never.” Children are more likely than TAY to “always attend”
school, according to data.
16
Priority Indicator 2: Employment
Indicator Summary
This indicator provides the proportion of TAY, adults and older adults who are employed (paid and non-‐paid,
including voluntary contributions) and not employed as recorded during the most recent update (second date of
service). This indicator provides descriptive information regarding clients’ employment status during their second
date of service.
Indicator Calculation
Client & Service Information (CSI)
• The number of paid employed clients divided by the total number of TAY, adults, and older adults for whom
there were employment data.
• The number of nonpaid employed clients divided by the total number of TAY, adults, and older adults for
whom there were employment data.
• The number of non-‐employed clients divided by the total number of TAY, adults, and older adults for whom
there were employment data.
Note: There were multiple periodic updates for clients within each fiscal year. These ratios provide information for
those who had a second periodic update (referred to in datasets as “ServiceDate.2,” or the second date of service)
within a given fiscal year. Additionally, the age groupings were revised to capture those truly eligible for
employment. Those who indicated they were retired or incarcerated were excluded from calculations.
Data Collection and Reporting (DCR)
• The number of TAY, adults, and older adults who reported paid employment at admission divided by the total
number of TAY, adults, and older adults.
• The number of TAY, adults, and older adults who reported nonpaid employment at admission divided by the
total number of TAY, adults, and older adults.
• The number of TAY, adults, and older adults who did not report any employment at admission divided by the
total number of TAY, adults, and older adults.
Note for CSI and FSP data:
Age groupings were revised such that
TAY ages = 18-‐25 (previously 16-‐25)
Older adults = 60-‐65 (60 and up previously)
Data Sources
CSI Periodic Post-‐dig, Data Field: Employment Status
DCR (PAF -‐ NONRES) Data Fields: Current_CompetitiveAvgHrWeek, Current_SupportedAvgHrWeek,
Current_TransitionalAvgHrWeek, Current_In-‐HouseAvgHrWeek, Current_OtherEmploymentAvgHrWeek,
Current_Non-‐paidAvgHrWeek
Review of Existing Data
Client & Service Information (CSI)
• Data sources likely to be sustained
• Data relevant to populations of interest (all consumers)
• Data available across multiple service years
• Approximately 23% missing/unknown values
17
Data Collection and Reporting (DCR)
• Data sources likely to be sustained
• Data relevant to populations of interest (FSPs)
The amount of missing data for these ratios is unknown given how the employment data are collected. There is no
data code option for “missing;” as a consequence, blank responses are either missing or not applicable.
Analytic Potential of Indicator
Client & Service Information (CSI)
• Analysis across time possible but very difficult
• Analysis among specific service populations not possible
• State-‐ and county-‐level analysis possible
Data Collection and Reporting (DCR)
• Analysis across time possible
• Analysis among specific service populations possible
• State-‐ and county-‐level analysis possible
18
Figure 2.1 -‐ Proportion of clients who were employed and not employed as reported during their
second date of service, FY 2008-‐09 (CSI)
100%
90%
80%
70%
60%
86.9% 86.0%
91.5% Not Employed
50%
Nonpaid Employment
40%
Paid Employment
30%
20%
0.2% 0.3%
10%
12.9% 13.7% 0.3%
8.2%
0%
TAY Adult Older Adult
(n = 15,754) (n = 55,743) (n = 3,137)
Unknown/Missing for FY 2008-‐09 = 23.8% (n = 41,621)
Figure 2.2 – Proportion of clients who were employed and not employed as reported during their
second date of service , FY 2009–10 (CSI)
100%
90%
80%
70%
60%
85.7% 87.3%
93.3% Not Employed
50%
Nonpaid Employment
40%
Paid Employment
30%
20%
0.2%
0.3%
10%
14.1% 12.4% 0.5%
6.3%
0%
TAY Adult Older Adult
(n = 12,741) (n = 44,152) (n = 2,655)
Unknown/Missing for FY 2009-‐10 = 21.9% (n = 46,014)
Among all age groups, at least 86% of consumers were not employed during FY 2008-‐09 and 2009-‐
10. Older adults were least likely to be employed. Of those consumers who were employed, most
were involved in paid employment, including volunteer work.
19
Figure 2.3 –The proportion of FSPs who were employed during FY 2008–09 admission (DCR)
100%
90%
80%
70%
60%
91.7% Not Employed
95.2% 96.7%
50%
Nonpaid Employment
40%
Paid Employment
30%
20%
10% 0.5%
0.9% 0.9%
7.8%
3.9% 2.4%
0%
TAY Adult Older Adult
(n = 3,749) (n = 10,399) (n = 926)
Amount of missing data unknown for FY 2008–09. There is no data code for missing data. Blank data cells can be
interpreted as either “not applicable” or “missing.”
Figure 2-‐4 –The proportion of FSPs who were employed during FY 2009–10 admission (DCR)
100%
90%
80%
70%
60%
91.6% Not Employed
50% 95.1% 97.0%
Nonpaid Employment
40%
Paid Employment
30%
20%
10% 0.5%
0.8% 0.8%
7.9% 4.1% 2.3%
0%
TAY Adult Older Adult
(n = 5,032) (n = 13,833) (n = 1,181)
Amount of missing data unknown for FY 2009–10. There is no data code for missing data. Blank data cells can be
interpreted as either “not applicable” or “missing.”
Trends among Full Service Partnership (FSP) participants were similar to what was seen among
consumers in the CSI. Admission data showed that most consumers (at least 92%) in each age
group were not employed during intake. Older adults were least likely to be employed. Of those
who were employed, most were paid.
20
Priority Indicator 3: Homelessness and Housing Rates
Indicator Summary
This indicator summarizes the housing status of all mental health consumers and FSPs served during FYs 2008-‐09
and 2009-‐10. There are two parts: (a) a breakdown by most recently available housing status and (b) the
percentage of consumers experiencing homelessness at any point during the year.
Indicator Calculation
Frequencies of the most recent housing statuses were computed for mental health and FSP consumers served in
FYs 2008-‐09 and 2009-‐10. This calculation excludes consumers with no housing data within the given FYs or
consumers whose most recent status was homeless. The percentages of mental health and FSP consumers who
experienced homelessness at any point during the given FY were also computed.
Note that a consumer who was most recently homeless would not be included in the first indicator for most recent
housing status, whereas a consumer who was previously homeless and more recently reported as not homeless
would be included.
Data Sources
Client & Service Information (CSI): H-‐01.0 County / City / Mental Health Plan Submitting Record; H-‐02.0 County
Client Number; C-‐03.0 Date of Birth; P-‐01.0 Date Completed; P-‐09.0 Living Arrangement
Data Collection and Reporting (DCR) Key Event Tracking (KET): 1.01 Global ID; 1.02 Assessment ID; 1.07 Age Group;
3.01 CountyID; 3.06 Assessment Date; 5.01 DateResidentialChange; 5.02 Current
Review of Existing Data
These data were taken from the Key Event Tracking (KET) updates for FSP consumers and the periodic updates for
all mental health consumers, limited to the given fiscal year. Any consumer who did not have an update available
during the year was not included. Data sources are likely to be sustained in the foreseeable future, providing a
consistent source for tracking system performance moving forward. Taking a conservative approach, we
considered cases without valid data “missing.” (These particular consumers have an update, but the updates do
not include housing information.) It should be noted that the data reporting and collection practices currently in
place do not allow for a distinction between missing data from unreported changes in housing status and blank
values from standard data entry practices. This is especially notable in the KET updates for FSP consumers, leading
to large percentages of “missing” data. These results should be interpreted cautiously. In particular, there is the
risk of systematic bias in underreporting certain housing statuses.
Analytic Potential of Indicator
Data across service years support analysis of the distribution and change of housing statuses, including
homelessness, among consumers.
Indicator Displays
The first set of charts displays the most recently reported non-‐homeless housing statuses of consumers, by
percentage, during each fiscal year. The second set displays the percentages of consumers who were reported as
experiencing homelessness at any time during the fiscal year.
21
A comparison of the two fiscal years indicates relatively steady housing rates across the entire
population of consumers. Of the housing options, most children, TAY, adults, and older adults
reside in a house or apartment. This category includes consumers who live fully autonomously or
receive some level of structured support. Group settings were the next most frequent option. The
least common category for children and TAY was housing through foster care (children more than
TAY). In rare instances, adults and older adults were identified as being housed through foster care
also.
Figure 3.1 – Most recent housing status excluding homelessness, all consumers (CSI)
100%&
8.9%& 7.9%& 11.7%& 11.7%&
90%& 19.0%& 19.6%& 16.7%& 16.2%&
9.8%& 9.5%& 0.1%& 0.1%&
0.2%& 0.1%&
80%& 2.6%& 2.6%&
70%&
60%&
50%&
88.2%& 88.2%&
40%& 81.4%& 82.6%& 78.4%& 77.8%& 83.1%& 83.7%&
30%&
20%&
10%&
0%&
Child& Child&& TAY& TAY&& Adult&& Adult& Older& Older&
&08309& 09310& 08309& 09310& 08309& 09310& Adult& Adult&
&08309& 09310&
House&or&Apartment& Foster& Group&SeFng&
Unknown/Missing for FY 2008-‐09 = 15.7% (n = 12,837) for children; 14.5% (n = 9,063) for TAY; 16.1% (n = 22,258)
for adults; and 22.2% (n = 4,057) for older adults
Unknown/Missing for FY 2009-‐10 = 16.4% (n = 14,848) for children; 14.2% (n = 10,485) for TAY; 15.3% (n = 23,233)
for adults; and 21.2% (n = 4,501) for older adults∗
The subset of consumers enrolled in FSPs showed much more variation in housing status between
the two fiscal years compared. Although children were more likely to live with family, TAY housing
oscillated between family and group settings. Among adults and older adults, the group setting was
more prevalent, followed by independent living. However, caution should be used in attempting to
directly compare these results for FSP consumers with the previous results for all consumers. The
FSP data contained more refined information, which led to more finely grained categories.
Additionally, the amount of missing or unknown data for FSP consumers increased dramatically
∗ We cannot distinguish between KETs “for a change in housing” and those “not for a change in housing”
because multiple status changes (for housing, employment, etc.) can and were inputted in each KET. Both
unknown and missing are included here to be thorough.
22
from the 2008-‐09 fiscal year to the 2009-‐10 fiscal year. Any changes in the percentages from year
to year should be interpreted cautiously.
Figure 3.2 – Most recent housing status excluding homelessness, FSP consumers only (DCR)
100%%
90%% 21.9%% 24.5%%
80%% 42.5%%
46.8%%
10.0%% 53.7%% 53.6%% 51.4%%
70%% 60.2%%
2.1%% 15.2%%
60%% 0.8%%
2.0%%
1.1%%
50%% 0.0%%
20.5%% 0.0%% 0.0%%
20.1%%
40%% 0.0%%
66.0%%
30%% 59.5%% 37.8%% 35.7%% 45.2%%
35.8%%
20%%
32.1%% 35.0%%
10%%
8.6%% 10.7%%
3.4%% 4.1%%
0%%
Child%% Child% TAY% TAY%% Adult%% Adult% Older% Older%
08309% %09310% %08309% 09310% 08309% 09310% Adult%% Adult%%
08309% 09310%
With%Family% Independent% Foster% Group%SeHng%
Unknown/Missing for FY 2008-‐09 = 71.6% (n = 1,497) for children; 44.6% (n = 1,300) for TAY; 30.5% (n = 1,936) for
adults, and 43.2% (n = 448) for older adults
Unknown/Missing for FY 2009-‐10 = 73.2% (n = 2,301) for children; 50.6% (n = 2,126) for TAY, 37.9% (n = 3,085) for
adults; and 50.9% (n = 687) for older adults
In the population of all consumers, the percentages of each age category who experienced
homelessness remained fairly stable across the two fiscal years examined. For FSP consumers only,
the percentages of those who experienced homelessness show a decline in every age category.
However, as previously noted, there is also an increase of unknown or missing data from one year
to the next. Considering that the increase in such data is larger than the suggested decrease in
homelessness, there may not be enough evidence to support a conclusion of decrease in
homelessness among FSP consumers between the two years.
23
Figure 3.3 – Experienced homelessness at any point during the year, all consumers (CSI)
30%%
25%%
20%%
FY%2008<09%
15%%
FY%2009<10%
8.9%%
10%% 8.1%%
4.7%%4.7%%
5%% 3.4%%3.3%%
0.5%%0.6%%
0%%
Child% TAY% Adult% Older%Adult%
Unknown/Missing for FY 2008-‐09 = 15.7% (n = 12,837) for children; 14.5% (n = 9,063) for TAY; 16.1% (n = 22,258)
for adults; and 22.2% (n = 4,057) for older adults
Unknown/Missing for FY 2009-‐10 = 16.4% (n = 14,848) for children; 14.2% (n = 10,485) for TAY; 15.3% (n = 23,233)
for adults; and 21.2% (n = 4,501) for older adults
Figure 3.4 – Experienced homelessness at any point during the year, FSP consumers only (DCR)
30%%
25%% 23.6%% 24.0%%
19.7%%
20%% 18.7%%
FY%2008<09%
15%% 13.1%%
FY%2009<10%
9.1%%
10%%
6.7%%
5.7%%
5%%
0%%
Child% TAY% Adult% Older%Adult%
Unknown/Missing for FY 2008-‐09 = 71.6% (n = 1,497) for children; 44.6% (n = 1,300) for TAY; 30.5% (n = 1,936) for
adults, and 43.2% (n = 448) for older adults
Unknown/Missing for FY 2009-‐10 = 73.2% (n = 2,301) for children; 50.6% (n = 2,126) for TAY; 37.9% (n = 3,085) for
adults; and 50.9% (n = 687) for older adults
24
Priority Indicator 4: Arrest Rates
Indicator Summary
This indicator provides the proportion of youth, adults, and older adults who reported being arrested 12 months
prior to receiving services and the proportion of youth, adults, and older adults who reported being arrested since
beginning services.
For calculations involving consumer perception surveys, this indicator includes only youth, adults, and older adults
who reported receiving services for 6 to 12 months. This indicator provides information regarding whether the
proportion of arrested clients has increased or decreased after 6 to 12 months of service.
For calculations involving Full Service Partnership consumers, this indicator tracks arrests prior to enrollment using
intake data. This indicator accounts for consumers enrolled during the target fiscal years for which PAF surveys are
available.
Indicator Calculation
Consumer Perception Surveys (CPS)
• The number of reported arrest 12 months prior to services divided by the total number of youth, adults, and
older adults for who there was data
• The number of reported arrest since beginning services divided by the total number of youth, adults, and older
adults for who there was data
Note: Clients were surveyed multiple times during the 2008 – 2009 fiscal year. However, only one survey
administration was used to get both the proportion of clients who reported being arrested 12 months prior to
beginning services and since receiving services.
Age groupings are as follows:
• Youth, 1 – 25 years
• Adult, 26 – 59 years
• Older adult, 60 and above
Data Collection and Reporting (DCR)
• The number of youth (children and TAY), adults, and older adults reporting arrests 12 months prior to
enrollment divided by the total number of unique clients for who there was data
• The number of youth (children and TAY), adults, and older adults reporting arrests 12 months prior to the
past 12 months divided by the total number of unique clients for who there was data
Note: In rare cases where two surveys were entered for one client, only the earliest entry was used in calculations.
Data Sources
Consumer Perception Survey (CPS) for Youth, Adults, and Older Adults Data Fields: HowLong, LES12AREST,
LES12PSTAREST
Data Collection and Reporting (DCR PAF NONRES): Age_Group, ArrestPast12, ArrestPrior12
Review of Existing Data
Consumer Perception Surveys (CPS)
• Data sources likely to be sustained
• Data relevant to populations of interest
• Approximately 16% missing or unknown values for youth
25
• Approximately 14.5% missing or unknown values for adult
• Approximately 18.5% missing or unknown values for older adult
Data Collection and Reporting (DCR)
• Data sources likely to be sustained
• Data relevant to populations of interest
• On average, 5% missing or unknown values for youth
• On average, 2% missing or unknown values for adults
• On average, 5.5% missing or unknown values for older adults
Analytic Potential of Existing Data
For both data sources
• Analysis across time possible
• Analysis among specific service populations not possible
• State and county individual level analysis possible
Note: As of the submission of this report, a new calculation has been proposed to examine arrest rates.
The proposed calculation would use FSP-‐DCR data during consumers’ enrollment (not intake as it is
presented here). An updated indicator will be available shortly.
26
Figure 4.1 – Proportion of youth (children and TAY) who were arrested prior to beginning services
and since receiving services, FY 2008-‐09 (CPS)
100%
87.7%
85.7%
90%
80%
70%
60%
50%
No
40%
30% Yes
14.3%
20% 12.3%
10%
0%
Arrested 12 months prior to Arrested since receiving
services services
(n = 3,352) (n = 3,305)
Missing/unknown for Arrested 12 months prior to services = 16.5% (n = 651)
Missing/unknown for Arrested since receiving services = 15.4% (n = 604)
Figure 4.2 – Proportion of adults who were arrested prior to beginning services and since receiving
services, FY 2008-‐09 (CPS)
100% 90.5%
84.9%
90%
80%
70%
60%
50%
No
40%
30% Yes
16.0%
20%
9.5%
10%
0%
Arrested 12 months prior to Arrested since receiving
services services
(n = 2,904) (n = 2,940)
Missing/unknown for Arrested 12 months prior to services = 15% (n = 514)
Missing/unknown for Arrested since receiving services = 14% (n = 478)
27
Figure 4.3 – Proportion of older adults who were arrested prior to beginning services and since
receiving services, FY 2008-‐09 (CPS)
100% 93.8% 97.4%
90%
80%
70%
60%
50%
No
40%
30% Yes
20%
6.3%
10% 2.6%
0%
Arrested 12 months prior to Arrested since receiving
services services
(n = 272) (n = 269)
Missing/unknown for Arrested 12 months prior to services = 18.1% (n = 60)
Missing/unknown for Arrested since receiving services = 19% (n =63)
Across the three age groups, most survey respondents (at least 85%) reported that they had not
been arrested within 12 months prior to services. More respondents (at least 88% in each age
group) reported that they had not been arrested since receiving services. Of the three age groups,
older adults had the lowest arrest rates.
28
Available DCR data shows that there were fewer arrests among adults and older adults from “prior
to the past 12 months” to “the past 12 months.”
Figure 4.4 -‐ Proportion of youth (Children and TAY) who were arrested within the past 12 months and
12 months prior (DCR)
100%
90%
80%
70%
60%
50% FY 2008-‐09
40%
FY 2009-‐10
25.8%
30% 20.6% 19.2% 22.3%
20%
10%
0%
Arrested prior to Arrested during
the past 12 months the past 12 months
Missing/Unknown for FY 2008-‐09: Arrested during the past 12 months = 7.8% (n = 384); Arrested prior to the past
12 months = 2.5% (n = 121)
Missing/Unknown for FY 2009-‐10: Arrested during the past 12 months = 2.0% (n = 131); Arrested prior to the past
12 months = 2.8% (n = 182)
Figure 4.5 – Proportion of adults who were arrested within the past 12 months and 12 months prior
(DCR)
100%
90%
80%
70%
60%
50% 41.0% 41.2% FY 2008-‐09
40%
25.8% FY 2009-‐10
30%
20.0%
20%
10%
0%
Arrested prior to Arrested during
the past 12 months the past 12 months
Missing/Unknown for FY 2008-‐09: Arrested during the past 12 months = 2.6% (n = 125); Arrested prior to the past
12 months = 1.4% (n = 69)
Missing/Unknown for FY 2009-‐10: Arrested during the past 12 months = 1.7% (n = 98); Arrested prior to the past 12
months = 1.3% (n = 75)
29
Figure 4.6 Proportion of older adults who were arrested within the past 12 months and 12 months
prior (DCR)
100%
90%
80%
70%
60%
50% FY 2008-‐09
40%
FY 2009-‐10
30% 21.4% 20.2%
20%
6.1% 6.3%
10%
0%
Arrested prior to Arrested during
the past 12 months the past 12 months
Missing/Unknown for FY 2008-‐09: Arrested during the past 12 months = 5.1% (n = 36); Arrested prior to the past 12
months = 6.1% (n = 43)
Missing/Unknown for FY 2009-‐10: Arrested during the past 12 months = 3.6% (n = 29); Arrested prior to the past 12
months = 6.8% (n = 55)
30
Discussion: Consumer Indicators
Domain: Education and Employment
Education – In the absence of data that tell how many days a youth attended or was absent from
school, the evaluation team used suspension/expulsion counts collected through consumer
perception surveys. Thus, findings only capture youths who completed surveys. Attendance among
FSP consumers was captured by estimates of how often youth, including TAY 18 years old and
younger, attended school. No numerical values were available; rather consumers responded
“always,” “mostly,” or “sometimes” attends. These findings have limited reach. (The information
that is sought – attendance – is not currently collected. Available data measure something other
than attendance.) The type of data needed for this calculation begins with survey revisions. Or the
indicator definition might be revised to accommodate existing data and expectations of what the
data can provide.
Employment – DCR data provided robust information with which to calculate paid and nonpaid
employment rates across FYs 2008-‐09 and 2009-‐10. Of the small percentage of all consumers and
FSP consumers who were employed, nearly all received pay for their work. The variables used
provide information regarding the proportion of employed consumers at any given point in the
fiscal years. However, variables do not provide a sense of how long they held a particular
employment status. A close examination of the data indicated that consumers, who are surveyed
multiple times during each fiscal year, maintained their employment statuses for much of the year.
Domain: Homelessness and Housing
There are some outstanding questions regarding the accuracy and reliability of the data in
reflecting consumers’ housing status. The data used in the calculation were collected sporadically.
For FSP consumers, these data were collected through Key Event Tracking (KET); for CSI
consumers, through periodic updates. However, feedback from counties suggests that a uniform
standard for such updates does not exist. This reduces confidence that KET and DCR data faithfully
and completely capture a description of a status so transitory as homelessness. In particular, it
would be reasonable to expect that those consumers at highest risk would also be least likely to be
represented in such periodic updates. There are, then, two issues that require further study before
substantive claims based on these data can be made: (1) the standard practices for meriting and
recording such periodic updates; and (2) the effectiveness of these practices in faithfully and
completely representing the consumer population.
Domain: Arrest Rates
Consumer perception surveys only provided arrest information about persons who completed
surveys. Although arrest rates suggest that consumers do not often interact with law enforcement
in this way, it is a less accurate estimate than what the team would find using a more
comprehensive dataset such as the CSI. The evaluation team has identified possible additional CSI
data from which to glean arrest rates. However, the data were not as complete during the fiscal
years identified. Subsequent reports would benefit from diligent tracking of arrests within the CSI
and an expansion of the definition to include incidents that lead to “jail,” “juvenile detention,”
“incarceration,” “Department of Juvenile Justice” intervention and the like. DCR data provided
additional insights into arrests, but information was limited. Arrest data are available in intake
forms, which do not necessarily capture activities that take place during services.
31
Priority Indicators Analysis and Findings: Community Mental
Health System Indicators
Priority Indicator 5: Demographic Profile of Consumers Served
Indicator Summary
This indicator profiles the demographics (race/ethnicity, age, and gender) of all mental health consumers and Full
Service Partnership consumers served during FYs 2008-‐09 and 2009-‐10. It summarizes levels of service to
California’s diverse population supported by the community mental health system.
Indicator Calculation
• The frequencies of all mental health consumers and FSP consumers served in FYs 2008-‐09 and 2009-‐10 were
calculated overall.
• Additionally, the proportion of consumers represented by race/ethnicity, age, and gender categories was
calculated by dividing the number of consumers within each demographic category by all consumers served.
Proportions were calculated for both service populations (all consumers and FSPs) and both fiscal years
examined (see Figures 5.1-‐5.6 below).
Data Sources
Client & Service Information (CSI) Data Fields: H-‐01.0 County / City / Mental Health Plan Submitting Record; H-‐02.0
County Client Number; C-‐05.0 Gender; C-‐09.0 Ethnicity; C-‐10.0 Race; S-‐05.0 Mode of Service; S-‐16.0 From / Entry
Date; S-‐17.0 Through / Exit Date; S-‐23.0 Date of Service.
Data Collection and Reporting (DCR) Data Fields: 1.01 Global ID; 1.02 Assessment ID; 1.04 Date Partnership Status
Change; 1.05 Partnership Status; 1.07 Age Group; 1.08 Assessment Type; 2.01 CSI Date of Birth; 2.02 Gender; 2.03
CSIRace1; 2.04 CSIRace2; 2.05 CSIRace3; 2.06 CSIRace4; 2.07 CSIRace5; 2.10 CSI Hispanic; 3.01 County ID; 3.05
Partnership Date; 3.06 Assessment Date.
Review of Existing Data
• Data sources likely to be sustained
• Data relevant to populations of interest (all consumers and FSPs)
• Data available across multiple service years
• Less than 10% missing or unknown values (see Appendix D for details of recoding race/ ethnicity data fields)
Analytic Potential of Indicator
• Analysis across time possible
• Analysis among specific service populations possible (e.g., all consumers, FSPs, demographic groups)
• State-‐ and county-‐level analysis possible
32
Figures 5.1 and 5.2 display the race and ethnicity of mental health and FSP consumers served in FYs
2008-‐09 and 2009-‐10. More white and Hispanic/Latino consumers were served compared to other
racial or ethnic categories within each fiscal year analyzed.
Figure 5.1 – Race/ethnicity of mental health consumers
100%
90%
80%
70%
60%
50%
36.4%
40% 36.6%
29.0% 30.1%
30% 16.9% 17.5%
20%
7.2% 7.4%
10% 6.6% 5.2% 2.6%
0.3% 0.3% 0.7% 0.7% 2.5%
0%
White Hispanic / Asian Pacific Black American Mulmrace Other
Lamno Islander Indian
FY 2008-‐09 (n = 644,802) FY 2009-‐10 (n = 647,246)
FY 2008-‐09 Unknown/Missing = 7.3% (n = 49,303); FY 2009-‐10 Unknown/Missing = 8.7% (n = 60,490)
Figure 5.2 – Race/ethnicity of FSP consumers
100%
90%
80%
70%
60%
50% 38.1%
37.6%
40% 27.7%
30% 26.6% 20.5%
18.9%
20% 5.9% 7.9%
5.2% 7.2%
10%
0.2% 0.2% 0.6% 0.6% 1.4% 1.4%
0%
White Hispanic / Asian Pacific Black American Mulmrace Other
Lamno Islander Indian
FY 2008-‐09 (n = 20,422) FY 2009-‐10 (n = 28,357)
FY 2008-‐09 Unknown/Missing = 5.4% (n = 1,177); FY 2009-‐10 Unknown/Missing = 5.5% (n = 1,660)
33
Figures 5.3 and 5.4 display all mental health and FSP consumers served within age group during
FYs 2008-‐09 and 2009-‐10. More adults were served compared to other age groups within each
fiscal year analyzed.
Figure 5.3 – Mental health consumers by age group
100%
90%
80%
70%
60%
47.9% 46.6%
50%
40%
26.8% 27.7%
30%
18.8% 19.2%
20%
6.4% 6.6%
10%
0%
Children TAY Adults Older Adults
FY 2008-‐09 (n = 673,941) FY 2009-‐10 (n = 632,807)
FY 2008-‐09 Unknown/Missing = 0.0% (n = 133); FY 2009-‐10 Unknown/Missing = 9.4% (n = 65,968)
Figure 5.4 – FSP consumers by age group
100%
90%
80%
70%
60%
48.1% 47.1%
50%
40%
30% 21.7% 22.7% 22.8% 23.4%
20%
7.4% 6.8%
10%
0%
Children TAY Adults Older Adults
FY 2008-‐09 (n = 21,599) FY 2009-‐10 (n = 30,017)
34
Figures 5.5 and 5.6 display gender of mental health and FSP consumers served in FYs 2008-‐
09 and 2009-‐10. More male consumers were served compared to female consumers within
each fiscal year analyzed.
Figure 5.5 – Mental health consumers by gender7
100%
90%
80%
70%
60% 51.9% 52.1%
48.1% 47.9%
50%
40%
30%
20%
10%
0%
Female Male
FY 2008-‐09 (n = 672,519) FY 2009-‐10 (n = 697,695)
FY 2008-‐09 Other/Unknown/Missing = 0.2% (n = 1,555); FY 2009-‐10 0ther/Unknown/Missing = 0.2% (n = 1,080)
Figure 5.6 – FSP consumers by gender
100%
90%
80%
70%
55.7% 55.8%
60% 44.3% 44.2%
50%
40%
30%
20%
10%
0%
Female Male
FY 2008-‐09 (n = 20,939) FY 2009-‐10 (n = 29,038)
FY 2008-‐09 Other/Unknown/Missing = 3.1% (n = 660); FY 2009-‐10 Other/Unknown/Missing = 3.3% (n = 979)
7 Consumer stakeholders felt it important to note that “transgender” is not currently a category that is
available in the datasets. Male and female categories might incorporate this population, but it cannot be
distinguished as a third group from existing data.
35
Priority Indicator 6: Demographic Profile of New Consumers
Indicator Summary
This indicator profiles new mental health consumers (i.e., served during FY, without service for prior six months)
overall and full service partners (FSPs) served during FYs 2008-‐09 and 2009-‐10.
Indicator Calculation
• For all mental health consumers, CSI data support calculation of new (i.e., did not receive services for 6
months prior to given FY) versus past consumers (i.e., initial services received prior to the given FY) overall and
within race/ethnicity, age, and gender categories. The frequency of new consumers served was divided by all
previous consumers served, in each fiscal year, to calculate the proportion of new consumers served. This
same calculation was conducted within each demographic category (race/ethnicity, age, and gender), in each
FY (see Figures 6.1 – 6.4 below).
• For FSPs, DCR data support calculation of new (i.e., did not receive services for 6 months prior to given FY)
versus existing (i.e., current Full Service Partners) overall and within race/ethnicity, age, and gender
categories. The frequency of new consumers served was divided by all existing consumers, in each fiscal year,
to calculate the proportion of new consumers served. This same calculation was conducted within each
demographic category (race/ethnicity, age, and gender), in each FY (see Figures 6.5 – 6.8, below).
Data Sources
Client & Service Information (CSI) Data Fields: H-‐01.0 County / City / Mental Health Plan Submitting Record; H-‐02.0
County Client Number; C-‐05.0 Gender; C-‐09.0 Ethnicity; C-‐10.0 Race; S-‐05.0 Mode of Service; S-‐16.0 From / Entry
Date; S-‐17.0 Through / Exit Date; S-‐23.0 Date of Service.
Data Collection and Reporting (DCR) Data Fields: 1.01 Global ID; 1.02 Assessment ID; 1.04 Date Partnership Status
Change; 1.05 Partnership Status; 1.07 Age Group; 1.08 Assessment Type; 2.01 CSI Date of Birth; 2.02 Gender; 2.03
CSIRace1; 2.04 CSIRace2; 2.05 CSIRace3; 2.06 CSIRace4; 2.07 CSIRace5; 2.10 CSI Hispanic; 3.01 County ID; 3.05
Partnership Date; 3.06 Assessment Date.
Review of Existing Data
• Data sources likely to be sustained
• Data relevant to populations of interest (all consumers and FSPs)
• Data available across multiple service years
• Less than 10% missing or unknown values (see Appendix D for details of recoding race/ ethnicity data fields)
Analytic Potential of Indicator
• Analysis across time possible
• Analysis among specific service populations possible (e.g., all consumers, FSPs, demographic groups)
• State-‐ and county-‐level analysis possible
36
All Consumers – Data Source: Client & Service Information (CSI)
Figures 6.1 – 6.4 present new mental health consumers served during FY 2008-‐09 and 2009-‐10
overall and by demographic categories. New consumers (i.e., did not receive services for six months
prior to given FY) represented a smaller proportion of all consumers served compared to previous
consumers (i.e., initiated services prior to given FY), in each FY examined. New white and
Hispanic/Latino consumers represented greater proportions of all new consumers served than
other racial or ethnic groups in both fiscal years (see Figure 5.1). More new adult consumers were
served in each FY compared to other age groups. More new male consumers were served in each FY
compared to female consumers.
Figure 6.1 – New and continuing mental health consumers served
100%
84.3%
90%
78.3%
80%
70%
60%
50%
40%
30% 21.7%
15.7%
20%
10%
0%
FY 2008-‐09 FY 2009-‐10
(n = 1,148,527) (n = 1,440,215)
Previous Consumers New Consumers
Figure 6.2 – Race/ethnicity of new mental health consumers
100%
90%
80%
70%
60%
50%
40% 36.1% 3 5.2%3 4.2% 35.8%
30%
20%
8.7% 8.5% 7.8% 7.8% 8.4% 8.5%
10% 2.9% 3.0% 0.2% 0.2% 0.7% 0.7%
0%
White Hispanic / Asian Pacific Black American Mulmrace Other
Lamno Islander Indian
FY 2008-‐09 (n = 227,994) FY 2009-‐10 (n = 206,738)
FY 2008-‐09 Unknown/Missing: 8.4% (n = 21,034); FY 2009-‐10 Unknown/Missing: 8.3% (n = 19,159)
37
Figure 6.3 – New mental health consumers by age group
100%
4.6% 4.3%
90%
80%
42.0% 40.1%
70%
60% Older Adults
50% Adults
22.3%
22.6%
40%
TAY
30%
Children
20%
30.8% 33.2%
10%
0%
FY 2008-‐09 FY 2009-‐10
(n = 248,938) (n = 225,787)
FY 2008-‐09 Unknown/Missing 0.0% (n = 90); FY 2009-‐10 Unknown/Missing 0.0% (n = 110)
Child and TAY consumers represent larger proportions of all new consumers (Figure 6.3) compared
to the proportions these age groups represent among all consumers served in each FY analyzed
(see Figure 5.3).
Figure 6.4 – Gender of new mental health consumers
100%
90%
80%
52.9% 52.7%
70%
60%
50% Male
40%
Female
30%
47.1% 47.3%
20%
10%
0%
FY 2008-‐09 FY 2009-‐10
(n = 248,464) (n = 225,389)
FY 2008-‐09 Other/Unknown/Missing = 0.2% (n = 564); FY 2009-‐10 Other/Unknown/Missing = 0.2% (n = 508)
Male consumers represent a larger proportion of all new consumers (Figure 6.4) compared to the
proportion males represent among all consumers served in each FY analyzed (see Figure 5.5).
38
FSP Consumers – Data Source: Data Collection and Reporting (DCR)
Figures 6.5 – 6.8 present new FSP consumers (i.e., did not receive services for six months prior to
given FY) served during FYs 2008-‐09 and 2009-‐10 overall and by race/ethnicity, age, and gender
categories. New FSPs represented a smaller proportion of all consumers served compared to
continuing consumers (i.e., current Full Service Partners), in each FY examined. New white and
Hispanic/ Latino consumers represented greater proportions of all new consumers served than any
other racial or ethnic groups in both fiscal years examined. More new adult consumers were served
in each FY compared to other age groups. More new male consumers were served in each FY
compared to female consumers.
Figure 6.5 – New and continuing FSP consumers served
100%&
90%&
80%&
70%&
52.4%& 57.4%&
60%&
50%& 47.6%& 42.6%&
40%&
30%&
20%&
10%&
0%&
FY&200802009&& FY&200902010&&
(n&=&21,599)& (n&=&30,017)&
Con8nuing&Consumers& New&Consumers&
FY 2008-‐09 Unknown/Missing = 5.7% (n = 2,673); FY 2009-‐10 Unknown/Missing = 14.9% (n = 7,032)
Figure 6.6 – Race/ethnicity of new FSP consumers
100%%
90%%
80%%
70%%
60%%
50%% 39.5%%
36.3%%
40%%
28.0%% 28.5%%
30%%
19.0%%
16.0%%
20%% 5.5%%4.5%% 8.5%%9.0%%
10%% 0.2%%0.2%% 1.1%%0.9%% 1.3%%1.4%%
0%%
White%% Hispanic%/% Asian% Pacific% Black% American% Mul;race% Other%
La;no% Islander% Indian%
FY%2008L09%% FY%2009L10%%
(n%=%9,649)% (n%=%11,904)%
39
FY 2008-‐09 Unknown/Missing = 6.1% (n = 628) FY 2009-‐10 Unknown/Missing = 6.8% (n = 873)
Hispanic / Latino, American Indian, and multiracial consumers represent a larger proportion of all
new consumers (Figure 6.6) compared to the proportions these racial/ethnic groups represent
among all consumers served in each FY analyzed (see Figure 5.2).
Figure 6.7 – New FSP consumers by age group ____
100.0%
6.7% 6.1%
90.0%
80.0%
70.0% 45.6% 43.5%
Older Adults
60.0%
Adults
50.0%
40.0% TAY
24.7%
24.3%
30.0% Children
20.0%
10.0% 23.4% 25.7%
0.0%
FY 2008-‐09 (n = 10,277) FY 2009-‐10 (n = 12,777)
Child and TAY consumers together represent larger proportions of all new consumers (Figure 6.7)
compared to the proportions these age groups represent among all consumers served in each FY
analyzed (see Figure 5.4).
Figure 6.8 – Gender of new FSP consumers
100%%
90%%
80%% 44.6%% 43.5%%
70%%
60%%
50%% Female%
40%%
Male%
30%% 55.4%% 56.5%%
20%%
10%%
0%%
FY%2008009%% FY%2009010%%
(n%=%9,898)% (n%=%12,184)%
FY 2008-‐09 Other/Unknown/Missing = 3.7% (n = 379); FY 2009-‐10 Other/Unknown/Missing = 4.6% (n = 593)
40
In FY 2008-‐09, female consumers represented a larger proportion of all new consumers (Figure
6.8) compared to the proportion they represented among all consumers served (see Figure 5.6). In
FY 2009-‐10, male consumers represented a larger proportion of all new consumers (Figure 6.8)
compared to the proportion they represented among all consumers served (see Figure 5.6).
Service levels and demographic characteristics of new mental health consumers served can indicate
the changing makeup of the service population and potentially provide insight regarding the extent
to which unserved and underserved populations are entering the community mental health system.
41
Priority Indicator 7: Penetration of Mental Health Services
Indicator Summary
This indicator details rates of service access relative to estimates of need for service among Californians earning
less than 200% of the federal poverty income level. This metric is intended to show the extent to which service
access is in line with the level of need for services.
Indicator Calculation
The number of all mental health consumers served (i.e., at least one service received during FY) was divided by
estimates of need for service (Holzer Targets) among Californians earning less than 200% of the federal poverty
income level and among demographic category (i.e., race/ethnicity, age, and gender). (See Figures 7.1-‐7.5 below).
Data Sources
• Client & Service Information (CSI) Data Fields: H-‐01.0 County/City/Mental Health Plan Submitting Record; H-‐
02.0 County Client Number; C-‐05.0 Gender; C-‐09.0 Ethnicity; C-‐10.0 Race; S-‐05.0 Mode of Service; S-‐16.0 From
/ Entry Date; S-‐17.0 Through / Exit Date; S-‐23.0 Date of Service.
• Estimates of need for mental health services (Holzer Targets) among Californians earning less than 200% of
the federal poverty income level.
Review of Existing Data
• Data sources likely to be sustained
• Data appropriate for analysis of all mental health consumers. The estimates of need for service (Holzer
Targets) used are not appropriate points of comparison for FSP service levels.
• Data available across multiple service years
• Less than 10% missing or unknown values (see Appendix D for details of recoding race/ ethnicity data fields)
Analytic Potential of Indicator
• Analysis across time possible
• Analysis among specific service populations possible (e.g., all consumers, FSPs, demographic groups)
• State-‐ and county-‐level analysis possible
42
The ratio of consumers served (i.e., at least one service received during FY) to those estimated to be
in need of service was lower in FY 2009-‐10 than in the previous fiscal year (see Figure 7.1). A
similar pattern is reflected among female and male consumers (see Figure 7.2).
Figure 7.1 – Penetration of services
100%
90%
80%
67.5%
70% 64.5%
60%
50%
40%
30%
20%
10%
0%
FY 2008-‐09 FY 2009-‐10
Consumers Served/Holzer Target
FY 2008-‐09 (686,876/1,018,138)
FY 2009-‐10 (662,409/1,027,663)
Figure 7.2 – Penetration of services by gender
100%%
90%% 82.8%%
78.9%%
80%%
70%%
55.8%% 53.6%%
60%%
50%%
40%%
30%%
20%%
10%%
0%%
FY%2008009% FY%2009010% FY%2008009% FY%2009010%
Female% Male%
FY 2008-‐09 Other/Unknown/Missing = 0.3% (n = 2,107); FY 2009-‐10 Other/Unknown/Missing = 0.2% (n = 1,174)
FY 2008-‐09 FY 2009-‐10
Female (326,589/585,467) (358,180/432,671)
Male (317,101/591,431) (344,164/436,233)
43
Figure 7.3 – Penetration of services by age group
100% 90.6%
86.8%
77.1%
80% 69.9% 73.8%
64.9%
60% 52.8% 52.8%
40%
20%
0%
Children TAY Adult Older Adult
FY 2008-‐09 FY 2009-‐10
FY 2008-‐09 FY 2009-‐10
Children (180,184/341,225) (180,283/341,702)
TAY (128,066/141,346) (125,213/144,214)
Adult (334,916/479,007) (313,465/483,073)
Older Adult (43,605/56,559) (43,287/58,674)
The rate at which consumers were served compared to estimates of need for service was greater
among TAY consumers than any other age group in each fiscal year analyzed. A similar pattern is
reflected among female and male consumers (see Figure 7.2).
Figure 7.4 – Penetration of services by race/ethnicity (FY 2008-‐09)
280.1%
300%
250%
177.3%
200%
145.4%
150%
88.8%
100%
32.6% 47.8% 28.7% 38.4%
50%
0%
White Hispanic/ Black Asian Pacific American Mulmrace Other
Lamno Islander Indian
FY 2008-‐09 Unknown/Missing = 7.9% (n = 54,169)
44
FY 2008-‐09 FY 2009-‐10
White (246,084/277,091) (230,147/276,046)
Hispanic/ Latino (183,432/561,860) (188,121/571,226)
Black (113,067/77,784) (108,649/77,677)
Asian (28,102/58,804) (26,340/59,607)
Pacific Islander (800/2,783) (849/2,851)
American Indian (3,806/9.908) (3,538/10,078)
Multirace (45,415/25,622) (44,542/25,893)
Other (12,001/4,285) (11,024/4,285)
Figure 7.5 -‐ Penetration of services by race/ethnicity (FY 2009-‐10)
300%
257.3%
250%
172.0%
200%
139.9%
150%
83.4%
100%
32.9% 44.2% 29.8% 35.1%
50%
0%
White Hispanic/ Black Asian Pacific American Mulmrace Other
Lamno Islander Indian
FY 2009-‐10 Unknown/Missing = 7.4% (n = 49,199)
Overall, rates of penetration of services were relatively stable across the two fiscal years analyzed.
The rate of penetration overall and among demographic groups can provide an indication of the
extent to which service levels are in line with the level of need. As estimates of the need for mental
health services statewide become more accurate and additional service years are analyzed, this
indicator may become more informative for those planning operating and monitoring services.
45
Priority Indicator 8: Access to a Primary Care Physician
Indicator Summary
This indicator details the level of access to a primary care physician reported among FSP consumers, during FYs
2008-‐09 and 2009-‐10.
Indicator Calculation
The ratio of FSP consumers indicating access to a primary care physician at any point during a fiscal year to all FSP
consumers served during a fiscal year was calculated (see Figure 8.1). This ratio was also calculated within
demographic categories (i.e., race/ethnicity, age, and gender) for each FY (see Figures 8.2-‐8.4 below).
Data Sources
Data Collection and Reporting (DCR) Data Fields: 1.01 Global ID; 1.02 Assessment ID; 1.04 Date Partnership Status
Change; 1.05 Partnership Status; 1.07 Age Group; 1.08 Assessment Type; 2.01 CSI Date of Birth; 2.02 Gender; 2.03
CSIRace1; 2.04 CSIRace2; 2.05 CSIRace3; 2.06 CSIRace4; 2.07 CSIRace5; 2.10 CSI Hispanic; 3.01 County ID; 3.05
Partnership Date; 3.06 Assessment Date; 11.01 PhysicianCurr.
Review of Existing Data
• Data source likely to be sustained
• Data relevant to population of interest (FSPs). Relevant data not available to assess primary care access among
all mental health consumers (e.g., CSI).
• Data available across multiple service years
• More than 10% missing or unknown values within key DCR fields (see Appendix D for details of recoding
race/ethnicity data fields)
Analytic Potential of Indicator
• Analysis across time possible
• Analysis among specific service populations possible (e.g., all consumers, FSPs, demographic groups)
• State-‐ and county-‐level analysis possible
46
Figure 8.1 – FSP access to a primary care physician
100%&
90%&
80%&
67.3%&
70%&
59.7%&&&
60%&
50%&
40%&
30%&
20%&
10%&
0%&
FY&2008009&& FY&2009010&&
(n&=&13,970)& (n&=&19,391)&
FY 2008 -‐09 Unknown/Missing = 35.3% (n = 7,629); FY 2009-‐10 Unknown/Missing = 35.4% (n = 10,626)
Figure 8.2 – FSP access to a primary care physician by age group
100%%
84.8%% 85.6%%
90%% 86.5%%
81.7%%
80%%
63.1%%
70%%
53.4%%
60%% 52.0%%
50%% 47.2%%
40%%
30%%
20%%
10%%
0%%
Children% TAY% Adult% Older%Adult%
FY%2008=09%% FY%2009=10%%
(n%=%13,970)% (n%=%19,391)%
FY 2008 -‐09 Unknown/Missing: 37.1% (n = 8,016); FY 2009-‐10 Unknown/Missing 37.5% (n = 11,258)
47
Figure 8.3 –FSP access to a primary care physician by gender
100.0%
90.0%
80.0%
70.6%
70.0% 64.5% 65.0%
55.9%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
Female Male
FY 2008-‐09 (n = 13,665) FY 2009-‐10 (n = 18,899)
FY 2008 -‐09 Unknown/Missing: 36.2% (n = 7,810); FY 2009-‐10 Unknown/Missing: 36.4% (n = 10,931)
Figure 8.4 – FSP access to a primary care physician by race/ethnicity
100%&
90%&
80%& 71.0%& 68.2%&
69.3%& 68.4%& 67.5%&
70%& 60.3%& 61.6%& 64.1%& 60.9%& 64.1%& 62.0%& 66.6%& 61.4%&
60%& 53.8%&
50%& 45.5%&
40.6%&
40%&
30%&
20%&
10%&
0%&
White& Hispanic/ Asian& Pacific&Islander& Black& American& Mul;race& Other&
La;no& Indian&
FY&2008L09&& FY&2009L10&&
(n&=&13,970)& (n&=&19,391)&
FY 2008-‐09 Unknown/Missing 36.7% (n = 7,924); FY 2009-‐10 Unknown/Missing 37.0% (n = 11,112)
Information regarding primary care access overall and among various demographic groups can
provide insight into the relative success of FSP programs in connecting consumers to primary
health care.
48
Priority Indicator 9: Perceptions of Access to Services
Indicator Summary
This indicator provides insight into consumer and family perceptions of access to mental health services, among a
sample of those currently accessing the community mental health system.
Indicator Calculation
• Family members/caregivers and TAY respondents’ ratings (1–Strongly Disagree to 5–Strongly Agree) of two self-‐
report items (specified in the Data Sources section below) were averaged to calculate aggregate ratings of
perceptions of access to mental health services (see Figures 9.1-‐9.2 and Tables 9.1-‐9.2 below). Aggregate
ratings were calculated for each fiscal year. Ratings of 3.5 or greater generally indicate positive perceptions. This
calculation method is in line with previous DHCS practices.
• Adult and Older Adult respondents’ ratings (1-‐Strongly Disagree to 5-‐Strongly Agree) of 14 self-‐report items
(specified under the Data Sources section below) were averaged to calculate aggregate ratings of perceptions of
access to mental health services (see Figures 9.1-‐9.2 and Tables 9.1-‐9.2 below). Aggregate ratings were
calculated for each fiscal year. Ratings of 3.5 or greater generally indicate positive perceptions. This calculation
method is in line with previous DHCS practices.
Data Sources
Consumer Perception Surveys
• Family members/caregivers and TAY self-‐report items analyzed (Youth and Family Member Surveys):
o The location of services was convenient for us.
o Services were available at times that were convenient for us.
• Adult and older adult self-‐report items analyzed (MHSIP):
o The location of services was convenient (parking, public transportation, distance, etc.).
o Staff were willing to see me as often as I felt it was necessary.
o Staff returned my call in 24 hours.
o Services were available at times that were good for me.
o I was able to get all the services I thought I needed.
o I was able to see a psychiatrist when I wanted to.
Note: Data collected in FYs 2008-‐09 and 2009-‐10 must be interpreted separately because a convenience sampling
method was employed to gather FY 2008-‐09 data and a random sampling method employed to gather data in FY
2009-‐10. 8
Review of Existing Data
• Data source likely to be sustained
• Data relevant to population of interest (i.e., convenience or random sample of all mental health consumers)
• Data available across multiple service years
• More than 10% missing or unknown values within key CPS scales
Analytic Potential of Indicator
• Analysis across time will be possible if the sampling methodology and instrument used are used consistently
each year.
• Analysis among specific service populations possible (e.g., all consumers, demographic groups)
• State and county analysis possible for FY 2008-‐09 (convenience sample), but only state-‐level analysis is possible
in FY 2009-‐10 (random sample)
8 Cowles, E. L., Harris, K., Larsen, C., and Prince, A. (2010). Assessing Representativeness of the Mental Health
Services Consumer Perception Survey.
49
Figure 9.1 – Perceptions of access to services, FY 2008-‐09
Older Adult 4.28 (n = 4,773)
Adult 4.18 (n = 47,878)
TAY 3.99 (n = 24,255)
Family Member/Caregiver 4.35 (n = 36,292)
1 2 3 4 5
Figure 9.2 – Perceptions of access to services, FY 2009-‐10
Older Adult 4.05 (n = 2,489)
Adult 3.81 (n = 1,612)
Family Member/Caregiver 4.07 (n = 1,094)
1 2 3 4 5
Table 9.1 – Perceptions of access to services by race/ethnicity
Family Member/
Caregiver of Children TAY Adult Older Adult
and/or TAY
FY FY FY FY FY FY FY FY
2008-‐09 2009-‐10 2008-‐09 2009-‐109 2008-‐09 2009-‐10 2008-‐09 2009-‐10
4.36 4.07 4.06 4.18 3.69 4.29 4.01
White
(n=13,035) (n=564) (n=7,782) (n=20,190) (n=842) (n=2,381) (n=1,345)
Hispanic / 4.38 4.12 4.04 4.27 3.95 4.44 4.20
Latino (n=17,783) (n=490) (n=10,708) (n=11,400) (n=370) (n=893) (n=414)
4.33 3.98 3.93 4.20 4.05 4.33 4.08
Asian
(n=1,211) (n=57) (n=1,004) (n=3,133) (n=181) (n=332) (n=465)
Pacific 4.34 3.70 4.01 4.24 3.76 4.08 3.69
Islander (n=476) (n=23) (n=487) (n=1,752) (n=26) (n=41) (n=8)
4.34 4.06 3.97 4.22 3.80 4.28 4.01
Black
(n=6,121) (n=160) (n=4,463) (n=6,627) (n=201) (n=472) (n=159)
American 4.32 4.24 4.01 4.14 3.62 4.26 3.87
Indian (n=1,742) (n=69) (n=1,748) (n=2,634) (n=108) (n=185) (n=114)
FY 2008-‐09 Unknown/Missing Values: Family Member/Caregiver 10.9% (n = 4,940), TAY 15.3% (n = 4,740), Adult
19.7% (n = 11,195), Older Adult 22.3% (n = 1,237); FY 2009-‐10 Unknown/Missing Values: Family Member/
Caregiver 6.8% (n = 100), Adult 11.6% (n = 227), Older Adult 14.3% (n = 417)
9 Consumer Perception Surveys were not completed by youth during FY 2009-‐10.
50
Table 9.2 – Perceptions of access to services by gender
Family Member/
Caregiver of Children TAY Adult Older Adult
and/or TAY
FY FY FY FY FY FY FY FY
2008-‐09 2009-‐10 2008-‐09 2009-‐ 2008-‐09 2009-‐10 2008-‐09 2009-‐10
1010
4.35 4.06 4.09 4.24 3.82 4.33 4.09
Female
(n=13,052) (n=399) (n=10,176) (n=22,915) (n=934) (n=2,531) (n=1,586)
4.37 4.08 3.95 4.19 3.80 4.31 3.97
Male
(n=21,115) (n=653) (n=12,116) (n=18,486) (n=631) (n=1,574) (n=771)
FY 2008-‐09 Unknown/Missing Values: Family Member/Caregiver 5.9% (n = 2,125), TAY 8.0% (n = 1,933), Adult
13.5% (n = 6,477), Older Adult 14.0% (n = 668); FY 2009-‐10 Unknown/Missing Values: Family Member/Caregiver
3.8% (n = 42), Adult 2.9% (n = 47), Older Adult 5.3% (n = 132)
Average ratings among most respondent groups, in both fiscal years analyzed, were greater than
3.5, suggesting positive perceptions of access to services. Such consumer-‐driven feedback regarding
the community mental health system provides vital indication of system performance from those
who have received services.
10 Consumer Perception Surveys were not completed by youth during FY 2009-‐10.
51
Priority Indicator 10: Involuntary Status
Indicator Summary
This indicator provides insight into the rates of involuntary status among all mental health consumers during FY
2008-‐09. Involuntary status refers to a legal designation that can be applied to individuals who are found to be a
danger to themselves and/or others, and/or gravely disabled.
Indicator Calculation
The California Department of Health Care Services (DHCS) reports incidents of involuntary status per 10,000
consumers. Such rates are reported here (see Figure 10.1, below).
Data Sources
The California Department of Health Care Services provides reports of incidents of involuntary status (see
http://www.dmh.ca.gov/statistics_and_data_analysis/Involuntary_Detention.asp)
Review of Existing Data
• Data source likely to be sustained
• Data relevant to population of interest (all mental health consumers). Relevant data are not available to
specifically assess involuntary status among FSP consumers.
• Data available across multiple service years
Analytic Potential of Indicator
• Analysis across time will be possible as information from additional fiscal years becomes available from DHCS
• Aggregate data do not allow for analysis among specific (e.g., demographic) service populations
• State-‐ and county-‐level analysis possible
52
Figure 10.1 – Involuntary status per 10,000 consumers, FY 2008-‐09 (NOTE: horizontal scale reduced
for ease of viewing)
Addimonal 14-‐day Intensive (Suicidal) 0.1
14-‐day Intensive Treatment 20.0
72-‐Hour Evaluamon and Treatment -‐ Child 18.4
72-‐Hour Evaluamon and Treatment -‐ Adult 48.6
0.0 100.0
This indicator shows the rate at which these legal designations are used. Further disaggregated of
involuntary status information (e.g., demographics) can provide an indication of the extent to which
these legal status designations may be applied at different rates among various consumer
populations.
53
Priority Indicator 11: Consumer Perceptions of Improvement in Well-‐
Being as a Result of Services
Indicator Summary
This indicator provides insight into consumer and family perceptions of well-‐being (i.e., outcomes, functioning, and
social connectedness) as a result of mental health services.
Indicator Calculation
• Family members/caregivers and TAY respondents’ ratings (1–Strongly Disagree to 5–Strongly Agree) of 11 self-‐
report items (specified in the Data Sources section below) were averaged to calculate aggregate ratings of
perceptions of well-‐being as a result of mental health services (see Figures 11.1-‐11.2 and Tables 11.1-‐11.2
below). Aggregate ratings were calculated for each fiscal year. Ratings of 3.5 or greater generally indicate
positive perceptions. This calculation was developed to approximate domains of well-‐being many respondents
noted in their feedback to our initial reports.
• Adult and older adult respondents’ ratings (1–Strongly Disagree to 5–Strongly Agree) of 14 self-‐report items
(specified in the Data Sources section below) were averaged to calculate aggregate ratings of perceptions of
well-‐being as a result of mental health services (see Figures 11.1-‐11.2 and Tables 11.1-‐11.2 below). Aggregate
ratings were calculated for each fiscal year. Ratings of 3.5 or greater generally indicate positive perceptions.
This calculation was developed to approximate domains of well-‐being many respondents noted in their
feedback to our initial reports.
Data Sources
Consumer Perception Surveys
• Family members/caregivers and TAY self-‐report items analyzed (YSS/YSS-‐F):
o My child is better at handling daily life.
o My child gets along better with family members.
o My child gets along better with friends and other people.
o My child is doing better in school and/or work.
o My child is better able to cope when things go wrong.
o I am satisfied with our family life right now.
o My child is better able to do things he or she wants to do.
o I know people who will listen and understand me when I need to talk.
o I have people that I am comfortable talking with about my child's problems.
o In a crisis, I would have the support I need from family or friends.
o I have people with whom I can do enjoyable things.
• Adult and older adult self-‐report items analyzed (MHSIP):
o I deal more effectively with daily problems.
o I am better able to control my life.
o I am better able to deal with crisis.
o I am getting along better with my family.
o I do better in social situations.
o I do better in school and/or work.
o I do things that are more meaningful to me.
o I am better able to take care of my needs.
o I am better able to handle things when they go wrong.
o I am better able to do things that I want to do.
o I am happy with the friendships I have.
o I have people with whom I can do enjoyable things.
54
o I feel I belong in my community.
o In a crisis, I would have the support I need from family or friends.
• Note: Data collected in FYs 2008-‐09 and 2009-‐10 must be interpreted separately because a convenience
sampling method was employed to gather FY 2008-‐09 data and a random sampling method employed to
gather data in FY 2009-‐10.11
Review of Existing Data
• Data source likely to be sustained (i.e., most items analyzed for this indicator are included in the August 2012
survey administration)
• Data relevant to population of interest (i.e., convenience or random sample of all mental health consumers)
• Data available across multiple service years
• More than 10% missing or unknown values within key CPS scales
Analytic Potential of Indicator
• Analysis across time will be possible if the sampling methodology and instrument used is employed in a
consistent manner each year
• Analysis among specific service populations possible (e.g., all consumers, demographic groups)
• State and county analysis possible for FY 2008-‐09 (convenience sample), but only state-‐level analysis is
possible in FY 2009-‐10 (random sample)
11 Cowles, E. L., Harris, K., Larsen, C., and Prince, A. (2010). Assessing Representativeness of the Mental Health
Services Consumer Perception Survey.
55
Figure 11.1 – Perceptions of well-‐being, FY 2008-‐09
Older Adult 3.92 (n= 4,523)
Adult 3.84 (n= 47,012)
TAY 3.85 (n= 24,270)
Family Member/Caregiver 3.80 (n= 35,746)
1.00 2.00 3.00 4.00 5.00
Figure 11.2 – Perceptions of well-‐being, FY 2009-‐10
Older Adult 3.73 (n= 2,450)
Adult 3.50 (n= 1,611)
Family Member/Caregiver 3.57 (n= 1,095)
1 2 3 4 5
Table 11.1 – Perceptions of well-‐being by race/ethnicity
Family Member/
Caregiver of Children TAY Adult Older Adult
and/or TAY
FY FY FY FY FY FY FY FY
2008-‐09 2009-‐10 2008-‐09 2009-‐1012 2008-‐09 2009-‐10 2008-‐09 2009-‐10
3.73 3.52 3.85 3.84 3.41 3.91 3.70
White
(n=12,860) (n=562) (n=7,774) (n=20,021) (n=842) (n=2,330) (n=1,340)
Hispanic / 3.89 3.64 3.89 3.95 3.68 4.09 3.88
Latino (n=17,476) (n=494) (n=10,732) (n=11,362) (n=371) (n=871) (n=407)
3.86 3.50 3.81 3.90 3.69 3.99 3.74
Asian
(n=1,192) (n=57) (n=1,007) (n=3,138) (n=182) (n=322) (n=464)
Pacific 3.80 3.42 3.81 3.90 3.78 3.76 3.63
Islander (n=473) (n=23) (n=487) (n=1,757) (n=26) (n=41) (n=10)
3.69 3.56 3.85 3.86 3.51 3.96 3.73
Black
(n=6,043) (n=161) (n=4,476) (n=6,609) (n=202) (n=463) (n=158)
American 3.74 3.50 3.84 3.82 3.50 3.83 3.59
Indian (n=1,705) (n=70) (n=1,754) (n=2,645) (n=108) (n=181) (n=113)
FY 2008-‐09 Unknown/Missing Values: Family Member/Caregiver 12.4% (n=4,852), TAY 15.3% (n=4,753), Adult
18.8% (n=10,528), Older Adult 20.2% (n=1,063); FY 2009-‐10 Unknown/Missing Values: Family Member / Caregiver
6.7% (n=98), Adult 26.7% (n=631), Older Adult 13.5% (n=390)
12 Consumer Perception Surveys were not completed by youth during FY 2009-‐10
56
Table 11.2 – Perceptions of well-‐being by gender
Family Member/
Caregiver of Children TAY Adult Older Adult
and/or TAY
FY FY FY FY FY FY FY FY
2008-‐09 2009-‐10 2008-‐09 2009-‐1013 2008-‐09 2009-‐10 2008-‐09 2009-‐10
3.80 3.54 3.82 3.85 3.50 3.95 3.74
Female
(n=12,865) (n=401) (n=10,173) (n=22,786) (n=936) (n=2,478) (n=1,575)
3.81 3.57 3.90 3.90 3.50 3.96 3.69
Male
(n=20,804) (n=652) (n=12,154) (n=18,426) (n=631) (n=1,534) (n=769)
FY 2008-‐09 Unknown/Missing Values: Family Member/Caregiver 5.8% (n=2,077), TAY 8.0% (n=1,943), Adult 12.3%
(n=5,800), Older Adult 11.3% (n=511); FY 2009-‐10 Unknown/Missing Values: Family Member/Caregiver 3.8%
(n=42), Adult 2.7% (n=44), Older Adult 4.3% (n = 106)
Average ratings among most respondent groups in both fiscal years analyzed were greater than 3.5,
suggesting positive perceptions of well-‐being as a result of services received. Such consumer-‐driven
feedback regarding the community mental health system provides a vital indication of system
performance from those who have received services.
13 Consumer Perception Surveys were not completed by youth during FY 2009-‐10.
57
Priority Indicator 12: Satisfaction With Services
Indicator Summary
This indicator provides insight into consumer and family perceptions of satisfaction with mental health services.
Indicator Calculation
• Family members/caregivers and TAY respondents’ ratings (1–Strongly Disagree to 5–Strongly Agree) of two self-‐
report items (specified in the Data Sources section below) were averaged to calculate aggregate ratings of
perceptions of access to mental health services (see Figures 12.1-‐12.2 and Tables 12.1-‐12.2 below). Aggregate
ratings were calculated for each fiscal year. Ratings of 3.5 or greater generally indicate positive perceptions. This
calculation method is in line with previous DHCS practices.
• Adult and older adult respondents’ ratings (1–Strongly Disagree to 5–Strongly Agree) of 14 self-‐report items
(specified in the Data Sources section below) were averaged to calculate aggregate ratings of perceptions of
access to mental health services (see Figures 12.1-‐12.2 and Tables 12.1-‐12.2 below). Aggregate ratings were
calculated for each fiscal year. Ratings of 3.5 or greater generally indicate positive perceptions. This calculation
method is in line with previous DHCS practices.
Data Sources
Consumer Perception Surveys
• Family members/caregivers and TAY self-‐report items analyzed (YSS/YSS-‐F):
o Overall, I am satisfied with the services my child received.
o The people helping my child stuck with us no matter what.
o I felt my child had someone to talk to when he/she was troubled.
o The services my child and/or family received were right for us.
o My family got the help we wanted for my child.
o My family got as much help as we needed for my child.
• Adult and older adult self-‐report items analyzed (MHSIP):
o I like the services that I received here.
o If I had other choices, I would still get services from this agency.
o I would recommend this agency to a friend or family member.
• Note: Data collected in FY 2008-‐09 and 2009-‐10 must be interpreted separately because a convenience sampling
method was used to gather FY 2008-‐09 data and random sampling was used to gather data in FY 2009-‐10.14
Review of Existing Data
• Data source likely to be sustained
• Data relevant to population of interest (i.e., convenience or random sample of all mental health consumers)
• Data available across multiple service years
• More than 10% missing or unknown values within key CPS scales
Analytic Potential of Indicator
• Analysis across time possible if the sampling methodology and instrument used is consistent each year
• Analysis among specific service populations possible (e.g., all consumers, demographic groups)
• State and county analysis possible for FY 2008-‐09 (convenience sample), but only state-‐level analysis is possible
in FY 2009-‐10 (random sample)
14 Cowles, E. L., Harris, K., Larsen, C., and Prince, A. (2010). Assessing Representativeness of the Mental Health
Services Consumer Perception Survey.
58
Figure 12.1 – Satisfaction with services, FY 2008-‐09
Older Adult 4.43 (n= 4,770)
Adult 4.33 (n= 47,900)
TAY 4.05 (n= 24,694)
Family Member/Caregiver 4.31 (n= 36,540)
1 2 3 4 5
Figure 12.2 – Satisfaction with services, FY 2009-‐10
Older Adult 4.16 (n= 2,485)
Adult 3.95 (n= 1,607)
Family Member/Caregiver 3.89 (n= 1,103)
1 2 3 4 5
Table 12.1 – Satisfaction with services by race/ethnicity
Family Member/
Caregiver of Children TAY Adult Older Adult
and/or TAY
FY FY FY FY FY FY FY FY
2008-‐09 2009-‐10 2008-‐09 2009-‐1015 2008-‐09 2009-‐10 2008-‐09 2009-‐10
4.31 3.87 4.10 4.35 3.84 4.47 4.13
White
(n=13,069) (n=568) (n=7,858) (n=20,155) (n=838) (n=2,375) (n=1,347)
Hispanic / 4.35 3.93 4.09 4.42 4.07 4.57 4.33
Latino (n=17,821) (n=495) (n=10,812) (n=11,388) (n=368) (n=892) (n=415)
4.31 3.86 4.02 4.32 4.12 4.42 4.15
Asian
(n=1,214) (n=57) (n=1,015) (n=3,131) (n=180) (n=332) (n=459)
Pacific 4.33 3.68 4.04 4.38 3.82 4.15 3.60
Islander (n=478) (n=23) (n=495) (n=1,753) (n=26) (n=41) (n=8)
4.28 3.87 4.02 4.35 4.03 4.37 4.15
Black
(n=6,124) (n=162) (n=4,521) (n=6,618) (n=203) (n=472) (n=159)
American 4.27 4.00 4.06 4.30 3.80 4.44 4.10
Indian (n=1,746) (n=70) (n=1,772) (n=2,626) (n=109) (n=184) (n=114)
FY 2008-‐09 Unknown/Missing Values: Family Member/Caregiver 11.2% (n=5,109), TAY 15.9% (n=5,012), Adult
19.8% (n=11,262), Older Adult 22.5% (n=1,247); FY 2009-‐10 Unknown/Missing Values: Family Member/Caregiver
6.9% (n=102), Adult 11.8% (n=230), Older Adult 14.4% (n=420)
15 Consumer Perception Surveys were not completed by youth during FY 2009-‐10.
59
Table 12.2 – Satisfaction with services by gender
Family Member/
Caregiver of Children TAY Adult Older Adult
and/or TAY
FY FY FY FY FY FY FY FY
2008-‐09 2009-‐10 2008-‐09 2009-‐1016 2008-‐09 2009-‐10 2008-‐09 2009-‐10
4.31 3.87 4.13 4.41 4.01 4.49 4.22
Female
(n=13,082) (n=404) (n=10,279) (n=22,891) (n=931) (n=2,527) (n=1,583)
4.32 3.90 4.02 4.32 3.85 4.42 4.04
Male
(n=21,176) (n=655) (n=12,281) (n=18,457) (n=628) (n=1,571) (n=768)
FY 2008-‐09 Unknown/Missing Values: Family Member/Caregiver 6.2% (n=2,282), TAY 8.6% (n=2,134), Adult 13.7%
(n=6,552), Older Adult 14.1% (n=672); FY 2009-‐10 Unknown/Missing Values: Family Member/Caregiver 4.0%
(n=44), Adult 3.0% (n=48), Older Adult 5.4% (n=134)
Average ratings among most respondent groups, in both fiscal years analyzed, were greater than
3.5, suggesting positive perceptions of satisfaction with services. Such consumer-‐driven feedback
regarding the community mental health system provides a vital indication of system performance
from those who have received services.
16 Consumer Perception Surveys were not completed by youth during FY 2009-‐10.
60
Discussion: Community Mental Health System Indicators
This report represents an important step toward refining priority performance indicators of the
community mental health system. System indicators were designed to provide a multidimensional
understanding of how the mental health system overall, and Full Service Partnerships specifically,
are serving consumers and their families, providers, and other stakeholders. The system indicator
results presented in this report suggest several conclusions and implications regarding the
reliability, diagnostic utility, and sustainability of each indicator.
Demographic Profile of Consumers Served – This indicator provides important understanding of
the extent to which the community mental health system statewide is serving various populations,
including racially and ethnically diverse and other traditionally underserved or unserved groups.
However, the two fiscal years presented in this report represent only a snapshot of mental health
service populations. Additionally, this indicator must be interpreted carefully because of data
inconsistencies across years and among counties that were noted by stakeholders and seen during
the data quality review. Further analysis of service information from additional fiscal years will
provide greater insight concerning the changing demographic composition of the mental health
service population.
New Consumers – This indicator summarizes who new mental health consumers are, and when
considered relative to all consumers can provide insight regarding changes in the composition of
service populations. It will provide greater understanding of the direction and magnitude of
changes in the composition of service populations as information from additional service years is
analyzed.
Penetration of Mental Health Services – This indicator estimates the extent to which mental
health services are reaching those in need and is a crucial component of a multidimensional
assessment of the mental health system. As the accuracy of estimations of the need for mental
health services improves (e.g., National Comorbidity Survey or California Health Information
Survey), the rate of penetration of services will become more reliable and instructive. Additionally,
analysis of penetration rates over longer periods can provide insight regarding changes in the
extent to which services are reaching those in need.
Access to a Primary Care Physician –This indicator provides insight into the extent to which
consumers are connected with a key point of access to physical health care. More complete and
regular tracking of this factor among FSP consumers, and initiating tracking of this factor among all
mental health consumers, will improve the diagnostic potential of this indicator.
Perceptions of Access to Services – This indicator provides important insight regarding
perceptions of access to services among those who have received services. Ratings suggest that on
average, consumers held positive perceptions of their access to mental health services. As noted
previously, concerns regarding the sampling methods used to collect consumer perception
information reduce confidence in the representative nature of this data and do not allow for
reliable comparisons across the two fiscal years analyzed. Implementation of a sampling
methodology that can produce information that is representative of consumer perceptions
statewide and in each county will improve the accuracy and explanatory potential of this indicator.
Involuntary Status – Investigations of involuntary status patterns over time are necessary to
provide a fuller picture of their use. The aggregate involuntary status information available from
61
DHCS does not allow for a statistical breakdown among specific populations (e.g., FSPs). However,
this indicator has the potential to monitor the use of this legal status designation.
Consumer Well-‐Being – This indicator provides important insight regarding consumer perceptions
of well-‐being as a result of services (i.e., outcomes, functioning, social connections) among those
who engaged the mental health service system. Ratings indicate that on average during FY 2008-‐09
and 2009-‐10, consumers and family members held positive perceptions of improvements in their
well-‐being as a result of the services. These perceptions provide another indication of the quality
and appropriateness of the care consumers receive.
Satisfaction – This indicator provides important insight regarding service satisfaction among those
who engaged the mental health service system. Ratings suggest that on average, consumers and
family members were generally satisfied with the services they received. This indicator provides
another important signal of service quality and offers a counterpoint to system indicators that are
not consumer-‐driven.
System Indicator Conclusions and Future Directions
The system-‐level priority indicators presented in this report provide a multidimensional
assessment of community mental health service system access, performance, and quality. Analyses
presented and discussed provide greater understanding of the feasibility, reliability, and
information potential of system indicators going forward, built upon existing data systems and
sources. However, stakeholder feedback to previous evaluation team reports (see the Previous work
of the UCLA-‐EMT Evaluation Team leading to this report section above) and the present evaluation
of system indicators suggests additional performance guides may provide more comprehensive
monitoring of the mental health system.
Several additional indicators were suggested by stakeholders and explored by the evaluation team
but were not included in this report due to their tentative underlying data, calculations, and format.
Exploratory system indicators that may prove informative in the future include:
• Recovery orientation – intended to monitor the extent to which community mental health
systems are structured around providing services focused on the ongoing recovery of the
consumer. Sufficient data are not available to create such an indicator.
• Evidence-‐based practices and programs – intended to monitor the extent to which such
proven services are used throughout the community mental health system. Relevant data
collected through existing systems (e.g., CSI) are incomplete or unreliable and cannot
support such an indicator as currently reported.
Several other indicators were also explored but will not be included in formal reporting until
sufficient data exist to accurately and reliably sustain additional monitoring tools and the MHSOAC
approves additional indicators as part of its ongoing oversight process.
Overall, system indicators evaluated in the present report were found to be informative regarding
the performance of community mental health systems. However, several indicators were also found
to require additional development or supporting information. As such, this report represents an
important initial step, necessary to arrive at a more focused, reliable, and instructive mental health
performance monitoring system.
62
Stakeholder Engagement and Feedback
Stakeholder feedback throughout the evaluation process has been integral to shaping this and other
documents about priority indicator development. The evaluation team incorporates stakeholder
feedback – a continual process – in generating all statewide and county-‐specific reports.
Feedback about an earlier version of this document was collected in the following ways:
1. During report development, research analysts interpreted and provided historical context
about statewide data (CSI, DCR, CPS).
2. During report development, representatives from California State University, Sacramento,
provided insights about data quality based on their ongoing efforts to evaluate a different
facet of the MHSA.
3. During report development, representatives from California counties provided feedback
about the accuracy of data to be included in priority indicator calculations.
4. Stakeholders and the general public were invited to comment on a report draft made
available online (at UCLA and MHSOAC websites) and through two webinars that offered a
forum for stakeholders to comment and assist the evaluation team in improving the report.
5. Consumer stakeholders reviewed key report excerpts for accessibility during a facilitated
webinar.
Stakeholder feedback received through process #4 is summarized in Appendix F, and feedback
from all five processes is noted throughout the report where possible. Stakeholder insights are
treated as an integral part of the conversation about priority indicators. Such feedback will
continue to be required in subsequent reports to involve all interested persons in improving the
quality of mental health services.
For the present report, consumers were invited to participate in a series of focus groups to clarify
particular features, including language, displays, and report organization. The goal of such work
was to ensure the document’s accessibility to a wide range of stakeholders, including those with
limited understanding of statistics and methods.
Next Steps
The evaluation team will move forward with developing new state-‐ and county-‐level reports using
the priority indicators summarized here. Reports will present 1) priority indicators that are refined
based on stakeholder feedback and MHSOAC guidance, 2) analyses of the most recent data
available, and 3) lessons learned from this initial report. These reports are scheduled for release
during March 2013. An overview of county-‐specific data is included as Appendix G of this report.
The MHSOAC will simultaneously vet the appropriateness of the first proposed indicator set and
additional indicators proposed by stakeholders. The MHSOAC will make all final decisions about
priority indicators, their definitions, and their computation.
63
Appendix A – California Mental Health Planning Council’s Proposed Indicators and Definitions
64
Appendix B – Priority Indicator Updates
Decisions made about previously proposed indicators, based on data limitations. (Strikethrough specifies indicators not previously
approved by the MHSOAC)
CHANGE FROM INITIAL 2F DRAFT REPORT – MENTAL HEALTH
DATA SERVICES ACT EVALUATION: COMPILING DATA TO PRODUCE
CONSUMER INDICATORS INDICATOR CALCULATION
SOURCE(S) ALL PRIORITY INDICATORS CONTRACT DELIVERABLE 2F, PHASE
II
Indicator 1.1. School No count of school days attended/absent is available.
Total # of expulsions/suspensions per total # of unique
Attendance (Expulsions and CPS Instead the team calculated the average number of
student consumers
suspensions) expulsion/suspension days per student consumer.
Indicator 1.2. School
Total # of youth reporting that they attended school
Attendance (Rate of
DCR “always” and “most of the time” suggested by MHSOAC ad-‐
attendance compared to
hoc committee
previous year)
Total # of employed-‐paid consumers by total # of work-‐
Indicator 2. Proportion eligible FSP consumers
participating in paid and DCR No change
unpaid employment Total # of employed-‐unpaid consumers by total # of
work-‐eligible FSP consumers
Indicator 3. Proportion
Total # of children, TAY, adults, or older adults (all This is a version of Recommended Ratio 5 in 2D. While
homeless annually;
CSI; DCR consumers and FSP consumers) homeless or housed housed/not homeless responses were regularly reported,
Proportion housed (not
during the FY by total # of consumers days homeless were inconsistently tracked in data.
homeless) annually
Total # of arrests per total # of unique consumers No change. This is Recommended Ratio 2 in 2D.
Indicator 4. Arrest rate CPS; DCR
Total # of arrests (jail time) per total # of unique FSP
consumers This is a version of Recommended Ratio 2 in 2D.
Proportion incarcerated New data collection was proposed, thus this has been
CSI; DCR
removed from the report.
Emergency intervention for This is a version of Recommended Ratio 1. Total number of
Total # of hospitalizations per total # of unique mental
mental health episodes CSI hospital visits is unavailable in datasets. The denominator
health consumers
was changed.
Emergency intervention for co-‐ New data collection was proposed, thus this indicator is not
occurring physical injury included in the report.
Proportion who identify New data collection was proposed, thus this has been
family support removed from the report.
65
CHANGE FROM INITIAL 2F DRAFT REPORT – MENTAL HEALTH
DATA SERVICES ACT EVALUATION: COMPILING DATA TO PRODUCE
CONSUMER INDICATORS INDICATOR CALCULATION
SOURCE(S) ALL PRIORITY INDICATORS CONTRACT DELIVERABLE 2F, PHASE
II
Proportion who identify
community support New data collection was proposed, thus this has been
removed from the report.
CHANGE FROM INITIAL 2F DRAFT REPORT – MENTAL HEALTH
DATA SERVICES ACT EVALUATION: COMPILING DATA TO PRODUCE
SYSTEM INDICATORS INDICATOR CACLULATION
SOURCE(S) ALL PRIORITY INDICATORS CONTRACT DELIVERABLE 2F, PHASE
II
Indicator 5. Demographic % of Overall and FSP service populations represented by
CSI; DCR No Change
profile of consumers served Racial/Ethnic, Age, and Gender Groups
Indicator 6. Demographic % of Overall and FSP service populations represented by
Profile of New Consumers CSI; DCR new consumers (served less than 6 months), by No Change
Racial/Ethnic, Age, and Gender Groups
Indicator 7. Penetration of CSI; Estimates
Mental Health Services (Holzer) of
Ratio of all mental health consumers served to estimates Estimate of need revised to focus on individuals living within
Serious Mental
of need for service (SMI & 200% of poverty level) 200% of the federal poverty line.
Illness (SMI) in
CA
High need consumers served Indicator removed due to redundancy with Consumer
Indicators.
Indicator 8. Access to Primary % of FSP consumers indicating access to a primary care
DCR No Change
Care Physician physician
Indicator 9. Perceptions of Mean aggregate ratings of consumer perception of
CPS No Change
Access to Services access to services
FSP Consumers Served • Formerly titled “Consumers Served Annually through
CSS”. Title changed for accuracy/specificity of data
DCR; County available.
Plans / Annual Ratio of FSP consumers served to planned service levels • CSS Exhibit 6 data was reported to be unreliable by many
Updates experts and stakeholders. So, service levels planned by
counties were use as the denominator for this indicator
calculation.
66
CHANGE FROM INITIAL 2F DRAFT REPORT – MENTAL HEALTH
DATA SERVICES ACT EVALUATION: COMPILING DATA TO PRODUCE
SYSTEM INDICATORS INDICATOR CACLULATION
SOURCE(S) ALL PRIORITY INDICATORS CONTRACT DELIVERABLE 2F, PHASE
II
Indicator 10. Involuntary • Involuntary Status information only available from DHCS
Status California through FY 2008-‐09, thus 2009-‐10 is not available as of
DMH the preparation of this report
Reports of Rate of involuntary services per 10,000 served. • Seclusion/Restraint information only available from 7
Involuntary state facilities. Because the community mental health
Status system is the focus of this report, seclusion/restraint will
not be reported.
24-‐hour care % of Overall and FSP consumers who received 24-‐hr
CSI; DCR No Change
services
Consumer and Family Mean aggregate ratings of consumer/family centered Formerly titled “Appropriateness of Care”. Title changed for
CPS
Centered Care care accuracy/specificity of data available.
Integrated Service Delivery • Formerly titled “Continuity of Care”. Title changed in
response to expert/stakeholder feedback and for
accuracy/specificity of data available.
County Plans / • CSI and DCR data fields proposed for analysis in
Prevalence of planned county strategies for achieving
Annual Deliverable 2D were found incomplete and unreliable. As
integrated service delivery.
Updates Integrated Service Delivery is an MHSA service goal,
county plans were systematically coded to assess the
prevalence of county strategies for achieving integrated
service delivery.
Indicator 11. Consumer
CPS Aggregate mean consumer/family ratings of wellbeing No Change
wellbeing
Indicator 12. Satisfaction Aggregate mean consumer/family ratings of satisfaction
CPS No Change
with services
Workforce composition Indicator removed due to redundancy with the work of other
contractors (per MHSAOC request).
Evidence-‐based Practice Proposed DCR data fields were reported to be unreliable by
Programs experts and stakeholders, and were found to be incomplete
County Plans /
through our analysis. Evidence based practices were identified
Annual Prevalence of evidence based practices planned
by an expert contractor and our advisory panel. Then county
Updates
plans were coded to assess the prevalence of plans to
implement evidence based practices.
Cultural Appropriateness of Only 1 currently collected CPS item assesses cultural
WET Plans;
Services appropriateness of services. Such a narrow measure would not
County Plans / Prevalence of planned county strategies for providing
be instructive. Thus, county plans were systematically coded to
Annual culturally appropriate services
assess the prevalence of culturally appropriate service
Updates
strategies planned.
67
CHANGE FROM INITIAL 2F DRAFT REPORT – MENTAL HEALTH
DATA SERVICES ACT EVALUATION: COMPILING DATA TO PRODUCE
SYSTEM INDICATORS INDICATOR CACLULATION
SOURCE(S) ALL PRIORITY INDICATORS CONTRACT DELIVERABLE 2F, PHASE
II
Recovery, wellness, and Resources were not available to conduct the additional a data
WET Plans;
resilience orientation collection, proposed in Deliverable 2D. Thus, county plans were
County Plans / Prevalence of planned county strategies for promoting a
systematically coded to assess the prevalence planned
Annual recovery, wellness, resilience orientation
strategies to promote a recovery, wellness, resilience
Updates
orientation
68
Appendix C – Stakeholder (Consumer/Client) Webinar Feedback
Notes from September 17, 2012
Green font indicates suggestions that were incorporated into the report.
Regarding the Executive Summary
p. 1
• The term consumer/client might be considered
• The term "efficacy" could be difficult for readers to understand. Perhaps stick with the
term "use."
• "Actionable" could be difficult for readers to understand. Does this really mean "system
improvement?"
• Is there a term or punctuation missing in the phrase consumer and system level priority
indicators?
• It is easier to understand "use" rather than "utility."
• Instead of "lack," can the phrase "hasn't yet been developed for statistical and practical
use" be used?
p.2
• Can we include "volunteer contribution" when discussing employment? It could be a
parenthetical like "employment (including volunteer contribution)"
• Spell out FSP if this is the first time it is mentioned in the report.
• The sentence that begins with "Overall, employment data" is confusing.
• Spell out CSI if this is the first time it is mentioned in the report.
p. 3
• The sentence that begins "Rates of Involuntary Status seem to suggest" is confusing.
• Adding examples following the sentences that begin with "Perceptions of consumer
wellbeing" and "Consumer perceptions of satisfaction" would be helpful.
• In the third point within the conclusion section, changing “may” to “can” could leave the
door open to future changes.
Regarding Priority Indicator Description
• Consider using the term consumer/client
Regarding Priority Indicator Cover (Summary) Page
• "Frequency of Arrest" carries a stigma. Can we say "reducing recidivism?"
• CPS also stands for Child Protection Services. Is there a way to change its appearance when
differentiating between Youth, Youth-‐Family, Adult, and Older Adult Forms?
• Can ethnicity be included in the arrest breakdown? If not, can the presence of analysis by
ethnicity be noted in the indicator section?
69
Regarding Housing Indicator Graphs
• Some people will need "n" defined as a sample number. Maybe this should be attached to
each chart like a key.
• Green shades are very close and need more distinction.
Regarding One Full Indicator Section (Satisfaction)
• The references to figures and tables in one description are heavy. Can you say "see charted
data below?"
• "n =" is missing from this page.
• Table 12.2 -‐ Where are transgender respondents? Can you add a note that there is no
transgender category to choose?
Other Discussion Topics
• What is the importance of including Missing/Unknown values?
• In the tables, please note that Family Member/Caregiver refers to children and TAY.
• Race and ethnicity need to be peeled farther so that services can be fine-‐tuned (e.g., who is
in the White race and how can services accommodate those ethnic groups?).
• "Lived experience" will need to be explained. You might get different responses from
people based on their length of LE and/or their cultures.
70
Appendix D – Recoding Pre-‐DIG Race Data to Post-‐DIG Format
Stakeholder feedback to previous evaluation team reports suggested inconsistency and potential
inaccuracy among Race and Ethnicity data fields may be due in part to changes in the format of
these fields in the CSI and DCR data systems. In 2006, DMH implemented changes to the Race and
Ethnicity fields due to Uniform Data System/Data Infrastructure Grant (DIG) requirements from the
federal government (see DMH Information Notice: 06-‐02). Although DMH provided training about
these changes, Race and Ethnicity information seems to be reported inconsistently across counties.
Because demographic information in the CSI system is transferred to corresponding fields in the
DCR system, Race and Ethnicity information in both systems was analyzed but interpreted with
caution. To ameliorate potential shortcomings of this change, the evaluation team used pre-‐DIG
information to fill gaps in missing post-‐DIG Race and Ethnicity fields for analyses involving
demographic information. The table below details the recoding process.
Before Recode After Recode (if Post-‐DIG field empty)
Data Post-‐DIG Data
Pre-‐DIG Field Definition Definition
Value Field Value
Empty formerly
White 1 Race White or Caucasian 1
Ethnicity / Race
Empty formerly
Hispanic 2 Ethnicity Yes (Hispanic or Latino) Y
Ethnicity / Race
Empty formerly Black or African
Black 3 Race 3
Ethnicity / Race American
Empty formerly American Indian or
American Native 5 Race 5
Ethnicity / Race Alaska Native
Empty formerly
Amerasian A Race Other Asian O
Ethnicity / Race
Empty formerly
Hawaiian Native P Race Native Hawaiian P
Ethnicity / Race
Empty formerly
Multiple X Race Multiracial Multiracial
Ethnicity / Race
Empty formerly Other Asian or Pacific
4 Race Other Asian O
Ethnicity / Race Islander
71
Appendix E – Counties Responding to Data Quality Assurance Reports,
Comparison to Declined/ Non-‐Respondents
County
County Identification
Number
1) Alameda 1
2) Butte 4
3) Calaveras 5
4) Contra Costa 7
5) Fresno 10
6) Glenn 11
7) Kings 16
8) Lake 17
9) Los Angeles 19
10) Marin 21
11) Mariposa 22
12) Napa 28
13) Placer 31
14) San Benito 35
15) San Bernardino 36
16) San Francisco 38
17) San Joaquin 39
18) San Mateo 41
19) Santa Barbara 42
20) Santa Clara 43
21) Santa Cruz 44
22) Shasta 45
23) Sierra 46
24) Siskiyou 47
25) Solano 48
26) Stanislaus 50
27) Trinity 53
28) Tulare 54
29) Tuolumne 55
72
Figure E -‐ 1. Population of counties responding/not responding to data quality assurance reports
Declined/Non-‐ Responding
Respondents, 29% CounIes, 71%
(n = 10,474,454 ) (n = 25,242,297)
Figure E -‐ 2. Counties responding/not responding to data quality assurance reports, by size category
6
6
10 6
9 10
6 Responding CounIes
4
1
Declined/Non-‐Respondents
73
Figure E -‐ 3. Counties responding/not responding to data quality assurance reports, by region
9
7
Responding CounIes
2
10 Declined/Non-‐Respondents
11
9
7
2 1
Superior Central Bay Area Southern Los Angeles
Figure E -‐ 4. Race dispersion of counties responding/not responding to data quality assurance reports
74
037,846,41
721,879,6
861,759,1
603,364 761,032 770,821
772,867,3
643,590,1
436,301
095,04
123,435,4
800,967,1
015,192,1
071,625
White Black or American Asian NaIve Some Other Two or More
African Indian and Hawaiian and Race Races
American Alaska NaIve Other Pacific
Islander
Responding CounIes Declined/Non-‐Respondents
Figure E -‐ 5. Latino ethnicity dispersion of counties responding/not responding to data quality
assurance reports
16,497,044
10,036,763
7,033,085
3,967,539
Hispanic or LaIno (of any race) Not Hispanic or LaIno
Responding CounIes Declined/Non-‐Respondents
Figure E -‐ 6. Gender dispersion of counties responding/not responding to data quality assurance
reports
13,150,721 13,383,526
5,489,296 5,511,328
Male populaIon Female populaIon
Responding CounIes Declined/Non-‐Respondents
75
Appendix F – Summary of Stakeholder Feedback to the Previous Version of This Report
Note: Immediate actions taken by the evaluation team in response to feedback are contained in brackets.
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Life Reaching 8.3 Recovery, Wellness, 4.1 Emergency Intervention for My concern is that spirituality Spirituality is a person's
Across to Life and Resilience Orientation Mental Health Episodes / 6.1 is not addressed in this deepest sense of purpose,
/ 7.6 Consumer Well-‐Being Demographic Profile of Consumers document at all. Studies show belonging and connection. It
/ 7.4 Consumer/ Family-‐ Served. These are statistics and do that it can be the single most is often the single most
Centered Care / 5.2 not relate to how people see their important factor in recovery. important factor in recovery.
Proportion who Identify own lives. Please see the Alameda It cannot be left out of this
Community Support. These County Behavioral Health document. Please see
factors define how Care Services Spirituality Alameda County Behavioral
consumers and their Statement, dated April 2012, Health Care Services
families view their lives for a good explanation of Statement on Spirituality.
and recovery -‐-‐ how spirituality and its importance {Not a vetted indicator}
successful they think they in recovery. This simply
are. cannot be left out of this
document.
Second entry: Spirituality
needs to be considered. It is
often the single most
important factor in recovery.
Please see the Alameda
County Behavioral Healthcare
statement on Spirituality for a
good explanation of this
factor. It simply must be
included in this document.
{Not a vetted indicator}
n/a The lack of ability to compare data not related to page number
over time makes the report but to overall helpfulness and
somewhat useless at this time. The purpose of the report-‐-‐-‐ needs
lack of reporting statistical to be stated CLEARLY so
significance/insignificance of people understand its value
differences between measures over or lack of value or intent for
time also makes the report future value {Addressed in
somewhat useless. Not clear what discussion}
the intention of the report is.
MHSOAC should have REQUIRED
ALL COUNTIES to submit data.
Makes me question why some did
not submit.
76
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Mental Health P. 92: Break down by type of P. 98: Identify an indicator P. 34: Need to understand
Services program-‐-‐ more than just Full that is not only tracking what the unknown/other
Oversight and Service Partnerships (FSP), increases in access to, but column includes and means. /
Accountability need more program compares to a baseline that Why is there a large difference
Commission's categories. / Define the all displays how well counties in FSP clients and other
Cultural and consumers category. {FSP are towards closing the gap mental health consumers
Linguistic programs not available in in access to care. / Identify a marking unknown? FSP 2009-‐
Competence datasets} different way to measure 10: 41.6% and Other MH
Committee penetration rates apart from Consumers 7.1%. / Break
(CLCC) P.34: Collect/display LGBTQ the Holtzer Model. Maybe down the demographic
data throughout the report use California Health information into more pieces
and compile this data at the Information Survey (CHIS) than FSP and Mental Health
state level. /LGBTQ data data for indicator of unmet Consumers. /Add age groups
should be disaggregated to needs instead. {No action to this chart. {Point 1
display lesbian, gay, bisexual taken to point 1; CHIS incorporated}
categories, and at least two of proposed to MHSOAC}
the transgendered or variant P. 62: Cultural Competence
people categories. / {Sexual P. 62: Cultural Competence Plans (CCP) should be used as
orientation unavailable in Plans (CCP) should be used a data source / The idea is to
datasets} as a data source. The CCP change the indicators from
provide a more realistic being based on what they plan
P. 58: "As compared to males, picture of what has and is and instead look at what is
female consumers indicated occurring at the county level. available, what they have done
greater satisfaction with / Maybe then using CCP plan or are doing. {No action taken}
services across most age or future versions of it can
groups and both fiscal years have indicators like: / o P. 62: To close the gaps, there
examined"-‐-‐ Services to males Percent of clients needing needs to be a general
call for greater attention to language assistance services understanding of cultural
unique age-‐appropriate and that received it / o Staff belief systems/traditions and
cultural needs that are demographic statistics per historical trauma experienced
relevant to that gender county compared to by different groups in order to
population. These needs population demographics / o break the barriers of stigma
should be considered as Percent of public information and honor/engage all
equally effective and delivery-‐ made available in county communities, especially
responsive, as with services threshold languages {New under-‐represented
for the female gender from data source noted} populations. {No action taken}
same age and cultural groups.
{No action} P. 62: Disparities broadened
beyond race and ethnicity
need to call out age, cultural
heritage and identification,
special needs (e.g.,
relationship status -‐-‐
unattached single, in a
committed relationship,
77
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
widowed, etc. -‐-‐ sexual and
gender orientation,
faith/beliefs, veteran
background, physical
limitations, single parents,
etc.). A wider lens would
address age and
multidimensional needs for
individuals to access services
and, more importantly,
utilize prevention/early
intervention. {Limited
demographic information
collected. No action taken}
78
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Mental Health Most instructive at Least instructive at consumer level: P. 118: Instead of mean P. 118: How about There’s room for refinements.
Department consumer level: School 1) Homelessness & Housing because average number of visits, discussions about the goal: *Break down employment
Attendance, Emergency the definition of homelessness varies maybe report in terms of equity/parity, identifying beyond paid/
Care Visits & Intervention across the nation, the criteria for mode or median; less than 1 disparities, as well as on unpaid.*Definition of
for Co-‐occurring Physical housing eligibility vary widely, & visit or a fraction of a visit what’s a significant change & homelessness needs
Injury, Social Connection & consumers do not have control over does not make sense (For what the improvement standardization. Argument:
Employment. Engaged the number of housing units and example, see P. 69: targets are? Given that MHSA Crowded living conditions
clients & their social placements that are available; &, Emergency Intervention for funds boosted services, it should be considered in
support (with tailored Justice Involvement because the Mental Health Episodes). would be nice to see changes policies/procedures on
health care program) will number of arrests depends on {Indicator removed, not from before MHSA, how housing/ homelessness. It may
have personal control & officers in some ways & clients do vetted by MHSOAC} California is doing compared be culturally acceptable in
can be expected to show not have full control of systems to national/regional/ Asian households to have
behavioral improvements procedures. Officers’ training about P. "0": I think the indicator comparable states. How several generations live in one
by these indicators. mental illness & where to drop off Access: 1) must track tailored about adding incidence rates but not by American
Employment could be the person who exhibits mental (EBP) program completion in against response rates standards. Such conditions
refined by type of paid/ illness-‐related behaviors are beyond addition to at least 1-‐5 visits, regardless of funding prevent recovery from mental
unpaid work to gauge a client’s ability to manage. Least broken down by streams, especially for illness. *Refine Justice
clients’ long-‐term stability. instructive at system level are the race/ethnicity, age, gender, incidence & response rates Involvement by type of
System-‐level indicators are Performance indicators based on the preferred clinical language 2) for new eligible cases? (See P. violations, # of days in jail, &
instructive. Access gives a Consumer Perception Surveys. The need clarifications -‐-‐ who are 40 on pen rates) {Non-‐scope adjudicated arrests. {Action
quick sense of where the ratings tend to be positive, meaning, the New Consumers of work (SOW)} pending}
gap is. Access to PCP is the clients are generally appreciative (i.e.,Totally New/Brand New
informative. In a Medical of their providers, & from quality or Returning after how many P. 73: To assess system-‐wide
Model, at least one health improvement purposes the results years without service?). Are collaboration: descriptive
care visit with the PCP do not highlight areas for those transferring from profile of the extent of data
suggests the person is in improvement. If data can be broken another state & registering sharing that does not violate
care. It is unclear if access down by preferred clinical language, with county considered new? individuals’ need/right to
means at least 1 visit in a maybe areas for improvement will 3) would be more meaningful privacy will help. There is
year. Performance as surface. if data on severity by Dx (type tacit understanding that the
service rate vs target for of illness) at intake can be departments that need to be
FSP services, involuntary collected for all {No action involved are: HHS, Social
status rate, use of 24-‐hour taken} Services, Education, Labor/
care are helpful for Employment, Housing, &
resource mgmt. Structure Justice. The CA system can be
in terms of EBPs, cultural monitored in its
appropriateness & RWR infrastructure development
orientation ground clinical to capture data to identify
mgmt on principles & long-‐ disparities, error correction
term direction of MH & data quality (e.g., # of
services. missing, unknown,
incomplete).
{No action taken}
79
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Tulare County A. Housing It is important A. Justice Involvement. Data show Indicators commented on A. Structure. Counties might
Department of to capture the type of low arrest rates (<1) 12 months were located on multiple consider collecting this data
Mental Health housing and living prior to services, but do not provide pages. using Dr. Mark Ragins
conditions in that setting data 12 months post-‐services. / B. Recovery Progress Report.
as research shows strong Education/ Employment. The Tulare County established a
correlations between difference in variable types across baseline measurement of its
housing type/quality and data categories (e.g., DCR data mental health system using a
mental health functioning. measures categorically always modified version of the
/ B. Emergency Care Rates attends, infrequently attends) makes progress report before
of mental health and drawing comparisons difficult. / C. implementing multiple
physical health related Structure. County MHSA plans often wellness & recovery focused
emergency visits measure do not detail each wellness & activities. Assessments of
consumer functioning, recovery related or culturally system improvement are
service need, and access to competent activity/service within a conducted yearly to measure
appropriate levels of care program, therefore qualitative change over time. / {No
(e.g., outpatient vs. analysis would need strict inclusion action taken}
inpatient mental health parameters. Researchers should Q. Do you have suggestions
treatment, and connection allow counties to indicate which of for alternate ways of
to PCP). / C. Connectivity. their programs contain these presenting specific indicators
Engagement in services important elements. / presented in this report? / A.
and degree of family Indicate the number of
support are critical consumers in each sample
indicators in the measure and outcomes for discrete
of service effectiveness. data periods. Also, please
Tulare County has indicate whether the sample
implemented self-‐report contains a duplicated or
measures to gather data on unduplicated pool of
how services might have consumers. / {Point 1
impacted family incorporated}
relationships for FSP Q. Do the indicators
consumers. An additional presented in this report
assessment tool has been provide an accurate
implemented within representation of consumer
service team meetings to outcomes? / A. No, these
measure the degree of indicators do not appear to
consumer engagement and measure true outcomes as
family inclusion in there is no comparison
treatment planning. / between baseline and a
follow-‐up, and no
consideration of
type/frequency of services
received. Measuring
between fiscal years alone
does not seem sufficient
given the variance in service
80
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
lengths for consumers. {No
action taken}
Q. Do the indicators
presented in this report
provide an accurate
representation of mental
health system performance?
/ A. The ratio of continuous
vs. new consumers by fiscal
year was helpful, and it was
interesting to see the
proportions of consumers of
different ethnicities
accessing services over time.
Overall, indicators measuring
system performance seemed
much more accurate and
appropriate than those
measuring consumer-‐level
outcomes. /{No action taken}
Family member Present the county indicators
of a consumer on an interactive Web page.
User selects county and fiscal
year. Then provide the total
mental health budget, funding
from MHSA, total population,
and number of consumers
served (individuals). Then
provide the indicators. See
first report by the CA Chief
Probation Officers on prisoner
realignment (Web page). See
report CMHDA 2008,
Transforming Local Mental
Health Systems, for 06/07
data on first four items
(provide through most
current year data available).
{Non-‐SOW}
81
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Family member P.4: Delete "using prevention P.5: Just above the heading P. 6: Define Children, TAY,
of a consumer and early intervention "Background," an evaluation Adults, and Older Adults.
programs" in first sentence. team is mentioned. List the {Action pending}
"Prevention and Early team members in the
Intervention" is one of several Appendix. / Inform the P.11: State the source and year
programs defined in the reader where the footnotes of the race data. "Some Other
Mental Health Services Act. are located in the report. {No Race" and "Two or More
{No action taken} action taken.} Races" equal 21.6% of the
total population. After the
P.8: Data Sources brings to P.9: Rand Corp. is evaluating 2010 Census, the Census
mind the External Quality the Prevention and Early Bureau concluded that this is a
Review Organization (EQRO) Intervention Program under growing trend. This has data
yearly reviews of the county contract with CalMHSA. It is reliability implications.
mental health agencies. possible that Rand could Perhaps we should look more
Consider reviewing, make use of the to socio-‐economic data. Dr.
compiling, and summarizing data/analysis for the Three Holzer uses poverty data to
these reviews. With the next Year Plans & Updates, WET arrive at his estimate of
year's review, some measure Plans, estimates of need for mental health needs. {No
of progress towards mental health services, and action taken}
addressing the issues involuntary status. {Find
identified may be made. / requester}
"Not categorized as
'medication only' " suggests a
diagnostic profile of some
type. For example # meds
only, remainder, # above
some $ value of services. OR
mental illness diagnosis. {No
action taken}
82
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Lake County LCMH found all of the None. P. 18: As Justice involvement P. "0": Overall, the indicators Data entered into the DCR is
Mental Health indicators instructive. is not tracked within the presented in this report only as accurate, reliable, and
LCMH EHR, data relating to provide an accurate complete as recalled/disclosed
justice involvement as representation of consumer by the FSP/family member
entered into the DCR is only outcomes and mental health and entered by the PSC. / / As
as accurate as system performance. {No much as possible, CSI data
recalled/reported by the FSP action taken} should be used
and entered by the PSC. {No (i.e., Crisis/ Hospitalization
action taken} P. 6: ADL data for TAY and services/dates) for purposes
Adults may be a good of maximizing the use of
P. 19: As some of the DCR data additional indicator of existing data and minimizing
consist of subjective estimates recovery. / / A measure of duplicate entry into the DCR
(Always/Most of the time/ recovery/level of and the potential for
Sometimes/ engagement (i.e. MORS) inconsistencies due to data
Infrequently/Never or Very could also be helpful. {No entry errors/omissions. {No
good/ Good/ Average/ action taken} action taken}
verage/ Poor), redefining how
that data are collected (i.e., P. 75: LCMH would find
collecting quantifiable data) helpful a County-‐Level
may allow for improved Compared to State-‐ Level
analysis. / / Average school Priority Indicator report. {No
attendance per year may be action taken. Future reports in
better calculated if the SOW}
question “How many days has
s/he been absent from
school?” were added to the
quarterly report (for youth
who are required by law to
attend school). {Proposed in
earlier reports}
P. 32: LCMH supports the
addition of the Social
Connection Domain. How
many times/hours a month do
you see/spend time with
family/ friends/community
organizations may be
additional data points for this
indicator. / {Proposed to
MHSOAC}
83
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Letter, Debbie Rather than stacked graphs Evidence-‐based or promising Finally, in order for counties to
Innes-‐Gomberg, for employment and housing, practices is incomplete and use a priority indicators report
Los Angeles simply stating the percent of not adequately measured via for quality improvement
County currently enrolled FSP clients the documents reviewed by purposes, reports must be
who are employed and the UCLA-‐EMT and is specific to ongoing so that data can be
percent of clients in nonpaid individual providers of FSP tracked and used over time.
work (volunteering, services. In order to {Addressed in report
interning) would be more determine whether a county introductions}
useful. Similarly, the percent has FSP programs providing
of clients who are homeless, specific practices, a site visit Several counties have
living independently, etc., would need to be conducted. established performance
would be most useful. {No action taken} dashboards for quality
{Already addressed with improvement purposes and
MHSOAC} could be used as models in
developing a statewide
Arrest rate is not a useful dashboard. {Request
metric. Generally the value of dashboards identified by
FSP services are seen in the MHSOAC}
reductions of incidents as well
as days incarcerated, so
within-‐subjects analysis is
usually more beneficial. For a
dashboard I would
recommend # of clients
currently incarcerated.
{Recommended in earlier
reports, not vetted by
MHSOAC}
Integrated service delivery
cannot be adequately
measured via the documents
reviewed by UCLA-‐EMT. {No
action taken}
84
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
Patricia Ryan, As background, earlier this Access to quality,
Executive year UCLA, in partnership appropriate, timely data is
Director, with EMT Associates, Inc., essential for state and county
California distributed a Web-‐based evaluation activities,
Mental Health survey asking counties to including those facilitated by
Directors validate Client & Service the MHSOAC. Inadequate
Association Information System (CSI) and state-‐level systems continue
Data Collection Reporting to pose serious challenges to
System (DCR) data. There state-‐level evaluation efforts.
were significant limitations to The challenges faced by the
the survey design that were researchers to identify and
raised by CMHDA and utilize current and accurate
individual counties and data from all counties in the
brought to the attention of the development of this report
Mental Health Services underscores the need to
Oversight and Accountability focus on modernizing the
Commission (MHSOAC). data systems and platforms
While CMHDA and counties available to the state, the
were and are strongly counties and their
committed to ensuring the subcontractors as we move
availability of critical data at toward health care reform
the state level to inform and integration. CMHDA
important evaluation strongly supports efforts that
activities to help demonstrate will result in an accurate
the value of the MHSA, the presentation of data from all
survey design did not account counties, through both the
for the significant variance improvement of data
between counties and the systems and state-‐county
myriad of nuances that are collaboration to identify and
intrinsic to MHSA programs. design alternative solutions,
Because of the design, many such as the aforementioned
counties necessarily left survey tool. {Non-‐SOW}
certain questions unanswered
(when the offered choices did
not appropriately capture the
county’s experience) and/or
indicated on the survey that
certain information was not
accurate, based on the
reporting format. These sorts
of responses were catalogued
by the evaluators as “not
reported.” However, had the
survey been constructed in
another manner, it is possible
85
Responding What indicators do you What indicators do you find least Brief comment Brief comment, continued Brief comment, continued
organization or find most instructive and instructive and why?
individual why?
that much of the information
that counties either left
unanswered or indicated to
be inaccurate may have been
captured. CMHDA is
concerned that the
challenging survey design
may have inadvertently
impacted the accuracy of
information collected. {No
longer applies to method}
86
1
Appendix G – County-Level Outcomes
Priority Indicator 1: Attendance
1.1 Expulsions and Suspensions Per Year (CPS)
Table 1.1-1 - Proportion of clients who were expelled or suspended 12 months before receiving services and after receiving services for FY
2008-09 (CPS)
Child TAY
Exp/Sus 12 mon Exp/Sus since Exp/Sus 12 mon Exp/Sus since
County
prior to services beginning services prior to services beginning services
No Yes No Yes No Yes No Yes
Alameda 61.4% (51) 38.6% (32) 62.7% (52) 37.3% (31) 65.8% (25) 34.2% (13) 84.2% (32) 15.8% (6)
Butte 74.3% (26) 25.7% (9) 79.4% (27) 20.6% (7) 80.0% (20) 20.0% (5) 84.0% (21) 16.0% (4)
Contra Costa 72.5% (37) 27.5% (14) 68.6% (35) 31.4% (16) 53.8% (7) 46.2% (6) 46.2% (6) 53.8% (7)
Fresno 70.7% (29) 29.3% (12) 69.8% (30) 30.2% (13) 75.9% (22) 24.1% (7) 82.8% (24) 17.2% (5)
Kern 75.5% (37) 24.5% (12) 63.5% (33) 36.5% (19) 73.1% (19) 26.9% (7) 70.4% (19) 29.6% (8)
Los Angeles 73.3% (418) 26.7% (152) 73.9% (424) 26.1% (150) 77.8% (291) 22.2% (83) 83.8% (321) 16.2% (62)
Marin 45.5% (5) 54.5% (6) 45.5% (5) 54.5% (6) 66.7% (6) 33.3% (3) 55.6% (5) 44.4% (4)
Merced 66.7% (2) 33.3% (1) 33.3% (1) 66.7% (2)
Monterey 63.2% (12) 36.8% (7) 88.9% (16) 11.1% (2) 64.3% (9) 35.7% (5) 71.4% (10) 28.6% (4)
Orange
Placer
Riverside 63.6% (28) 36.4% (16) 66.7% (30) 33.3% (15) 62.2% (23) 37.8% (14) 77.1% (27) 22.9% (8)
Sacramento 70.7% (118) 29.3% (49) 69.9% (119) 30.4% (52) 84.9% (101) 15.1% (18) 86.7% (104) 13.3% (16)
San Bernardino 65.0% (93) 35.0% (50) 66.0% (97) 34.0% (50) 77.3% (34) 22.7% (10) 82.2% (37) 17.8% (8)
San Diego 72.5% (203) 27.5% (77) 71.3% (201) 28.7% (81) 81.1% (133) 18.9% (31) 87.2% (143) 12.8% (21)
San Francisco 60.0% (27) 40.0% (18) 72.7% (32) 27.3% (12) 78.9% (15) 21.1% (4) 95.0% (19) 5.0% (1)
San Joaquin 87.5% (7) 12.5% (1) 75.0% (6) 25.0% (2) 87.5% (7) 12.5% (1) 87.5% (7) 12.5% (1)
San Luis Obispo 100% (2) 0.0% (0) 100% (3) 0.0% (0) 100% (1) 0.0% (0) 100% (1) 0.0% (0)
San Mateo 44.4% (12) 55.6% (15) 56.5% (13) 43.5% (10) 60.0% (12) 40.0% (8) 77.8% (14) 22.2% (4)
Santa Barbara 100% (2) 0.0% (0) 100% (2) 0.0% (0) 71.4% (5) 28.6% (2) 85.7% (6) 14.3% (1)
Santa Clara 73.7% (87) 26.3% (31) 71.9% (87) 28.1% (34) 70.8% (51) 29.2% (21) 84.9% (62) 15.1% (11)
Santa Cruz 76.2% (16) 23.8% (5) 73.9% (17) 26.1% (6) 71.4% (10) 28.6% (4) 85.7% (12) 14.3% (2)
Solano 80.0% (4) 20.0% (1) 100% (5) 0.0% (0) 37.5% (3) 62.5% (5) 62.5% (5) 37.5% (3)
Sonoma 68.4% (13) 31.6% (6) 63.2% (12) 36.8% (7) 100% (7) 0.0% (0) 85.7% (6) 14.3% (1)
Stanislaus 69.0% (40) 31.0% (18) 78.0% (46) 22.0% (13) 79.2% (19) 20.8% (5) 84.6% (22) 15.4% (4)
Tulare 91.7% (11) 8.3% (1) 84.6% (11) 15.4% (2) 75.0% (6) 25.0% (2) 87.5% (7) 12.5% (1)
Ventura 74.1% (20) 25.9% (7) 59.3% (16) 40.7% (11) 90.0% (18) 10.0% (2) 85.0% (17) 15.0% (3)
Yolo 0.0% (0) 100% (1) 100% (1) 0.0% (0)
Small Counties 60.7% (51) 39.3% (33) 64.6% (53) 35.4% (29) 63.2% (36) 36.8% (21) 68.4% (39) 31.6% (18)
Total 69.4% (1,300) 30.6% (574) 70.7% (1,374) 29.3% (570) 76.1% (880) 23.9% (276) 82.6% (966) 17.4% (204)
Black shading indicates where data was unavailable to calculate an indicator.
2
Table 1.1-2- Proportion of clients who were expelled or suspended 12 months before receiving services
and after receiving services for FY 2008-09 (CPS) – Missing and Unknown Data
County Unknown/Missing
Children TAY
Alameda 22.4% (24) 20.8% (10)
Butte 8.3% (15) 13.8% (8)
Contra Costa 5.6% (6) 0% (0)
Fresno 20.8% (22) 7.3% (8)
Kern 21.1% (27) 11.7% (7)
Los Angeles 21.1% (306) 20.6% (197)
Marin 15.4% (4) 30.8% (8)
Merced 0% (0)
Monterey 11.9% (5) 17.6% (6)
Orange
Placer
Riverside 14.5% (15) 20.0% (18)
Sacramento 26.9% (124) 23.9% (75)
San Bernardino 14.2% (48) 17.6% (19)
San Diego 8.2% (50) 4.1% (14)
San Francisco 20.5% (23) 22.0% (11)
San Joaquin 38.5% (10) 11.1% (1)
San Luis Obispo 37.5% (3) 0% (0)
San Mateo 24.3% (16) 24.0% (12)
Santa Barbara 0% (0) 30.0% (3)
Santa Clara 15.3% (43) 10.5% (17)
Santa Cruz 15.3% (8) 6.7% (2)
Solano 37.5% (6) 11.1% (2)
Sonoma 5.0% (2) 0% (0)
Stanislaus 10.8% (7) 9.2% (6)
Tulare 37.5% (15) 33.0% (8)
Ventura 12.9% (8) 13.0% (6)
Yolo 0% (0)
Small Counties 18.6% (38) 12.3% (8)
Total 17.8% (825) 16.1% (446)
Black shading indicates where data was unavailable to calculate an indicator.
3
Priority Indicator 1: Attendance
1.2 Average School Attendance Per Year (FSP)
Table 1.2-1 –The frequency with which children and TAY attended school during FY 2008-09 (FSP)
Child TAY
County Always Mostly Sometimes Infrequently Never Always Mostly Sometimes Infrequently Never
Attends Attends Attends Attends Attends Attends Attends Attends Attends Attends
.Alameda
.Butte 18.2% (2) 27.3% (3) 27.3% (3) 27.3% (3) 0.0% (0) 36.4% (4) 9.1% (1) 9.1% (1) 27.3% (3) 18.2% (2)
.Contra Costa 44.4% (48) 38.9% (42) 13.0% (14) 2.8% (3) 0.9% (1) 29.4% (5) 41.2% (7) 11.8% (2) 11.8% (2) 5.9% (1)
.Fresno 26.7% (4) 46.7% (7) 13.3% (2) 6.7% (1) 6.7% (1) 38.1% (8) 52.4% (11) 9.5% (2) 0.0% (0) 0.0% (0)
.Kern 34.0% (18) 43.4% (23) 18.9% (10) 3.8% (2) 0.0% (0) 27.8% (5) 27.8% (5) 22.2% (4) 16.7% (3) 5.6% (1)
.Los Angeles 50.0% (1,035) 30.6% (634) 6.3% (131) 6.2% (128) 6.8% (141) 28.3% (51) 35.6% (64) 10.6% (19) 11.1% (20) 14.4% (26)
.Marin
.Merced 63.6% (35) 23.6% (13) 7.3% (4) 3.6% (2) 1.8% (1) 14.3% (1) 57.1% (4) 28.6% (2) 0.0% (0) 0.0% (0)
.Monterey
.Orange 52.6% (152) 30.1% (87) 7.6% (22) 3.5% (10) 6.2% (18) 45.7% (42) 25.0% (23) 15.2% (14) 5.4% (5) 8.7% (8)
.Placer 30.0% (6) 50.0% (10) 10.0% (2) 10.0% (2) 0.0% (0) 50.0% (4) 50.0% (4) 0.0% (0) 0.0% (0) 0.0% (0)
.Riverside
.Sacramento 53.0% (61) 27.0% (31) 8.7% (10) 1.7% (2) 9.6% (11) 40.0% (6) 33.3% (5) 0.0% (0) 13.3% (2) 13.3% (2)
.San Bernardino 45.1% (196) 29.4% (128) 14.3% (62) 9.0% (39) 2.3% (10) 34.3% (46) 31.3% (42) 13.4% (18) 11.2% (15) 9.7% (13)
.San Diego 58.0% (163) 29.5% (83) 6.8% (19) 3.6% (10) 2.1% (6) 32.8% (45) 46.7% (64) 8.8% (12) 4.4% (6) 7.3% (10)
.San Francisco 43.3% (65) 37.3% (56) 6.7% (10) 10.0% (15) 2.7% (4) 24.6% (16) 35.4% (23) 18.5% (12) 16.9% (11) 4.6% (3)
.San Joaquin 38.5% (10) 42.3% (11) 3.8% (1) 7.7% (2) 7.7% (2) 7.7% (1) 30.8% (4) 15.4% (2) 23.1% (3) 23.1% (3)
.San Luis Obispo 26.1% (7) 26.1% (7) 26.1% (7) 17.4% (4) 4.3% (1) 18.8% (3) 37.5% (6) 25.0% (4) 6.3% (1) 12.5% (2)
.San Mateo 51.4% (18) 22.9% (8) 8.6% (3) 11.4% (4) 5.7% (2) 41.9% (13) 32.3% (10) 9.7% (3) 6.5% (2) 9.7% (3)
.Santa Barbara 48.7% (1,096) 31.3% (706) 8.4% (189) 6.8% (154) 4.8% (107) 32.9% (208) 38.9% (246) 10.4% (66) 10.1% (64) 4.6% (29)
.Santa Clara 28.1% (18) 25.0% (16) 21.9% (14) 20.3% (13) 4.7% (3) 26.5% (13) 28.6% (14) 14.3% (7) 20.4% (10) 10.2% (5)
.Santa Cruz
.Solano 20.6% (7) 58.8% (20) 8.8% (3) 5.9% (2) 5.9% (2) 27.3% (3) 36.4% (4) 9.1% (1) 27.3% (3) 0.0% (0)
.Sonoma 46.3% (38) 31.7% (26) 4.9% (4) 2.4% (2) 14.6% (12) 0.0% (0) 0.0% (0) 50.0% (1) 50.0% (1) 0.0% (0)
.Stanislaus 31.3% (10) 37.5% (12) 15.6% (5) 9.4% (3) 6.3% (2) 42.1% (8) 36.8% (7) 0.0% (0) 10.5% (2) 10.5% (2)
.Tulare 0.0% (0) 55.6% (5) 11.1% (1) 33.3% (3) 0.0% (0) 37.5% (3) 25.0% (2) 0.0% (0) 0.0% (0) 37.5% (3)
.Ventura 37.5% (30) 40.0% (32) 11.3% (9) 10.0% (8) 1.3% (1) 22.4% (11) 40.8% (20) 14.3% (7) 18.4% (9) 4.1% (2)
.Yolo 50.0% (1) 50.0% (1) 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0) 100% (1) 0.0% (0) 0.0% (0) 0.0% (0)
Small Counties 50.8% (187) 29.6% (109) 10.3% (38) 6.3% (23) 3.0% (11) 31.9% (52) 42.3% (69) 11.7% (19) 9.8% (16) 4.3% (7)
Total 49.3% (3,207) 31.8% (2,070) 8.7% (563) 6.7% (435) 3.5% (229) 32.5% (548) 37.9% (636) 11.7% (196) 10.6% (178) 7.3% (122)
Black shading indicates where data was unavailable to calculate an indicator.
4
Table 1.2-2 - The frequency with which children and TAY attended school during FY 2008-09 (FSP)–
Missing and Unknown Data
Unknown/Missing
County
Children TAY
Alameda
Butte 0% (0) 54.2% (13)
Contra Costa 3.6% (4) 48.5% (16)
Fresno 88.5% (115) 57.1% (28)
Kern 0% (0) 71.4% (45)
Los Angeles 6.3% (138) 62.2% (301)
Marin
Merced 5.2% (3) 70% (16)
Monterey
Orange 7.0% (2) 64.3% (166)
Placer 0% (0) 38.5% (5)
Riverside
Sacramento 1.7% (2) 40.0% (10)
San Bernardino 2.7% (12) 42.5% (99)
San Diego 0.4% (1) 30.8% (61)
San Francisco 0% (0) 28.6% (26)
San Joaquin 7.1% (2) 53.6% (15)
San Luis Obispo 0% (0) 36.0% (9)
San Mateo 8.0% (3) 44.6% (25)
Santa Barbara 5.4% (128) 44.0% (495)
Santa Clara 1.5% (1) 22.2% (14)
Santa Cruz
Solano 5.6% (2) 31.3% (5)
Sonoma 2.0% (2) 83.3% (10)
Stanislaus 0% (0) 38.7% (12)
Tulare 0% (0) 55.6% (10)
Ventura 0% (0) 22.0% (14)
Yolo 0% (0) 90.0% (9)
Small Counties 3.2% (12) 22.7% (48)
Total 6.2% (427) 46.4% (1452)
Black shading indicates where data was unavailable to calculate an indicator.
5
Table 1.2-3 –The frequency with which children and TAY attended school during FY 2009-10 (FSP)
Child TAY
County Always Mostly Sometimes Infrequently Never Always Mostly Sometimes Infrequently Never
Attends Attends Attends Attends Attends Attends Attends Attends Attends Attends
.Alameda
.Butte 20.0% (1) 60.0% (3) 0.0% (0) 20.0% (1) 0.0% (0) 20.0% (2) 20.0% (2) 30.0% (3) 10.0% (1) 20.0% (2)
.Contra Costa 54.3% (70) 29.5% (38) 10.9% (14) 3.1% (4) 2.3% (3) 38.9% (7) 16.7% (3) 22.2% (4) 16.7% (3) 5.6% (1)
.Fresno 47.2% (60) 31.5% (40) 7.1% (9) 7.9% (10) 6.3% (8) 32.7% (18) 41.8% (23) 10.9% (6) 7.3% (4) 7.3% (4)
.Kern 32.1% (17) 41.5% (22) 20.8% (11) 5.7% (3) 0.0% (0) 50.0% (9) 11.1% (2) 27.8% (5) 0.0% (0) 11.1% (2)
.Los Angeles 51.7% (1,537) 29.1% (865) 6.8% (203) 5.9% (175) 6.4% (191) 26.9% (80) 34.3% (102) 12.8% (38) 11.1% (33) 14.8% (44)
.Marin
.Merced 44.8% (30) 38.8% (26) 9.0% (6) 3.0% (2) 4.5% (3) 25.0% (3) 58.3% (7) 16.7% (2) 0.0% (0) 0.0% (0)
.Monterey
.Orange 56.5% (156) 30.4% (84) 5.1% (14) 3.6% (10) 4.3% (12) 43.0% (43) 26.0% (26) 17.0% (17) 3.0% (3) 11.0% (11)
.Placer 23.1% (3) 61.5% (8) 15.4% (2) 0.0% (0) 0.0% (0) 50.0% (2) 50.0% (2) 0.0% (0) 0.0% (0) 0.0% (0)
.Riverside
.Sacramento 56.7% (68) 24.2% (29) 10.0% (12) 1.7% (2) 7.5% (9) 40.9% (9) 27.3% (6) 0.0% (0) 13.6% (3) 18.2% (4)
.San Bernardino 51.4% (340) 27.2% (180) 12.1% (80) 7.6% (50) 1.8% (12) 39.8% (117) 26.2% (77) 12.6% (37) 11.2% (33) 10.2% (30)
.San Diego 53.9% (405) 31.5% (237) 8.2% (62) 4.7% (35) 1.7% (13) 41.3% (104) 36.5% (92) 11.5% (29) 6.7% (17) 4.8% (12)
.San Francisco 40.8% (78) 37.2% (71) 9.9% (19) 7.3% (14) 4.7% (9) 21.6% (19) 42.0% (37) 14.8% (13) 13.6% (12) 8.0% (7)
.San Joaquin 34.5% (19) 29.1% (16) 18.2% (10) 9.1% (5) 9.1% (5) 23.3% (7) 23.3% (7) 16.7% (5) 23.3% (7) 13.3% (4)
.San Luis Obispo 35.1% (26) 47.3% (35) 8.1% (6) 8.1% (6) 1.4% (1) 16.7% (4) 54.2% (13) 20.8% (5) 8.3% (2) 0.0% (0)
.San Mateo 44.7% (17) 23.7% (9) 13.2% (5) 10.5% (4) 7.9% (3) 43.9% (18) 29.3% (12) 4.9% (2) 9.8% (4) 12.2% (5)
.Santa Barbara 49.6% (1,545) 32.0% (999) 9.0% (280) 5.6% (176) 3.8% (118) 32.7% (297) 33.4% (304) 14.7% (134) 10.5% (95) 8.7% (79)
.Santa Clara 27.9% (11) 36.0% (14) 16.3% (6) 16.3% (6) 3.5% (1) 15.8% (6) 28.1% (12) 19.3% (8) 22.8% (9) 14.0% (6)
.Santa Cruz
.Solano 25.0% (10) 62.5% (25) 5.0% (2) 5.0% (2) 2.5% (1) 9.1% (1) 45.5% (5) 9.1% (1) 36.4% (4) 0.0% (0)
.Sonoma 39.5% (45) 38.6% (44) 5.3% (6) 5.3% (6) 11.4% (14) 14.3% (1) 28.6% (2) 28.6% (2) 14.3% (1) 14.3% (1)
.Stanislaus 13.3% (4) 50.0% (15) 20.0% (6) 16.7% (5) 0.0% (0) 29.4% (5) 41.2% (7) 17.6% (3) 11.8% (2) 0.0% (0)
.Tulare 10.0% (1) 50.0% (5) 0.0% (0) 30.0% (3) 10.0% (1) 37.5% (3) 37.5% (3) 0.0% (0) 0.0% (0) 25.0% (2)
.Ventura 36.8% (14) 50.0% (19) 10.5% (4) 2.6% (1) 0.0% (0) 18.4% (9) 36.7% (18) 14.3% (7) 20.4% (10) 10.2% (5)
.Yolo 50.0% (1) 50.0% (1) 0.0% (1) 0.0% (1) 0.0% (1) 100% (1) 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
Small Counties 39.1% (207) 40.9% (217) 10.8% (57) 6.4% (34) 2.8% (15) 29.5% (72) 44.7% (109) 14.3% (35) 8.6% (21) 2.9% (7)
Total 49.4% (4,665) 31.8% (3,002) 8.6% (815) 5.9% (555) 4.3% (408) 32.8% (837) 34.1% (872) 13.9% (356) 10.4% (264) 8.8% (226)
Black shading indicates where data was unavailable to calculate an indicator.
6
Table 1.2-4 – The frequency with which children and TAY attended school during FY 2009-10 (FSP) –
Missing and Unknown Data
Unknown/Missing
County
Children TAY
Alameda
Butte 0% (0) 56.5% (13)
Contra Costa 3% (4) 63.3% (31)
Fresno 50.8% (131) 46.6% (48)
Kern 0% (0) 70.5% (43)
Los Angeles 5.6% (175) 57.1% (236)
Marin
Merced 5.6% (4) 62.5% (20)
Monterey
Orange 7.0% (2) 66.3% (197)
Placer 0% (0) 50% (4)
Riverside
Sacramento 3.2% (4) 42.1% (16)
San Bernardino 1.6% (11) 29.3% (122)
San Diego 1.7% (13) 26.8% (93)
San Francisco 0% (0) 28.5% (35)
San Joaquin 6.8% (2) 50.8% (31)
San Luis Obispo 1.3% (1) 35.1% (13)
San Mateo 11.6% (5) 38.0% (25)
Santa Barbara 4.8% (156) 37.5% (545)
Santa Clara 1.1% (1) 32.1% (27)
Santa Cruz
Solano 11.1% (5) 38.9% (7)
Sonoma 1.7% (1) 69.9% (16)
Stanislaus 0% (0) 37% (10)
Tulare 0% (0) 69.2% (18)
Ventura 0% (0) 61.4% (78)
Yolo 0% (0) 85.7% (6)
Small Counties 5.0% (28) 23.0% (73)
Total 5.4% (543) 40.1% (1707)
Black shading indicates where data was unavailable to calculate an indicator.
7
Priority Indicator 2: Employment
Table 2-1 - Proportion of clients who were employed and not employed as reported during their second service date for FY 2008-09 (CSI)
County TAY Adults Older Adults
Not Nonpaid Paid Not Nonpaid Paid Not Nonpaid Paid
Employed Employment Employment Employed Employment Employment Employed Employment Employment
.Alameda 81.0% (837) 1.0% (10) 18.0% (186) 85.1% (2,969) 1.3% (46) 13.6% (475) 91.5% (270) 1.0% (3) 7.5% (22)
.Butte 86.3% (258) 0.0% (0) 13.7% (41) 90.6% (1,596) 0.0% (0) 9.4% (166) 94.2% (131) 0.0% (0) 5.8% (8)
.Contra Costa 93.3% (278) 0.0% (0) 6.7% (20) 90.1% (877) 0.3% (3) 9.6% (93) 97.7% (42) 0.0% (0) 2.3% (1)
.Fresno 95.6% (43) 0.0% (0) 4.4% (2) 96.9% (188) 0.5% (1) 2.6% (5) 100% (8) 0.0% (0) 0.0% (0)
.Kern 87.6% (1,885) 0.1% (2) 12.4% (266) 87.6% (5,362) 0.2% (15) 12.1% (742) 93.6% (280) 0.0% (0) 6.4% (19)
.Los Angeles 97.5% (39) 0.0% (0) 2.5% (1) 100% (80) 0.0% (0) 0.0% (0) 100% (2) 0.0% (0) 0.0% (0)
.Marin 100% (6) 0.0% (0) 0.0% (0) 73.5% (25) 14.7% (5) 11.8% (4) 100% (3) 0.0% (0) 0.0% (0)
.Merced 100% (9) 0.0% (0) 0.0% (0) 93.2% (55) 0.0% (0) 6.8% (4) 100% (3) 0.0% (0) 0.0% (0)
.Monterey 92.1% (58) 0.0% (0) 7.9% (5) 94.8% (328) 0.0% (0) 5.2% (18) 94.7% (18) 0.0% (0) 5.3% (1)
.Orange 92.0% (196) 0.5% (1) 7.5% (16) 79.3% (215) 0.0% (0) 20.7% (56) 77.8% (14) 5.6% (1) 16.7% (3)
.Placer 81.7% (143) 0.0% (0) 18.3% (32) 87.1% (681) 0.0% (0) 12.9% (101) 98.1% (53) 0.0% (0) 1.9% (1)
.Riverside 69.8% (67) 0.0% (0) 30.2% (29) 65.9% (226) 0.3% (1) 33.8% (116) 100% (1) 0.0% (0) 0.0% (0)
.Sacramento 100% (114) 0.0% (0) 0.0% (0) 100% (537) 0.0% (0) 0.0% (0) 100% (25) 0.0% (0) 0.0% (0)
.San Bernardino 91.8% (268) 0.3% (1) 7.9% (23) 94.0% (809) 0.0% (0) 6.0% (52) 100% (27) 0.0% (0) 0.0% (0)
.San Diego 84.0% (2290) 0.5% (13) 15.5% (424) 87.9% (9,966) 0.3% (37) 11.8% (1,337) 95.4% (681) 0.8% (6) 3.8% (27)
.San Francisco 82.9% (209) 0.0% (0) 17.1% (43) 90.8% (1,182) 0.0% (0) 9.2% (120) 94.6% (53) 0.0% (0) 5.4% (3)
.San Joaquin 91.4% (64) 0.0% (0) 8.6% (6) 95.5% (64) 0.0% (0) 4.5% (3) 100% (8) 0.0% (0) 0.0% (0)
.San Luis Obispo 77.2% (183) 0.0% (0) 22.8% (54) 81.6% (625) 0.3% (2) 18.1% (139) 90.2% (46) 0.0% (0) 9.8% (5)
.San Mateo 96.2% (226) 0.0% (0) 3.8% (9) 95.8% (1,034) 0.1% (1) 4.1% (44) 95.3% (82) 0.0% (0) 4.7% (4)
.Santa Barbara
.Santa Clara 92.5% (86) 0.0% (0) 7.5% (7) 91.1% (247) 0.0% (0) 8.9% (24) 100% (12) 0.0% (0) 0.0% (0)
.Santa Cruz 100% (1) 0.0% (0) 0.0% (0) 100% (1) 0.0% (0) 0.0% (0)
.Solano 90.9% (40) 0.0% (0) 9.1% (4) 90.6% (126) 0.7% (1) 8.6% (12) 100% (6) 0.0% (0) 0.0% (0)
.Sonoma 100% (8) 0.0% (0.0) 0.0% (0.0)
.Stanislaus 92.7% (38) 2.4% (1) 4.9% (2) 95.2% (157) 0.0% (0) 4.8% (8) 100% (23) 0.0% (0) 0.0% (0)
.Tulare 91.4% (128) 0.0% (0) 8.6% (12) 94.0% (404) 0.0% (0) 5.6% (24) 95.5% (21) 0.0% (0) 4.5% (1)
.Ventura
.Yolo 84.9% (214) 0.0% (0) 15.1% (38) 83.6% (644) 0.0% (0) 16.4% (126) 94.4% (51) 0.0% (0) 5.6% (3)
Small Counties 84.9% (3,239) 0.1% (5) 14.9% (569) 84.8% (10,146) 0.2% (19) 15.0% (1,798) 89.7% (616) 0.4% (3) 9.9% (68)
Total 85.7% (10,919) 0.3% (33) 14.0% (1,789) 87.3% (38,552) 0.3% (131) 12.4% (5,467) 93.3% (2,476) 0.5% (13) 6.2% (166)
Black shading indicates where data was unavailable to calculate an indicator.
8
Table 2-2 – Proportion of clients who were employed and not employed as reported during their second service date for FY 2009–10 (CSI)
TAY Adults Older Adults
County Not Nonpaid Paid Not Nonpaid Paid Not Nonpaid Paid
Employed Employment Employment Employed Employment Employment Employed Employment Employment
.Alameda 82.3% (910) 0.3% (3) 17.5% (193) 86.3% (2,934) 0.9% (32) 12.8% (434) 92.1% (292) 0.3% (1) 7.6% (24)
.Butte 86.8% (482) 0.0% (0) 13.2% (73) 88.5% (1,986) 0.0% (0) 11.5% (258) 94.0% (140) 0.0% (0) 6.0% (9)
.Contra Costa 81.3% (169) 0.0% (0) 18.8% (39) 84.5% (478) 0.5% (3) 15.0% (85) 86.5% (32) 0.0% (0) 13.5% (5)
.Fresno 97.0% (32) 0.0% (0) 3.0% (1) 97.7% (167) 0.0% (0) 2.3% (4) 95.5% (21) 0.0% (0) 4.5% (1)
.Kern 90.1% (3,473) 0.1% (3) 9.8% (378) 86.4% (8,479) 0.2% (18) 13.4% (1,315) 94.0% (518) 0.0% (0) 6.0% (33)
.Los Angeles 100% (38) 0.0% (0) 0.0% (0) 97.3% (71) 0.0% (0) 2.7% (2) 100% (2) 0.0% (0) 0.0% (0)
.Marin 83.3% (5) 0.0% (0) 16.7% (1) 84.4% (27) 6.3% (2) 9.4% (3) 100% (4) 0.0% (0) 0.0% (0)
.Merced 100% (14) 0.0% (0) 0.0% (0) 93.8% (32) 0.0% (0) 6.3% (2)
.Monterey 83.3% (488) 0.0% (0) 16.7% (98) 86.7% (1,547) 0.0% (0) 13.3% (237) 90.8% (129) 0.0% (0) 9.2% (13)
.Orange 95.8% (205) 0.0% (0) 4.2% (9) 79.3% (184) 0.0% (0) 20.7% (48) 81.8% (9) 0.0% (0) 18.2% (2)
.Placer 87.0% (107) 0.0% (0) 13.0% (16) 82.8% (434) 0.0% (0) 17.2% (90) 88.9% (32) 0.0% (0) 11.1% (4)
.Riverside 76.3% (74) 1.0% (1) 22.7% (22) 58.6% (207) 0.3% (1) 41.1% (145) 100% (1) 0.0% (0) 0.0% (0)
.Sacramento
.San Bernardino 86.0% (339) 0.0% (0) 14.0% (55) 90.0% (809) 0.2% (0) 9.8% (52) 100% (37) 0.0% (0) 0.0% (0)
.San Diego 85.5% (3,590) 0.4% (16) 14.1% (593) 86.5% (12,886) 0.3% (45) 13.2% (1,965) 92.2% (896) 0.6% (6) 7.2% (70)
.San Francisco 82.2% (226) 0.4% (1) 17.5% (48) 88.3% (1,380) 0.1% (2) 11.5% (180) 90.3% (56) 0.0% (0) 9.7% (6)
.San Joaquin 94.1% (64) 0.0% (0) 5.9% (4) 100% (23) 0.0% (0) 0.0% (0) 100% (1) 0.0% (0) 0.0% (0)
.San Luis Obispo 80.2% (198) 0.4% (1) 19.4% (48) 80.5% (642) 0.3% (2) 19.3% (154) 75.4% (43) 1.8% (1) 22.8% (13)
.San Mateo 88.8% (79) 0.0% (0) 11.2% (10) 93.2% (259) 0.0% (0) 6.8% (19) 93.9% (31) 0.0% (0) 6.1% (2)
.Santa Barbara
.Santa Clara 100% (73) 0.0% (0) 0.0% (0) 93.6% (206) 0.5% (1) 5.9% (13) 100% (9) 0.0% (0) 0.0% (0)
.Santa Cruz 100% (2) 0.0% (0) 0.0% (0)
.Solano 94.1% (48) 0.0% (0) 5.9% (3) 91.6% (131) 0.7% (1) 7.7% (11) 100% (6) 0.0% (0) 0.0% (0)
.Sonoma 100% (6) 0.0% (0) 0.0% (0) 100% (1) 0.0% (0) 0.0% (0)
.Stanislaus 80.6% (29) 0.0% (0) 19.4% (7) 88.8% (95) 0.0% (0) 11.2% (12) 100% (5) 0.0% (0) 0.0% (0)
.Tulare 91.7% (111) 0.0% (0) 8.3% (10) 90.1% (237) 0.8% (2) 9.1% (24) 100% (7) 0.0% (0) 0.0% (0)
.Ventura 90.0% (430) 0.0% (0) 10.0% (48) 72.6% (838) 0.0% (0) 27.4% (316) 58.0% (29) 0.0% (0) 42.2% (21)
.Yolo 87.7% (143) 0.0% (0) 12.3% (20) 83.9% (463) 0.0% (0) 16.1% (89) 88.6% (31) 0.0% (0) 11.4% (4)
Small Counties 87.8% (2,390) 0.1% (4) 12.1% (329) 86.3% (7,610) 0.2% (14) 13.5% (1,193) 91.7% (541) 0.3% (2) 8.3% (49)
Total 87.1% (13,719) 0.2% (29) 12.7% (2,005) 86.1% (42,131) 0.3% (123) 13.6% (6,651) 91.5% (2,873) 0.3% (10) 8.2% (256)
Black shading indicates where data was unavailable to calculate an indicator.
9
Table 2-3 – Proportion of clients who were employed and not employed as reported during their second
service date (CSI) – Missing and Unknown Data
County Unknown/Missing
FY 08-09 FY 09-10
.Alameda 0.0% (0) 0.0% (0)
.Butte 26.8% (768) 31.3% (1,387)
.Contra Costa 74.2% (3,787) 83.3% (4,037)
.Fresno 91.7% (2,727) 92.0% (2,596)
.Kern 40.1% (5,738) 16.1% (2,735)
.Los Angeles 65.4% (231) 64.1% (202)
.Marin 88.5% (331) 87.2% (287)
.Merced 64.5% (129) 73.3% (126)
.Monterey 78.1% (1,523) 29.8% (1,065)
.Orange 92.9% (6,579) 93.5% (6,592)
.Placer 56.2% (1,296) 61.1% (1,072)
.Riverside 72.7% (1,169) 74.9% (1,348)
.Sacramento 49.8% (671)
.San Bernardino 72.0% (3,046) 71.9% (4,097)
.San Diego 41.1% (10,304) 42.8% (15,021)
.San Francisco 71.9% (4,102) 71.5% (,4753)
.San Joaquin 90.8% (1,438) 90.0% (905)
.San Luis Obispo 58.3% (1,471) 55.3% (1,363)
.San Mateo 60.7% (2,165) 84.4% (2,167)
.Santa Barbara
.Santa Clara 46.1% (322) 44.6% (243)
.Santa Cruz 95.9% (47) 96.2% (50)
.Solano 83.0% (923) 88.4% (1,527)
.Sonoma 97.8% (361) 98.4% (431)
.Stanislaus 81.1% (1,127) 86.6% (956)
.Tulare 83.3% (3,167) 89.4% (3,310)
.Ventura 56.4% (2,173)
.Yolo 58.1% (1,490) 68.2% (1,611)
Small Counties 47.2% (14,743) 62.5% (20,219)
Total 61.7% (69655) 62.5% (80273)
Black shading indicates where data was unavailable to calculate an indicator.
10
Table 2-4 –The proportion of FSPs who were employed during FY 2008–09 (FSP)
TAY Adults Older Adults
County Not Nonpaid Paid Not Nonpaid Paid Not Nonpaid Paid
Employed Employment Employment Employed Employment Employment Employed Employment Employment
.Alameda
.Butte 90.3% (28) 0.0% (0) 9.7% (3) 74.7% (59) 0.0% (0) 25.3% (20) 50.0% (1) 0.0% (0) 50.0% (1)
.Contra Costa 92.6% (75) 1.2% (1) 6.2% (5) 94.4% (151) 0.6% (1) 5.0% (8) 100% (8) 0.0% (0) 0.0% (0)
.Fresno 99.3% (139) 0.7% (1) 0.0% (0) 99.7% (330) 0.0% (0) 0.3% (1) 100% (9) 0.0% (0) 0.0% (0)
.Kern 94.6% (157) 1.2% (2) 4.2% (7) 96.8% (336) 1.4% (5) 1.7% (6) 95.3% (41) 4.7% (2) 0.0% (0)
.Los Angeles 93.0% (936) 0.0% (5) 7.0% (66) 97.0% (4,038) 0.0% (19) 3.0% (118) 97.0% (236) 1.0% (2) 2.0% (6)
.Marin
.Merced 90.0% (18) 5.0% (1) 5.0% (1) 100% (37) 0.0% (0) 0.0% (0) 100% (1) 0.0% (0) 0.0% (0)
.Monterey
.Orange 82.3% (394) 0.2% (1) 15.5% (84) 94.4% (644) 2.1% (14) 3.9% (24) 93.7% (71) 2.5% (2) 3.8% (5)
.Placer 92.6% (25) 0.0% (0) 7.4% (2) 96.0% (72) 0.0% (0) 4.0% (3) 100% (12) 0.0% (0) 0.0% (0)
.Riverside
.Sacramento 98.1% (51) 0.0% (0) 1.9% (1) 93.4% (325) 0.9% (3) 5.7% (20) 98.8% (81) 0.0% (0) 1.2% (1)
.San Bernardino 94.1% (514) 0.0% (0) 5.9% (32) 96.1% (684) 1.1% (8) 2.8% (20) 95.5% (21) 0.0% (0) 4.5% (1)
.San Diego 95.1% (254) 0.4% (1) 4.5% (12) 98.0% (641) 0.6% (4) 1.4% (9) 96.7% (88) 1.1% (1) 2.2% (2)
.San Francisco 93.7% (74) 0.0% (0) 6.3% (5) 96.3% (257) 0.7% (2) 3.0% (8) 97.6% (41) 2.4% (1) 0.0% (0)
.San Joaquin 92.7% (101) 0.0% (0) 7.3% (8) 91.3% (443) 0.2% (1) 8.5% (41) 100% (48) 0.0% (0) 0.0% (0)
.San Luis Obispo 86.7% (13) 0.0% (0) 13.3% (2) 87.9% (51) 3.4% (2) 8.6% (5) 80.0% (4) 0.0% (0) 20.0% (1)
.San Mateo 89.7% (35) 0.0% (0) 10.3% (4)
.Santa Barbara 93.0% (1,681) 0.4% (8) 6.6% (119) 95.2% (4,468) 0.8% (39) 3.9% (185) 97.3% (390) 0.5% (2) 2.2% (9)
.Santa Clara 94.0% (79) 1.2% (1) 4.8% (4) 94.2% (324) 0.6% (2) 5.2% (18) 100% (18) 0.0% (0) 0.0% (0)
.Santa Cruz 87.3% (55) 0.0% (0) 12.7% (8) 76.2% (32) 2.4% (1) 21.4% (9) 100% (18) 0.0% (0) 0.0% (0)
.Solano 86.7% (13) 0.0% (0) 13.3% (2) 94.7% (36) 2.6% (1) 2.6% (1) 100% (21) 0.0% (0) 0.0% (0)
.Sonoma 94.5% (52) 0.0% (0) 5.5% (3) 94.4% (169) 1.7% (3) 3.9% (7) 100% (5) 0.0% (0) 0.0% (0)
.Stanislaus 97.6% (82) 0.0% (0) 2.4% (2) 95.7% (287) 0.7% (2) 3.7% (11) 100% (32) 0.0% (0) 0.0% (0)
.Tulare 91.1% (51) 0.0% (0) 8.9% (5) 96.0% (120) 0.0% (0) 4.0% (5) 100% (2) 0.0% (0) 0.0% (0)
.Ventura 89.1% (57) 1.6% (1) 9.4% (6) 95.7% (66) 0.0% (0) 4.3% (3) 98.1% (51) 0.0% (0) 1.9% (1)
.Yolo 93.8% (30) 3.1% (1) 3.1% (1) 89.8% (106) 2.5% (3) 7.6% (9) 88.9% (8) 0.0% (0) 11.1% (1)
Small Counties 86.4% (204) 1.3% (3) 12.3% (29) 89.2% (687) 2.7% (21) 8.1% (62) 96.3% (78) 0.0% (0) 3.7% (3)
Total 92.1% (5,118) 0.5% (26) 7.4% (411) 95.2% (14,363) 0.9% (131) 3.9% (593) 96.9% (1,285) 0.8% (10) 2.3% (31)
Black shading indicates where data was unavailable to calculate an indicator.
11
Table 2-5 –The proportion of FSPs who were employed during FY 2009–10 (FSP)
TAY Adults Older Adults
County Not Nonpaid Paid Not Nonpaid Paid Not Nonpaid Paid
Employed Employment Employment Employed Employment Employment Employed Employment Employment
.Alameda
.Butte 93.1% (27) 0.0% (0) 6.9% (2) 84.2% (112) 0.0% (0) 15.8% (21) 100% (17) 0.0% (0) 0.0% (0)
.Contra Costa 91.3% (105) 0.9% (1) 7.8% (9) 93.0% (174) 0.5% (1) 6.4% (12) 100% (11) 0.0% (0) 0.0% (0)
.Fresno 99.4% (164) 0.6% (1) 0.0% (0) 99.5% (362) 0.3% (1) 0.3% (1) 100% (9) 0.0% (0) 0.0% (0)
.Kern 94.2% (178) 1.1% (2) 4.8% (9) 96.7% (291) 1.3% (4) 2.0% (6) 92.7% (38) 4.9% (2) 2.4% (1)
.Los Angeles 93.5% (1,244) 0.6% (8) 5.9% (78) 96.8% (4,396) 0.4% (19) 3.0% (125) 96.7% (261) 0.7% (2) 2.6% (7)
.Marin
.Merced 95.7% (22) 4.3% (1) 0.0% (0) 100% (39) 0.0% (0) 0.0% (0) 100% (1) 0.0% (0) 0.0% (0)
.Monterey
.Orange 83.6% (408) 0.2% (1) 16.2% (79) 93.9% (666) 2.1% (15) 3.9% (28) 93.7% (74) 2.5% (2) 3.8% (3)
.Placer 96.4% (27) 0.0% (0) 3.6% (1) 97.3% (72) 0.0% (0) 2.7% (2) 100% (13) 0.0% (0) 0.0% (0)
.Riverside
.Sacramento 98.0% (98) 0.0% (0) 2.0% (2) 93.9% (970) 1.0% (10) 5.1% (53) 96.9% (126) 0.8% (1) 2.3% (3)
.San Bernardino 91.1% (654) 0.1% (1) 8.8% (63) 94.1% (929) 1.0% (10) 4.9% (48) 97.1% (34) 0.0% (0) 2.9% (1)
.San Diego 93.5% (376) 0.5% (2) 6.0% (24) 97.0% (1174) 0.6% (7) 2.4% (29) 97.8% (133) 0.0% (0) 2.2% (3)
.San Francisco 90.5% (86) 0.0% (0) 9.5% (9) 96.8% (276) 0.7% (2) 2.5% (7) 97.3% (36) 2.7% (1) 0.0% (0)
.San Joaquin 91.2% (177) 1.5% (3) 7.2% (14) 93.6% (876) 0.7% (7) 5.7% (53) 98.7% (75) 0.0% (0) 1.3% (1)
.San Luis Obispo 76.5% (26) 2.9% (1) 20.6% (7) 92.2% (59) 0.0% (0) 7.8% (5) 100% (10) 0.0% (0) 0.0% (0)
.San Mateo 87.5% (35) 0.0% (0) 12.5% (5) 100% (1) 0.0% (0) 0.0% (0)
.Santa Barbara 91.1% (2,025) 0.4% (8) 8.6% (191) 95.2% (5,284) 0.6% (35) 4.1% (230) 97.1% (440) 0.4% (2) 2.4% (11)
.Santa Clara 96.1% (74) 2.6% (2) 1.3% (1) 96.1% (271) 0.4% (1) 3.5% (10) 100% (14) 0.0% (0) 0.0% (0)
.Santa Cruz 85.7% (30) 0.0% (0) 14.3% (5) 75.0% (27) 2.8% (1) 22.2% (8) 100% (13) 0.0% (0) 0.0% (0)
.Solano 92.9% (13) 0.0% (0) 7.1% (1) 90.1% (73) 2.5% (2) 7.4% (6) 100% (20) 0.0% (0) 0.0% (0)
.Sonoma 96.1% (73) 0.0% (0) 3.9% (3) 95.5% (191) 1.5% (3) 3.0% (6) 96.4% (27) 3.6% (1) 0.0% (0)
.Stanislaus 96.7% (87) 0.0% (0) 3.3% (3) 96.6% (253) 0.8% (2) 2.7% (7) 100% (30) 0.0% (0) 0.0% (0)
.Tulare 94.4% (85) 1.1% (1) 4.4% (4) 97.9% (140) 0.0% (0) 2.1% (3) 100% (5) 0.0% (0) 0.0% (0)
.Ventura 85.2% (305) 0.6% (2) 14.2% (51) 92.2% (707) 0.5% (4) 7.3% (56) 96.4% (81) 0.0% (0) 3.6% (3)
.Yolo 92.0% (23) 4.0% (1) 4.0% (1) 90.5% (95) 2.9% (3) 6.7% (7) 90.0% (9) 0.0% (0) 10.0% (1)
Small Counties 91.2% (289) 0.9% (3) 7.9% (25) 91.6% (993) 2.3% (25) 6.1% (66) 96.5% (107) 0.0% (0) 3.6% (4)
Total 91.4% (6,631) 0.5% (38) 8.1% (587) 95.1% (18,431) 0.8% (152) 4.1% (789) 97.0% (1,584) 0.7% (12) 2.3% (38)
Percent of FAP employment data missing and/or unknown is unavailable.
Black shading indicates where data was unavailable to calculate an indicator.
12
Priority Indicator 3: Homelessness and Housing Rates
Table 3.1-1 – Most recent housing status excluding homelessness, children, all consumers (CSI)
FY 08-09 FY 09-10
County House/ Group House/ Group
Foster Care Foster Care
Apartment Setting Apartment Setting
.Alameda 81% (4,247) 9.4% (492) 9.6% (502) 84.1% (5,091) 8% (485) 7.9% (477)
.Butte 85% (1,154) 12% (163) 3% (41) 85.6% (1,627) 12.5% (238) 1.8% (35)
.Contra Costa 79.9% (2,568) 9.4% (302) 10.7% (343) 82.7% (2,976) 7.8% (281) 9.5% (343)
.Fresno 71.6% (1,883) 21% (551) 7.5% (196) 68.1% (1,551) 18.8% (428) 13.2% (300)
.Kern 84.6% (5,429) 5.8% (373) 9.6% (615) 83.3% (5,982) 7% (504) 9.7% (695)
.Los Angeles 65.1% (121) 21.5% (40) 13.4% (25) 62.5% (70) 30.4% (34) 7.1% (8)
.Marin 94.3% (132) 1.4% (2) 4.3% (6) 92.8% (128) 0.7% (1) 6.5% (9)
.Merced 100% (1) 0% (0) 0% (0) 100% (1) 0% (0) 0% (0)
.Monterey 74.6% (1,029) 18.4% (254) 7% (97) 83% (1,792) 13.6% (294) 3.4% (73)
.Orange 3.1% (70) 26.2% (592) 70.7% (1,601) 2.8% (60) 30.8% (662) 66.4% (1,426)
.Placer 91% (707) 6.8% (53) 2.2% (17) 90% (708) 7.9% (62) 2.2% (17)
.Riverside 83.9% (990) 14.7% (174) 1.4% (16) 80.1% (977) 19.3% (236) 0.6% (7)
.Sacramento
.San Bernardino 92.4% (3,935) 5.8% (246) 1.8% (77) 92.8% (4,211) 5.5% (248) 1.8% (81)
.San Diego 80.4% (8,366) 7.9% (819) 11.7% (1,222) 82.6% (11,893) 9% (1,293) 8.4% (1,212)
.San Francisco 88.5% (1,390) 8.7% (137) 2.7% (43) 89.8% (1,531) 8.3% (141) 1.9% (32)
.San Joaquin 71.7% (1,762) 14.9% (366) 13.4% (330) 71.8% (1,209) 12.1% (204) 16.1% (271)
.San Luis Obispo 86.2% (831) 11.1% (107) 2.7% (26) 83.6% (890) 13% (138) 3.5% (37)
.San Mateo 87.1% (1,544) 2.8% (50) 10.1% (179) 85.3% (1,516) 2.2% (39) 12.5% (222)
.Santa Barbara 78.8% (659) 15.6% (130) 5.6% (47) 80.5% (570) 12.7% (90) 6.8% (48)
.Santa Clara 57.1% (93) 16.6% (27) 26.4% (43) 53.8% (43) 16.3% (13) 30% (24)
.Santa Cruz 29.6% (8) 63% (17) 7.4% (2) 27.8% (5) 38.9% (7) 33.3% (6)
.Solano 87.4% (674) 9.7% (75) 2.9% (22) 87.4% (792) 9.8% (89) 2.8% (25)
.Sonoma 76.9% (113) 6.1% (9) 17% (25) 87.8% (216) 4.1% (10) 8.1% (20)
.Stanislaus 94.4% (1,836) 3.4% (66) 2.2% (43) 94.4% (1,742) 3.4% (63) 2.2% (40)
.Tulare 92.7% (3,295) 6.6% (233) 0.7% (26) 93.2% (3,608) 6% (231) 0.8% (32)
.Ventura 85.1% (2,755) 4.6% (148) 10.3% (334) 85.5% (2,788) 5.2% (169) 9.3% (304)
.Yolo 88.3% (567) 9% (58) 2.6% (17) 87.1% (445) 10.8% (55) 2.2% (11)
Small Counties 87.4% (9,655) 10.9% (1,205) 1.7% (193) 88.2% (9,851) 10.2% (1,138) 1.6% (183)
Total 81.4% (55,814) 9.8% (6,689) 8.9% (6,088) 82.6% (62,273) 9.5% (7,153) 7.9% (5,938)
Black shading indicates where data was unavailable to calculate an indicator.
13
Table 3.1-2 – Most recent housing status excluding homelessness, TAY, all consumers (CSI)
FY 08-09 FY 09-10
County House/ Group House/ Group
Foster Care Foster Care
Apartment Setting Apartment Setting
.Alameda 75.2% (2,580) 3.1% (106) 21.7% (744) 75.9% (2,898) 3.3% (126) 20.8% (795)
.Butte 88.9% (708) 3.9% (31) 7.2% (57) 86.4% (1,142) 4.2% (56) 9.4% (124)
.Contra Costa 68.6% (1,458) 2.4% (51) 29% (615) 70.3% (1,680) 1.5% (37) 28.2% (674)
.Fresno 75.8% (878) 6.9% (80) 17.3% (200) 67.1% (719) 5.1% (55) 27.8% (298)
.Kern 74.9% (4,683) 1.3% (84) 23.8% (1,486) 73.1% (6,200) 1.7% (144) 25.2% (2,137)
.Los Angeles 59.7% (111) 8.1% (15) 32.3% (60) 47.7% (73) 11.1% (17) 41.2% (63)
.Marin 80.2% (69) 2.3% (2) 17.4% (15) 83.3% (80) 0% (0) 16.7% (16)
.Merced 97.3% (109) 0% (0) 2.7% (3) 96% (97) 1% (1) 3% (3)
.Monterey 74.9% (552) 4.1% (30) 21% (155) 83.6% (1,308) 2.7% (42) 13.7% (214)
.Orange 63.3% (2,809) 2.3% (100) 34.5% (1,531) 67.4% (3,111) 2.6% (118) 30.1% (1,389)
.Placer 92.6% (746) 2.9% (23) 4.6% (37) 91.6% (679) 2.7% (20) 5.7% (42)
.Riverside 91.1% (493) 5.9% (32) 3% (16) 92% (543) 6.6% (39) 1.4% (8)
.Sacramento 77.8% (253) 0% (0) 22.2% (72)
.San Bernardino 94.3% (2,216) 1.7% (40) 4% (94) 93.4% (2,832) 1.7% (52) 4.9% (148)
.San Diego 70.3% (5,340) 1.2% (89) 28.5% (2,165) 70% (8638) 1.3% (155) 28.8% (3,551)
.San Francisco 87.8% (1,257) 2.8% (40) 9.4% (134) 87.7% (1,292) 3.2% (47) 9.1% (134)
.San Joaquin 52.8% (708) 3% (40) 44.3% (594) 48.8% (517) 3.2% (34) 48% (508)
.San Luis Obispo 88.2% (666) 3.6% (27) 8.2% (62) 90.4% (688) 3.2% (24) 6.4% (49)
.San Mateo 75.6% (1,121) 0.9% (14) 23.4% (347) 72.5% (1,102) 0.8% (12) 26.7% (405)
.Santa Barbara 83% (273) 0.6% (2) 16.4% (54) 79.1% (268) 2.4% (8) 18.6% (63)
.Santa Clara 50.7% (136) 7.8% (21) 41.4% (111) 51.4% (113) 10.9% (24) 37.7% (83)
.Santa Cruz 75% (15) 0% (0) 25% (5) 47.8% (11) 13% (3) 39.1% (9)
.Solano 85.9% (336) 4.1% (16) 10% (39) 87.3% (404) 3.9% (18) 8.9% (41)
.Sonoma 64.1% (66) 1.9% (2) 34% (35) 79.9% (115) 2.1% (3) 18.1% (26)
.Stanislaus 79.4% (454) 4% (23) 16.6% (95) 82.3% (496) 4.1% (25) 13.6% (82)
.Tulare 92.1% (1,380) 3.7% (56) 4.2% (63) 93.5% (1,533) 2.3% (37) 4.2% (69)
.Ventura 78.9% (2,045) 0.6% (15) 20.5% (532) 74.6% (1,994) 1.3% (35) 24.1% (644)
.Yolo 89.9% (692) 2.6% (20) 7.5% (58) 90.7% (563) 3.5% (22) 5.8% (36)
Small Counties 90.8% (8,401) 4.2% (387) 5% (465) 90.7% (8,875) 4.3% (423) 4.9% (484)
Total 78.4% (40,555) 2.6% (1,346) 19% (9,844) 77.8% (47,971) 2.6% (1,577) 19.6% (12,095)
Black shading indicates where data was unavailable to calculate an indicator.
14
Table 3.1-3 – Most recent housing status excluding homelessness, adult, all consumers (CSI)
FY 08-09 FY 09-10
County House/ Group House/ Group
Foster Care Foster Care
Apartment Setting Apartment Setting
.Alameda 84.9% (4,520) 0.3% (14) 14.8% (790) 88.9% (5,480) 0.1% (6) 11% (677)
.Butte 94.7% (2,223) 0.1% (3) 5.2% (121) 94.8% (3,005) 0.1% (2) 5.2% (164)
.Contra Costa 90.7% (3,125) 0.1% (2) 9.2% (317) 90.4% (3,236) 0% (0) 9.6% (345)
.Fresno 87.1% (1,701) 0.2% (3) 12.7% (249) 85.1% (1,535) 0.1% (2) 14.8% (266)
.Kern 75.2% (8,942) 0% (3) 24.8% (2,947) 73.1% (10,516) 0% (4) 26.9% (3,867)
.Los Angeles 82.7% (158) 0% (0) 17.3% (33) 87.1% (155) 0.6% (1) 12.4% (22)
.Marin 79.2% (228) 0% (0) 20.8% (60) 75% (186) 0% (0) 25% (62)
.Merced 85.4% (286) 0% (0) 14.6% (49) 85.1% (246) 0% (0) 14.9% (43)
.Monterey 86.1% (1,125) 0.1% (1) 13.8% (181) 89.2% (2,229) 0% (0) 10.8% (271)
.Orange 92.1% (8,433) 0% (4) 7.9% (721) 91.5% (9,003) 0% (1) 8.5% (840)
.Placer 92.5% (1,834) 0.1% (1) 7.5% (148) 90.3% (1,388) 0.1% (1) 9.6% (148)
.Riverside 96.6% (1,118) 0% (0) 3.4% (39) 96.8% (1,271) 0.2% (2) 3% (40)
.Sacramento 66.5% (1,038) 0% (0) 33.5% (522)
.San Bernardino 92.9% (4,030) 0.1% (3) 7% (304) 92.8% (4,536) 0% (0) 7.2% (351)
.San Diego 86% (16,060) 0% (5) 14% (2618) 87.1% (21,621) 0% (4) 12.8% (3,184)
.San Francisco 87% (3,504) 0.2% (7) 12.8% (517) 86.9% (4,136) 0.4% (20) 12.7% (605)
.San Joaquin 89.1% (718) 0.2% (2) 10.7% (86) 83.6% (504) 0.2% (1) 16.3% (98)
.San Luis Obispo 92.1% (1,497) 0.2% (4) 7.6% (124) 94.5% (1,586) 0.1% (2) 5.4% (90)
.San Mateo 87.8% (3,158) 0% (0) 12.2% (439) 87.3% (2,966) 0% (1) 12.7% (430)
.Santa Barbara 91.1% (236) 0.4% (1) 8.5% (22) 95.3% (203) 0.5% (1) 4.2% (9)
.Santa Clara 74.2% (348) 0% (0) 25.8% (121) 71.8% (247) 0% (0) 28.2% (97)
.Santa Cruz 0% (0) 0% (0) 100% (19) 0% (0) 0% (0) 100% (25)
.Solano 86.1% (661) 0% (0) 13.9% (107) 83.1% (1,101) 0% (0) 16.9% (224)
.Sonoma 61.5% (193) 0% (0) 38.5% (121) 63.8% (238) 0% (0) 36.2% (135)
.Stanislaus 89.8% (820) 0% (0) 10.2% (93) 90.3% (635) 0% (0) 9.7% (68)
.Tulare 90.6% (2,480) 0% (0) 9.4% (256) 89.6% (2,339) 0% (0) 10.4% (272)
.Ventura 91.5% (4,056) 0.1% (5) 8.4% (371) 91.4% (4,167) 0% (1) 8.5% (389)
.Yolo 92.1% (1,723) 0% (0) 7.9% (147) 91.9% (1,480) 0% (0) 8.1% (130)
Small Counties 95% (20,326) 0.1% (18) 5% (1,061) 95.1% (20,310) 0.1% (17) 4.8% (1,029)
Total 88.2% (94,541) 0.1% (76) 11.7% (12,583) 88.2% (104,319) 0.1% (66) 11.7% (13,881)
Black shading indicates where data was unavailable to calculate an indicator.
15
Table 3.1-4 – Most recent housing status excluding homelessness, older adult, all consumers (CSI)
FY 08-09 FY 09-10
County House/ Group House/ Group
Foster Care Foster Care
Apartment Setting Apartment Setting
.Alameda 79.3% (514) 0% (0) 20.7% (134) 82.7% (645) 0.3% (2) 17.1% (133)
.Butte 89.7% (296) 0% (0) 10.3% (34) 90% (398) 0% (0) 10% (44)
.Contra Costa 85.9% (371) 0% (0) 14.1% (61) 85.3% (365) 0.2% (1) 14.5% (62)
.Fresno 68.6% (144) 0% (0) 31.4% (66) 68.5% (231) 0% (0) 31.5% (106)
.Kern 86.3% (909) 0.2% (2) 13.5% (142) 85.8% (1,207) 0.1% (2) 14% (197)
.Los Angeles 90% (18) 0% (0) 10% (2) 90.9% (20) 0% (0) 9.1% (2)
.Marin 73.7% (42) 0% (0) 26.3% (15) 71.2% (37) 0% (0) 28.8% (15)
.Merced 89.5% (17) 0% (0) 10.5% (2) 92.9% (13) 0% (0) 7.1% (1)
.Monterey 73.4% (124) 0% (0) 26.6% (45) 78.8% (287) 0% (0) 21.2% (77)
.Orange 74.6% (533) 0% (0) 25.4% (181) 73.5% (515) 0% (0) 26.5% (186)
.Placer 80.3% (179) 0% (0) 19.7% (44) 76.7% (148) 0% (0) 23.3% (45)
.Riverside 100% (14) 0% (0) 0% (0) 95.5% (21) 0% (0) 4.5% (1)
.Sacramento 45.1% (69) 0% (0) 54.9% (84)
.San Bernardino 92.7% (318) 0.3% (1) 7% (24) 92.8% (413) 0% (0) 7.2% (32)
.San Diego 77.2% (2,117) 0% (0) 22.8% (627) 79.5% (3,065) 0% (0) 20.5% (788)
.San Francisco 86.3% (521) 0.7% (4) 13.1% (79) 90.1% (726) 0.6% (5) 9.3% (75)
.San Joaquin 77.2% (44) 1.8% (1) 21.1% (12) 78.6% (33) 0% (0) 21.4% (9)
.San Luis Obispo 94.2% (226) 0% (0) 5.8% (14) 90.5% (209) 0.4% (1) 9.1% (21)
.San Mateo 81.6% (647) 0% (0) 18.4% (146) 83.4% (687) 0% (0) 16.6% (137)
.Santa Barbara 100% (20) 0% (0) 0% (0) 96% (24) 0% (0) 4% (1)
.Santa Clara 87% (47) 0% (0) 13% (7) 89.2% (33) 0% (0) 10.8% (4)
.Santa Cruz 0% (0) 0% (0) 100% (3) 0% (0) 0% (0) 100% (9)
.Solano 87.5% (56) 0% (0) 12.5% (8) 68.5% (122) 0% (0) 31.5% (56)
.Sonoma 66.7% (16) 0% (0) 33.3% (8) 62.5% (20) 0% (0) 37.5% (12)
.Stanislaus 76.4% (162) 0% (0) 23.6% (50) 77.8% (133) 0% (0) 22.2% (38)
.Tulare 78.6% (246) 0% (0) 21.4% (67) 78.3% (260) 0% (0) 21.7% (72)
.Ventura 87.9% (714) 0% (0) 12.1% (98) 87.3% (665) 0% (0) 12.7% (97)
.Yolo 84.2% (278) 0% (0) 15.8% (52) 82.8% (256) 0% (0) 17.2% (53)
Small Counties 90.3% (2,682) 0.4% (13) 9.2% (274) 89.7% (2,883) 0.2% (7) 10.1% (324)
Total 83.1% (11,324) 0.2% (21) 16.7% (2,279) 83.7% (13,416) 0.1% (18) 16.2% (2,597)
Black shading indicates where data was unavailable to calculate an indicator.
16
Table 3.2-1 – Most recent housing status excluding homelessness, children, FSP consumers only (FSP)
FY 08-09 FY 09-10
County With Independent Foster Care Group Setting With Family Independent Foster Care Group Setting
Family
.Alameda
.Butte 50% (2) 0% (0) 50% (2) 0% (0) 66.7% (2) 0% (0) 0% (0) 33.3% (1)
.Contra Costa 50% (3) 16.7% (1) 33.3% (2) 0% (0) 50% (4) 0% (0) 25% (2) 25% (2)
.Fresno 52.4% (11) 4.8% (1) 9.5% (2) 33.3% (7)
.Kern 28.6% (2) 0% (0) 42.9% (3) 28.6% (2) 50% (4) 0% (0) 12.5% (1) 37.5% (3)
.Los Angeles 62.8% (113) 2.8% (5) 13.3% (24) 21.1% (38) 61.4% (208) 1.2% (4) 19.5% (66) 18% (61)
.Marin
.Merced 66.7% (6) 0% (0) 22.2% (2) 11.1% (1) 37.5% (3) 0% (0) 25% (2) 37.5% (3)
.Monterey
.Orange 92.6% (100) 0% (0) 7.4% (8) 93.9% (93) 0% (0) 1% (1) 5.1% (5)
.Placer 62.5% (5) 0% (0) 25% (2) 12.5% (1)
.Riverside
.Sacramento 97.3% (36) 0% (0) 0% (0) 2.7% (1) 69.6% (16) 0% (0) 26.1% (6) 4.3% (1)
.San Bernardino 52% (13) 24% (6) 8% (2) 16% (4) 28.6% (8) 7.1% (2) 21.4% (6) 42.9% (12)
.San Diego 62.5% (20) 0% (0) 6.3% (2) 31.3% (10) 54.2% (45) 0% (0) 8.4% (7) 37.3% (31)
.San Francisco 22.9% (8) 0% (0) 25.7% (9) 51.4% (18) 23.1% (9) 0% (0) 28.2% (11) 48.7% (19)
.San Joaquin 71.4% (5) 0% (0) 0% (0) 28.6% (2) 66.7% (2) 0% (0) 0% (0) 33.3% (1)
.San Luis Obispo 77.8% (7) 0% (0) 11.1% (1) 11.1% (1) 66.7% (4) 0% (0) 16.7% (1) 16.7% (1)
.San Mateo 25% (1) 0% (0) 0% (0) 75% (3) 42.9% (6) 0% (0) 0% (0) 57.1% (8)
.Santa Barbara
.Santa Clara 50% (7) 0% (0) 50% (7) 50% (9) 0% (0) 5.6% (1) 44.4% (8)
.Santa Cruz
.Solano 0% (0) 0% (0) 33.3% (1) 66.7% (2) 33.3% (1) 0% (0) 66.7% (2) 0% (0)
.Sonoma 28.6% (4) 0% (0) 0% (0) 71.4% (10) 50% (7) 0% (0) 7.1% (1) 42.9% (6)
.Stanislaus 77.8% (7) 0% (0) 0% (0) 22.2% (2) 66.7% (8) 0% (0) 0% (0) 33.3% (4)
.Tulare
.Ventura 62.5% (5) 0% (0) 0% (0) 37.5% (3) 75% (3) 0% (0) 0% (0) 25% (1)
.Yolo
Small Counties 63.9% (39) 0% (0) 13.1% (8) 23% (14) 52.6% (51) 0% (0) 17.5% (17) 29.9% (29)
Total 66% (383) 2.1% (12) 10% (58) 21.9% (127) 59.5% (494) 0.8% (7) 15.2% (126) 24.5% (203)
Black shading indicates where data was unavailable to calculate an indicator.
17
Table 3.2-2 – Most recent housing status excluding homelessness, TAY, FSP consumers only (FSP)
FY 08-09 FY 09-10
County
With Family Independent Foster Care Group Setting With Family Independent Foster Care Group Setting
.Alameda
.Butte 58.3% (7) 8.3% (1) 0% (0) 33.3% (4) 12.5% (2) 62.5% (10) 0% (0) 25% (4)
.Contra Costa 22.9% (8) 28.6% (10) 2.9% (1) 45.7% (16) 21.2% (11) 30.8% (16) 0% (0) 48.1% (25)
.Fresno 39.2% (31) 25.3% (20) 1.3% (1) 34.2% (27) 33.3% (25) 22.7% (17) 1.3% (1) 42.7% (32)
.Kern 29.6% (8) 40.7% (11) 0% (0) 29.6% (8) 28.6% (10) 28.6% (10) 0% (0) 42.9% (15)
.Los Angeles 28.4% (55) 13.4% (26) 1% (2) 57.2% (111) 34.8% (118) 16.8% (57) 3.8% (13) 44.5% (151)
.Marin
.Merced 36.8% (7) 42.1% (8) 0% (0) 21.1% (4) 34.8% (8) 34.8% (8) 4.3% (1) 26.1% (6)
.Monterey
.Orange 32.5% (94) 23.2% (67) 0% (0) 44.3% (128) 37.6% (108) 26.1% (75) 0% (0) 36.2% (104)
.Placer 30% (6) 20% (4) 0% (0) 50% (10) 23.5% (4) 35.3% (6) 0% (0) 41.2% (7)
.Riverside
.Sacramento 36.7% (11) 13.3% (4) 0% (0) 50% (15) 35.8% (19) 18.9% (10) 0% (0) 45.3% (24)
.San Bernardino 19.4% (20) 26.2% (27) 0% (0) 54.4% (56) 32.7% (33) 19.8% (20) 3% (3) 44.6% (45)
.San Diego 24.1% (34) 17.7% (25) 0.7% (1) 57.4% (81) 25% (49) 8.2% (16) 1% (2) 65.8% (129)
.San Francisco 19.3% (11) 19.3% (11) 7% (4) 54.4% (31) 29.4% (20) 20.6% (14) 14.7% (10) 35.3% (24)
.San Joaquin 45.5% (10) 18.2% (4) 0% (0) 36.4% (8) 26.7% (12) 15.6% (7) 2.2% (1) 55.6% (25)
.San Luis Obispo 53.3% (8) 26.7% (4) 0% (0) 20% (3) 50% (8) 18.8% (3) 0% (0) 31.3% (5)
.San Mateo 31.8% (7) 9.1% (2) 0% (0) 59.1% (13) 32.3% (10) 22.6% (7) 0% (0) 45.2% (14)
.Santa Barbara
.Santa Clara 22.4% (13) 10.3% (6) 0% (0) 67.2% (39) 26.5% (22) 14.5% (12) 0% (0) 59% (49)
.Santa Cruz 16.7% (1) 33.3% (2) 0% (0) 50% (3) 40% (6) 33.3% (5) 0% (0) 26.7% (4)
.Solano 37.5% (3) 0% (0) 0% (0) 62.5% (5) 0% (0) 0% (0) 0% (0) 100% (2)
.Sonoma 44.4% (4) 22.2% (2) 0% (0) 33.3% (3) 35.7% (5) 14.3% (2) 0% (0) 50% (7)
.Stanislaus 59.6% (31) 9.6% (5) 1.9% (1) 28.8% (15) 49.1% (26) 20.8% (11) 1.9% (1) 28.3% (15)
.Tulare 36% (9) 20% (5) 0% (0) 44% (11) 40.5% (15) 27% (10) 0% (0) 32.4% (12)
.Ventura 37% (10) 11.1% (3) 0% (0) 51.9% (14) 42.7% (47) 21.8% (24) 0% (0) 35.5% (39)
.Yolo 15.4% (2) 61.5% (8) 0% (0) 23.1% (3) 11.1% (1) 44.4% (4) 0% (0) 44.4% (4)
Small Counties 41.2% (68) 19.4% (32) 3% (5) 36.4% (60) 48.8% (101) 20.3% (42) 2.9% (6) 28% (58)
Total 32.1% (458) 20.1% (287) 1.1% (15) 46.8% (668) 35% (660) 20.5% (386) 2% (38) 42.5% (800)
Black shading indicates where data was unavailable to calculate an indicator.
18
Table 3.2-3 – Most recent housing status excluding homelessness, adults, FSP consumers only (FSP)
County FY 08-09 FY 09-10
With Family Independent Foster Care Group Setting With Family Independent Foster Care Group Setting
.Alameda
.Butte 7.1% (1) 85.7% (12) 0% (0) 7.1% (1) 0% (0) 60% (3) 0% (0) 40% (2)
.Contra Costa 1.7% (1) 53.3% (32) 0% (0) 45% (27) 11% (8) 43.8% (32) 0% (0) 45.2% (33)
.Fresno 17.6% (19) 33.3% (36) 0% (0) 49.1% (53) 19.8% (25) 25.4% (32) 0% (0) 54.8% (69)
.Kern 8.9% (11) 43.9% (54) 0% (0) 47.2% (58) 20.6% (20) 35.1% (34) 0% (0) 44.3% (43)
.Los Angeles 10.5% (144) 26.7% (367) 0% (0) 62.8% (864) 14% (200) 27.2% (389) 0% (0) 58.8% (841)
.Marin
.Merced 14.3% (3) 38.1% (8) 0% (0) 47.6% (10) 18.2% (4) 36.4% (8) 0% (0) 45.5% (10)
.Monterey
.Orange 7.5% (34) 48.5% (221) 0% (0) 44.1% (201) 10.9% (35) 48.8% (156) 0% (0) 40.3% (129)
.Placer 6% (3) 34% (17) 0% (0) 60% (30) 2% (1) 30% (15) 0% (0) 68% (34)
.Riverside
.Sacramento 4.5% (5) 63.6% (70) 0% (0) 31.8% (35) 5.4% (22) 37.5% (154) 0% (0) 57.2% (235)
.San Bernardino 8.3% (13) 18.6% (29) 0% (0) 73.1% (114) 17.3% (34) 26.4% (52) 0% (0) 56.3% (111)
.San Diego 2.4% (10) 42.4% (176) 0% (0) 55.2% (229) 6.1% (36) 39.3% (232) 0% (0) 54.7% (323)
.San Francisco 3.6% (4) 59.5% (66) 0% (0) 36.9% (41) 2.2% (2) 49.5% (45) 0% (0) 48.4% (44)
.San Joaquin 16.8% (16) 62.1% (59) 0% (0) 21.1% (20) 9.5% (16) 48.5% (82) 0% (0) 42% (71)
.San Luis Obispo 11.8% (2) 47.1% (8) 0% (0) 41.2% (7) 4% (1) 56% (14) 0% (0) 40% (10)
.San Mateo
.Santa Barbara
.Santa Clara 6.9% (12) 26.4% (46) 0% (0) 66.7% (116) 8.7% (18) 18.3% (38) 0% (0) 73.1% (152)
.Santa Cruz 0% (0) 50% (3) 0% (0) 50% (3) 0% (0) 50% (1) 0% (0) 50% (1)
.Solano 18.2% (6) 6.1% (2) 0% (0) 75.8% (25) 7.4% (2) 22.2% (6) 0% (0) 70.4% (19)
.Sonoma 6.7% (6) 36% (32) 0% (0) 57.3% (51) 6.3% (5) 40.5% (32) 0% (0) 53.2% (42)
.Stanislaus 16.2% (25) 37.7% (58) 0% (0) 46.1% (71) 16.4% (19) 44% (51) 0% (0) 39.7% (46)
.Tulare 12.5% (7) 32.1% (18) 0% (0) 55.4% (31) 11.1% (7) 30.2% (19) 0% (0) 58.7% (37)
.Ventura 3.2% (1) 32.3% (10) 0% (0) 64.5% (20) 9.6% (12) 33.6% (42) 0% (0) 56.8% (71)
.Yolo 1.6% (1) 50.8% (31) 0% (0) 47.5% (29) 8.8% (5) 56.1% (32) 0% (0) 35.1% (20)
Small Counties 6.5% (16) 57.1% (140) 0% (0) 36.3% (89) 6.7% (22) 54.5% (180) 0% (0) 38.8% (128)
Total 8.6% (340) 37.8% (1,495) 0% (0) 53.7% (2,125) 10.7% (494) 35.7% (1,649) 0% (0) 53.6% (2,471)
Black shading indicates where data was unavailable to calculate an indicator.
19
Table 3.2-4 – Most recent housing status excluding homelessness, older adults, FSP consumers only (FSP)
FY 08-09 FY 09-10
County
With Family Independent Foster Care Group Setting With Family Independent Foster Care Group Setting
.Alameda
.Butte 0% (0) 100% (1) 0% (0) 0% (0) 0% (0) 0% (0) 0% (0) 100% (1)
.Contra Costa 0% (0) 25% (1) 0% (0) 75% (3) 0% (0) 100% (1) 0% (0) 0% (0)
.Fresno 0% (0) 25% (1) 0% (0) 75% (3) 0% (0) 0% (0) 0% (0) 100% (4)
.Kern 5.1% (2) 64.1% (25) 0% (0) 30.8% (12) 11.1% (3) 33.3% (9) 0% (0) 55.6% (15)
.Los Angeles 3.3% (4) 33.1% (40) 0% (0) 63.6% (77) 5% (7) 27% (38) 0% (0) 68.1% (96)
.Marin
.Merced 0% (0) 50% (1) 0% (0) 50% (1)
.Monterey
.Orange 4.2% (3) 45.1% (32) 0% (0) 50.7% (36) 4.3% (3) 37.7% (26) 0% (0) 58% (40)
.Placer 7.1% (1) 42.9% (6) 0% (0) 50% (7) 0% (0) 25% (2) 0% (0) 75% (6)
.Riverside
.Sacramento 2.1% (1) 43.8% (21) 0% (0) 54.2% (26) 1.3% (1) 27.8% (22) 0% (0) 70.9% (56)
.San Bernardino 0% (0) 16.7% (2) 0% (0) 83.3% (10) 16.7% (2) 16.7% (2) 0% (0) 66.7% (8)
.San Diego 0% (0) 59.5% (25) 0% (0) 40.5% (17) 0% (0) 42.6% (29) 0% (0) 57.4% (39)
.San Francisco 3.2% (1) 58.1% (18) 0% (0) 38.7% (12) 0% (0) 73.7% (14) 0% (0) 26.3% (5)
.San Joaquin 14.3% (4) 64.3% (18) 0% (0) 21.4% (6) 15% (6) 55% (22) 0% (0) 30% (12)
.San Luis Obispo 0% (0) 100% (2) 0% (0) 0% (0) 0% (0) 66.7% (4) 0% (0) 33.3% (2)
.San Mateo
.Santa Barbara
.Santa Clara 0% (0) 14.3% (1) 0% (0) 85.7% (6) 0% (0) 12.5% (2) 0% (0) 87.5% (14)
.Santa Cruz 0% (0) 20% (1) 0% (0) 80% (4) 0% (0) 16.7% (1) 0% (0) 83.3% (5)
.Solano 0% (0) 52.9% (9) 0% (0) 47.1% (8) 5% (1) 60% (12) 0% (0) 35% (7)
.Sonoma 0% (0) 100% (2) 0% (0) 0% (0) 0% (0) 29.4% (5) 0% (0) 70.6% (12)
.Stanislaus 6.7% (1) 46.7% (7) 0% (0) 46.7% (7) 5.3% (1) 47.4% (9) 0% (0) 47.4% (9)
.Tulare 0% (0) 0% (0) 0% (0) 100% (1) 0% (0) 66.7% (2) 0% (0) 33.3% (1)
.Ventura 2.1% (1) 37.5% (18) 0% (0) 60.4% (29) 4.3% (1) 21.7% (5) 0% (0) 73.9% (17)
.Yolo 0% (0) 75% (6) 0% (0) 25% (2) 0% (0) 50% (1) 0% (0) 50% (1)
Small Counties 3.2% (1) 41.9% (13) 0% (0) 54.8% (17) 1.8% (1) 38.6% (22) 0% (0) 59.6% (34)
Total 3.4% (19) 45.2% (249) 0% (0) 51.4% (283) 4.1% (26) 35.8% (229) 0% (0) 60.2% (385)
Black shading indicates where data was unavailable to calculate an indicator.
20
Table 3.3-1 – Experienced homelessness at any point during the year, all consumers (CSI)
Children TAY Adults Older Adults
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
Alameda 2.9% (155) 3.3% (206) 3.9% (137) 4% (157) 8.6% (493) 7.4% (485) 5% (34) 2.8% (22)
Butte 0.4% (5) 0.3% (6) 6.6% (56) 6.8% (95) 6% (150) 8.3% (284) 2.9% (10) 3.3% (15)
Contra Costa 0.4% (13) 0.1% (5) 2.2% (48) 2.7% (67) 8.8% (333) 8.9% (349) 4.4% (20) 3.4% (15)
Fresno 0% (1) 0.2% (4) 0.5% (6) 1% (11) 2% (40) 1.3% (23) 0.5% (1) 0% (0)
Kern 0.2% (15) 0.2% (15) 1.6% (103) 1.2% (99) 3.8% (473) 3.6% (537) 3.1% (34) 3.3% (48)
Los Angeles 0% (0) 0.9% (1) 4.6% (9) 1.9% (3) 17% (39) 15.2% (32) 13% (3) 8.3% (2)
Marin 0% (0) 0% (0) 3.4% (3) 3% (3) 2% (6) 2% (5) 0% (0) 1.9% (1)
Merced 0% (0) 0% (0) 4.3% (5) 3.8% (4) 5.9% (21) 8.3% (26) 13.6% (3) 17.6% (3)
Monterey 0% (0) 0.2% (4) 1.9% (14) 2.6% (42) 6.9% (95) 6.9% (184) 5.6% (10) 5.8% (22)
Orange 0.7% (16) 0.8% (17) 5.3% (249) 6.5% (318) 9.8% (994) 11.3% (1,258) 13.9% (115) 15.6% (130)
Placer 0.6% (5) 0.4% (3) 1.7% (14) 2.3% (17) 5.6% (116) 5.5% (89) 3.1% (7) 4% (8)
Riverside 0.1% (1) 0% (0) 2.2% (12) 1.5% (9) 2.4% (29) 2.5% (34) 0% (0) 0% (0)
Sacramento 0% (0) 12.6% (44) 12.3% (207) 9.1% (15)
San Bernardino 0% (2) 0.1% (4) 2.9% (71) 4.4% (137) 6% (274) 8.4% (443) 3.9% (14) 4.6% (21)
San Diego 0.5% (50) 0.6% (80) 4.6% (362) 3.8% (490) 11.6% (2,423) 12.6% (3546) 5.9% (172) 6.2% (256)
San Francisco 0.9% (14) 1% (18) 10.9% (174) 12.4% (204) 23.8% (1,223) 27.6% (1,747) 12.1% (82) 12.3% (112)
San Joaquin 0% (1) 0% (0) 0.1% (2) 0.3% (3) 2.8% (23) 2.6% (16) 0% (0) 2.3% (1)
San Luis Obispo 1.5% (15) 1.2% (13) 4.8% (38) 6.4% (51) 13.4% (246) 13.2% (250) 6.7% (17) 5.8% (14)
San Mateo 0.2% (4) 0.1% (1) 2.1% (32) 1.8% (27) 4.2% (155) 5.2% (185) 1.4% (11) 0.8% (7)
Santa Barbara 0.4% (3) 0.1% (1) 2.7% (9) 1.7% (6) 15.4% (47) 16.5% (42) 13% (3) 3.8% (1)
Santa Clara 0% (0) 0% (0) 1.1% (3) 0.9% (2) 7% (35) 9% (34) 5.3% (3) 9.8% (4)
Santa Cruz 0% (0) 4.8% (1) 0% (0) 0% (0)
Solano 0.1% (1) 0.7% (6) 4.4% (18) 3.2% (15) 6.8% (56) 4.6% (63) 1.5% (1) 1.7% (3)
Sonoma 0% (0) 0% (0) 0% (0) 0% (0) 2.2% (7) 1.8% (7) 0% (0) 0% (0)
Stanislaus 0.1% (1) 0.4% (7) 2.7% (16) 2.8% (17) 3.6% (34) 4% (29) 0.5% (1) 0% (0)
Tulare 0.1% (2) 0.1% (3) 2% (31) 1.9% (31) 1.5% (41) 2.8% (74) 0.3% (1) 0.6% (2)
Ventura 0.1% (4) 0.2% (7) 2.3% (61) 2.5% (68) 7.6% (367) 8% (393) 3.1% (26) 2.3% (18)
Yolo 0.5% (3) 0.8% (4) 2.9% (23) 2.7% (17) 7.4% (150) 7.3% (126) 2.9% (10) 1.9% (6)
Small Counties 0.5% (56) 0.5% (59) 2.6% (248) 2.3% (229) 5.9% (1,325) 5.6% (1,266) 2.4% (72) 2.4% (78)
Total 0.5% (367) 0.6% (464) 3.4% (1,789) 3.3% (2,122) 8.1% (9,402) 8.9% (11,527) 4.7% (665) 4.7% (789)
Black shading indicates where data was unavailable to calculate an indicator.
21
Table 3.3-2 – Experienced homelessness at any point during the year, FSP consumers only (FSP)
County Children TAY Adults Older Adults
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
.Alameda
.Butte 66.7% (4) 0% (0) 70.8% (17) 44% (11) 25% (4) 0% (0) 0% (0) 0% (0)
.Contra Costa 16.7% (1) 0% (0) 39.5% (17) 28.8% (17) 16.9% (11) 12.7% (10) 0% (0) 0% (0)
.Fresno 0% (0) 11.5% (10) 6.5% (5) 8.1% (9) 10.9% (14) 25% (1) 0% (0)
.Kern 42.9% (3) 25% (2) 16.7% (5) 18.9% (7) 14.3% (19) 13.3% (14) 2.6% (1) 3.7% (1)
.Los Angeles 7% (13) 6.1% (21) 19.3% (42) 20.5% (78) 28.8% (467) 23.6% (385) 14.9% (20) 14.2% (21)
.Marin
.Merced 0% (0) 12.5% (1) 42.1% (8) 26.9% (7) 26.1% (6) 17.4% (4) 0% (0)
.Monterey
.Orange 2.8% (3) 1% (1) 24.8% (78) 17.5% (53) 29.6% (149) 28.5% (103) 25.9% (21) 14.7% (11)
.Placer 0% (0) 0% (0) 10% (2) 5.6% (1) 9.4% (5) 13.7% (7) 7.1% (1) 0% (0)
.Riverside
.Sacramento 7.9% (3) 0% (0) 10% (3) 17.2% (10) 6.1% (7) 7.8% (33) 4.2% (2) 0% (0)
.San Bernardino 0% (0) 6.7% (2) 45% (67) 26.4% (33) 13% (21) 19.3% (42) 8.3% (1) 16.7% (2)
.San Diego 14.7% (5) 5.8% (5) 19.4% (30) 11.9% (25) 22.1% (101) 16.5% (104) 13.3% (6) 5.8% (4)
.San Francisco 11.4% (4) 12.5% (5) 15.9% (10) 20.3% (15) 38% (49) 43% (49) 25% (9) 39.1% (9)
.San Joaquin 0% (0) 33.3% (1) 8.7% (2) 12.2% (6) 9.9% (10) 11.5% (21) 0% (0) 4.9% (2)
.San Luis Obispo 0% (0) 0% (0) 6.7% (1) 31.6% (6) 22.2% (4) 18.5% (5) 50% (1) 0% (0)
.San Mateo 0% (0) 6.7% (1) 26.9% (7) 18.2% (6)
.Santa Barbara
.Santa Clara 7.1% (1) 15.8% (3) 18.3% (11) 19.8% (18) 16.7% (31) 19.3% (43) 25% (2) 5.9% (1)
.Santa Cruz 0% (0) 14.3% (1) 14.3% (1) 0% (0)
.Solano 0% (0) 0% (0) 12.5% (1) 0% (0) 8.8% (3) 11.1% (3) 17.6% (3) 0% (0)
.Sonoma 0% (0) 7.1% (1) 33.3% (4) 41.2% (7) 22.3% (21) 27.1% (23) 50% (1) 5.6% (1)
.Stanislaus 0% (0) 0% (0) 27.6% (16) 13% (7) 27.3% (44) 24.6% (30) 13.3% (2) 15.8% (3)
.Tulare 0% (0) 0% (0) 10.7% (3) 19.5% (8) 5.1% (3) 4.7% (3) 0% (0) 0% (0)
.Ventura 0% (0) 0% (0) 14.3% (4) 18.2% (22) 27.8% (10) 13.7% (18) 2.1% (1) 0% (0)
.Yolo 0% (0) 0% (0) 21.4% (3) 22.2% (2) 20% (13) 25% (16) 0% (0) 0% (0)
Small Counties 4.9% (3) 5.2% (5) 22% (39) 18.9% (43) 25.8% (72) 19% (67) 14.3% (5) 8.6% (5)
Total 6.8% (40) 5.7% (48) 23.7% (381) 18.7% (387) 23.9% (1,060) 19.7% (994) 13.1% (77) 9.1% (60)
Black shading indicates where data was unavailable to calculate an indicator.
22
Table 3.4-1 – Homelessness and Housing Rates for all consumers (CSI) – Missing and Unknown Data
County Unknown/Missing
FY 08-09 FY 09-10
.Alameda 7% (1,153) 3.9% (707)
.Butte 2.9% (149) 3.4% (250)
.Contra Costa 22.2% (2,747) 22.1% (2,955)
.Fresno 10.3% (687) 12.8% (808)
.Kern 5.3% (1,462) 4.9% (1,671)
.Los Angeles 5.9% (40) 6.4% (34)
.Marin 3.5% (21) 3.7% (21)
.Merced 1% (5) 2.5% (11)
.Monterey 3% (115) 7.3% (538)
.Orange 38% (11,014) 39.7% (12,504)
.Placer 11.7% (520) 12.1% (461)
.Riverside 7% (221) 6.5% (221)
.Sacramento 20.7% (572)
.San Bernardino 6.3% (779) 6.1% (864)
.San Diego 18.4% (9,506) 16.5% (11,792)
.San Francisco 14.1% (1,478) 12.3% (1,480)
.San Joaquin 12.3% (655) 5.5% (198)
.San Luis Obispo 4.2% (168) 4.1% (170)
.San Mateo 19.1% (1,846) 19% (1,798)
.Santa Barbara 43.3% (1,149) 48.7% (1,265)
.Santa Clara 14.4% (167) 16.5% (142)
.Santa Cruz 80.9% (297) 72.1% (194)
.Solano 5.5% (121) 4.6% (142)
.Sonoma 2.6% (16) 5% (42)
.Stanislaus 3.1% (119) 2.3% (81)
.Tulare 0.7% (61) 0.8% (70)
.Ventura 2.2% (264) 4.5% (548)
.Yolo 26.4% (1,358) 30.5% (1,406)
Small Counties 19.9% (11,525) 21.2% (12,695)
Total 16.1% (48,215) 15.7% (53,068)
Black shading indicates where data was unavailable to calculate an indicator.
23
Table 3.4-2 – Homelessness and Housing Rates for FSP consumers – Missing and Unknown Data
Unknown/Missing
County
FY 2008-09 FY 2009-10
Alameda
Butte 48.9% (45) 58% (47)
Contra Costa 46.8% (104) 62.7% (247)
Fresno 40.4% (137) 57.1% (306)
Kern 52.3% (229) 60.8% (275)
Los Angeles 36.7% (1,250) 43.4% (1,917)
Marin
Merced 42% (37) 47.3% (53)
Monterey
Orange 26.2% (358) 23.2% (253)
Placer 26.4% (34) 18.1% (17)
Riverside
Sacramento 52.1% (250) 49.9% (582)
San Bernardino 60.6% (536) 67.8% (812)
San Diego 40.8% (476) 47.6% (906)
San Francisco 53.5% (302) 56.6% (328)
San Joaquin 54.6% (191) 63.7% (485)
San Luis Obispo 54.6% (53) 57.4% (78)
San Mateo 44.4% (24) 33.3% (24)
Santa Barbara
Santa Clara 34.8% (143) 34.5% (184)
Santa Cruz 87.7% (136) 69.7% (53)
Solano 28.7% (25) 49% (50)
Sonoma 12.2% (17) 18.3% (30)
Stanislaus 38.9% (155) 38.6% (130)
Tulare 43.2% (67) 41.6% (77)
Ventura 52.2% (131) 57.4% (376)
Yolo 33.1% (43) 30.6% (33)
Small Counties 44.2% (438) 56% (936)
Total 41.8% (5,181) 48.7% (8,199)
Black shading indicates where data was unavailable to calculate an indicator.
24
Priority Indicator 4: Arrest Rates
Table 4-1 – Proportion of youth who were arrested prior to beginning services and since receiving
services (CPS)
Arrested 12 months prior to services Arrested since receiving services
County
Yes No Yes No
Alameda 15.1% (21) 84.9% (118) 8.5% (12) 91.5% (129)
Butte 3.2% (2) 96.8% (61) 6.3% (4) 93.7% (59)
Contra Costa 9.7% (6) 90.3% (56) 14.5% (9) 85.5% (53)
Fresno 19.0% (15) 81.0% (64) 18.3% (15) 81.7% (67)
Kern 12.0% (10) 88.0% (73) 10.7% (9) 89.3% (75)
Los Angeles 14.0% (140) 86.0% (861) 11.0% (112) 89.0% (910)
Marin 21.7% (5) 78.3% (18) 18.2% (4) 81.8% (18)
Merced 0.0% (0) 100.0% (3) 33.3% (1) 66.7% (2)
Monterey 36.8% (14) 63.2% (24) 31.6% (12) 68.4% (26)
Orange
Placer
Riverside 22.5% (20) 77.5% (69) 23.3% (21) 76.7% (69)
Sacramento 10.0% (32) 90.0% (289) 10.0% (33) 90.0% (290)
San Bernardino 13.0% (26) 87.0% (174) 11.5% (23) 88.5% (177)
San Diego 12.0% (54) 88.0% (396) 10.9% (49) 89.1% (399)
San Francisco 18.9% (14) 81.1% (60) 13.2% (10) 86.8% (66)
San Joaquin 11.8% (2) 88.2% (15) 17.6% (3) 82.4% (14)
San Luis Obispo 33.3% (1) 66.7% (2) 25.0% (1) 75.0% (3)
San Mateo 19.2% (10) 80.8% (42) 7.4% (4) 92.6% (50)
Santa Barbara 25.0% (2) 75.0% (6) 22.2% (2) 78.8% (7)
Santa Clara 17.7% (36) 82.3% (167) 13.7% (28) 86.3% (177)
Santa Cruz 13.2% (5) 86.8% (33) 12.8% (5) 87.2% (34)
Solano 33.3% (4) 66.7% (8) 0.0% (0) 100.0% (12)
Sonoma 14.8% (4) 85.2% (23) 17.9% (5) 82.1% (23)
Stanislaus 10.0% (9) 90.0% (81) 9.8% (9) 90.2% (83)
Tulare 16.0% (4) 84.0% (21) 7.1% (2) 92.9% (26)
Ventura 11.5% (6) 88.5% (46) 16.7% (9) 83.3% (45)
Yolo 0.0% (0) 100.0% (1) 0.0% (0) 100.0% (1)
Small Counties 21.5% (32) 78.5% (117) 19.6% (30) 80.4% (123)
Total 14.4% (474) 85.6% (2,828) 12.3% (412) 87.7% (2,936)
Black shading indicates where data was unavailable to calculate an indicator.
25
Table 4-2 – Proportion of adults who were arrested prior to beginning services and since receiving
services (CPS)
Arrested 12 months prior to services Arrested since receiving services
County
Yes No Yes No
Alameda 25.0% (26) 75.0% (78) 22.0% (24) 78.0% (85)
Butte 32.3% (10) 67.7% (21) 19.4% (6) 80.6% (25)
Contra Costa 9.1% (3) 90.9% (30) 17.6% (6) 82.4% (28)
Fresno 9.4% (5) 90.6% (48) 11.1% (6) 88.9% (48)
Kern 16.1% (15) 83.9% (78) 11.8% (11) 88.2% (82)
Los Angeles 11.0% (90) 89.0% (728) 7.1% (59) 92.9% (768)
Marin 13.8% (4) 86.2% (25) 6.9% (2) 93.1% (27)
Merced 7.7% (1) 92.3% (12) 7.1% (1) 92.9% (13)
Monterey 20.8% (5) 79.2% (19) 16.7% (4) 83.3% (20)
Orange
Placer
Riverside 11.3% (15) 88.7% (118) 9.7% (13) 90.3% (121)
Sacramento 16.6% (38) 83.4% (191) 12.1% (28) 87.9% (203)
San Bernardino 15.5% (24) 84.5% (131) 9.4% (15) 90.6% (145)
San Diego 15.7% (39) 84.3% (209) 5.2% (13) 94.8% (238)
San Francisco 12.5% (21) 87.5% (147) 4.1% (7) 95.9% (165)
San Joaquin 30.0% (6) 70.0% (14) 15.0% (3) 85.0% (17)
San Luis Obispo 29.6% (8) 70.4% (19) 14.8% (4) 85.2% (23)
San Mateo 14.8% (9) 85.2% (52) 11.3% (7) 88.7% (55)
Santa Barbara 44.4% (4) 55.6% (5) 20.0% (2) 80.0% (8)
Santa Clara 22.2% (30) 77.8% (105) 9.6% (13) 90.4% (122)
Santa Cruz 11.5% (3) 88.5% (23) 7.7% (2) 92.3% (24)
Solano 22.2% (4) 77.8% (14) 16.7% (3) 83.3% (15)
Sonoma 25.7% (9) 74.3% (26) 28.6% (10) 71.4% (25)
Stanislaus 21.5% (14) 78.5% (51) 10.8% (7) 89.2% (58)
Tulare 13.5% (5) 86.5% (32) 8.3% (3) 91.7% (33)
Ventura 15.1% (8) 84.9% (45) 7.4% (4) 92.6% (50)
Yolo
Small Counties 15.3% (39) 84.7% (216) 9.3% (24) 90.7% (233)
Total 15.1% (435) 84.9% (2,437) 9.5% (277) 90.5% (2,631)
Black shading indicates where data was unavailable to calculate an indicator.
26
Table 4-3 – Proportion of older adults who were arrested prior to beginning services and since receiving
services (CPS)
County Arrested 12 months prior to services Arrested since receiving services
Yes No Yes No
Alameda 0.0% (0) 100.0% (9) 0.0% (0) 100.0% (9)
Butte 0.0% (0) 100.0% (1) 0.0% (0) 100.0% (1)
Contra Costa 33.3% (1) 66.7% (2) 0.0% (0) 100.0% (3)
Fresno 0.0% (0) 100.0% (3) 0.0% (0) 100.0% (3)
Kern 0.0% (0) 100.0% (1) 0.0% (0) 100.0% (1)
Los Angeles 3.2% (3) 96.8% (92) 1.1% (1) 98.9% (93)
Marin 0.0% (0) 100.0% (3) 0.0% (0) 100.0% (3)
Merced 0.0% (0) 100.0% (1) 0.0% (0) 100.0% (1)
Monterey 0.0% (0) 100.0% (1) 0.0% (0) 100.0% (1)
Orange
Placer
Riverside 3.4% (1) 96.6% (28) 3.4% (1) 96.6% (28)
Sacramento 12.5% (2) 87.5% (14) 12.5% (2) 87.5% (14)
San Bernardino 0.0% (0) 100.0% (6) 0.0% (0) 100.0% (6)
San Diego 4.0% (1) 96.0% (24) 0.0% (0) 100.0% (24)
San Francisco 9.1% (3) 90.9% (30) 6.3% (2) 93.7% (30)
San Joaquin
San Luis Obispo 100.0% (1) 0.0% (0) 0.0% (0) 100.0% (1)
San Mateo 20.0% (1) 80.0% (4) 0.0% (0) 100.0% (5)
Santa Barbara
Santa Clara 5.6% (1) 94.4% (17) 0.0% (0) 100.0% (18)
Santa Cruz
Solano
Sonoma 0.0% (0) 100.0% (3) 0.0% (0) 100.0% (3)
Stanislaus
Tulare
Ventura 50.0% (2) 50.0% (2) 25.0% (1) 75.0% (3)
Yolo
Small Counties 7.1% (1) 92.9% (13) 0.0% (0) 100.0% (13)
Total 6.3% (17) 93.7% (254) 2.6% (7) 97.4% (260)
Black shading indicates where data was unavailable to calculate an indicator.
27
Table 4-4 – Proportion of consumer/clients who were arrested prior to beginning services and since
receiving services (CPS) – Missing and Unknown Data
County FY 2008-09
Alameda 18.9% (119)
Butte 12.8% (28)
Contra Costa 5.8% (12)
Fresno 17.0% (56)
Kern 15.9% (67)
Los Angeles 18.8% (891)
Marin 25.7% (38)
Merced 30.0% (15)
Monterrey 13.7% (20)
Placer 0% (0)
Riverside 12.8% (74)
Sacramento 18.9% (264)
San Bernardino 15.9% (137)
San Diego 9.7% (156)
San Francisco 11.3% (71)
San Joaquin 19.6% (18)
San Luis Obispo 8.8% (6)
San Mateo 10.2% (27)
Santa Barbara 22.7% (10)
Santa Clara 10.5% (84)
Santa Cruz 9.2% (13)
Solano 23.1% (18)
Sonoma 17.6% (24)
Stanislaus 6.0% (20)
Tulare 20.3% (32)
Ventura 10.9% (27)
Yolo 0.0% (0)
Berkeley 10.7% (3)
Small Counties 15.9% (159)
Total 15.5% (2379)
Black shading indicates where data was unavailable to calculate an indicator.
28
Table 4-5 – Proportion of children who were arrested 12 months prior to beginning services
FY 2008-09 FY 2009-10
County
Yes No Yes No
Alameda
Butte 37.5% (3) 62.5% (5) 0.0% (0) 100.0% (1)
Contra Costa 2.7% (2) 97.3% (73) 4.8% (2) 95.2% (40)
Fresno 0.0% (0) 100.0% (40) 34.8% (40) 65.2% (75)
Kern 17.6% (3) 82.4% (14) 6.3% (1) 93.8% (15)
Los Angeles 7.3% (72) 92.7% (913) 5.5% (68) 94.5% (1,177)
Marin
Merced 17.1% (6) 82.9% (29) 7.9% (3) 92.1% (35)
Monterey
Orange 7.3% (11) 92.7% (139) 5.2% (3) 94.8% (55)
Placer 11.1% (1) 88.9% (8) 0.0% (0) 100.0% (7)
Riverside
Sacramento 3.8% (2) 96.2% (51) 2.9% (1) 97.1% (33)
San Bernardino 18.1% (39) 81.9% (176) 21.1% (97) 78.9% (362)
San Diego 7.1% (10) 92.9% (130) 4.0% (24) 96.0% (579)
San Francisco 15.7% (14) 84.3% (75) 16.7% (16) 83.3% (80)
San Joaquin 41.7% (5) 58.3% (7) 18.8% (9) 81.3% (39)
San Luis Obispo 33.3% (4) 66.7% (8) 4.7% (3) 95.3% (61)
San Mateo 27.3% (3) 72.7% (8) 40.0% (6) 60.0% (9)
Santa Barbara 13.6% (3) 86.4% (19) 19.2% (5) 80.8% (21)
Santa Clara 28.9% (13) 71.1% (32) 34.9% (15) 65.1% (28)
Santa Cruz
Solano 15.0% (3) 85.0% (17) 13.3% (2) 86.7% (13)
Sonoma 12.1% (4) 87.9% (29) 9.4% (3) 90.6% (29)
Stanislaus 73.3% (11) 26.7% (4) 85.7% (12) 14.3% (2)
Tulare 0.0% (0) 100.0% (3) 0.0% (0) 100.0% (4)
Ventura 64.4% (29) 35.6% (16) 100.0% (5) 0.0% (0)
Yolo 0.0% (0) 100.0% (1)
Small Counties 27.5% (49) 72.5% (129) 28.2% (59) 71.8% (150)
Total 13.0% (287) 87.0% (1,926) 11.7% (374) 88.3% (2,815)
Black shading indicates where data was unavailable to calculate an indicator.
29
Table 4-6 – Proportion of TAY who were arrested 12 months prior to beginning services
FY 2008-09 FY 2009-10
County
Yes No Yes No
Alameda
Butte 33.3% (9) 66.7% (18) 23.8% (5) 76.2% (16)
Contra Costa 26.2% (11) 73.8% (31) 28.3% (15) 71.7% (38)
Fresno 26.4% (23) 73.6% (64) 45.2% (47) 54.8% (57)
Kern 38.6% (32) 61.4% (51) 48.9% (46) 51.1% (48)
Los Angeles 21.0% (117) 79.0% (441) 24.9% (145) 75.1% (437)
Marin
Merced 41.2% (7) 58.8% (10) 38.9% (7) 61.1% (11)
Monterey
Orange 53.9% (137) 46.1% (117) 53.4% (71) 46.6% (62)
Placer 16.7% (2) 83.3% (10) 62.5% (5) 37.5% (3)
Riverside
Sacramento 25.0% (9) 75.0% (27) 30.4% (21) 69.6% (48)
San Bernardino 63.1% (157) 36.9% (92) 35.6% (186) 64.4% (337)
San Diego 25.7% (47) 74.3% (136) 22.6% (84) 77.4% (288)
San Francisco 41.4% (29) 58.6% (41) 36.6% (26) 63.4% (45)
San Joaquin 41.6% (42) 58.4% (59) 24.2% (32) 75.8% (100)
San Luis Obispo 13.3% (2) 86.7% (13) 35.1% (13) 64.9% (24)
San Mateo 37.5% (6) 62.5% (10) 33.3% (9) 66.7% (18)
Santa Barbara 16.7% (1) 83.3% (5) 35.3% (6) 64.7% (11)
Santa Clara 46.6% (34) 53.4% (39) 65.5% (57) 34.5% (30)
Santa Cruz 20.0% (1) 80.0% (4)
Solano 33.3% (5) 66.7% (10) 44.4% (8) 55.6% (10)
Sonoma 54.5% (6) 45.5% (5) 33.3% (9) 66.7% (18)
Stanislaus 42.0% (21) 58.0% (29) 52.9% (27) 47.1% (24)
Tulare 43.2% (16) 56.8% (21) 30.0% (15) 70.0% (35)
Ventura 64.4% (47) 35.6% (26) 26.9% (92) 73.1% (250)
Yolo 21.4% (3) 78.6% (11) 0.0% (0) 100.0% (1)
Small Counties 38.3% (70) 61.7% (113) 44.1% (104) 55.9% (132)
Total 37.6% (834) 62.4% (1,383) 33.5% (1,030) 66.5% (2,043)
Black shading indicates where data was unavailable to calculate an indicator.
30
Table 4-7 – Proportion of adults who were arrested 12 months prior to beginning services
FY 2008-09 FY 2009-10
County
Yes No Yes No
Alameda
Butte 26.8% (11) 73.2% (30) 8.4% (7) 91.6% (76)
Contra Costa 21.8% (12) 78.2% (43) 37.0% (17) 63.0% (29)
Fresno 15.8% (38) 84.2% (202) 27.7% (26) 72.3% (68)
Kern 49.2% (58) 50.8% (60) 37.2% (45) 62.8% (76)
Los Angeles 20.3% (310) 79.7% (1,220) 24.5% (229) 75.5% (707)
Marin
Merced 23.1% (3) 76.9% (10) 14.3% (1) 85.7% (6)
Monterey
Orange 53.0% (124) 47.0% (110) 54.9% (79) 45.1% (65)
Placer 35.7% (10) 64.3% (18) 43.5% (10) 56.5% (13)
Riverside
Sacramento 11.1% (10) 88.9% (80) 10.3% (77) 89.7% (670)
San Bernardino 27.0% (142) 73.0% (384) 30.3% (107) 69.7% (246)
San Diego 32.9% (48) 67.1% (98) 11.2% (78) 88.8% (618)
San Francisco 23.0% (41) 77.0% (137) 38.0% (27) 62.0% (44)
San Joaquin 23.2% (83) 76.8% (275) 14.9% (78) 85.1% (447)
San Luis Obispo 33.3% (6) 66.7% (12) 60.6% (20) 39.4% (13)
San Mateo
Santa Barbara 8.5% (13) 91.5% (140) 10.7% (18) 89.3% (150)
Santa Clara 59.4% (82) 40.6% (56) 54.1% (79) 45.9% (67)
Santa Cruz 17.6% (6) 82.4% (28)
Solano 23.1% (3) 76.9% (10) 40.7% (24) 59.3% (35)
Sonoma 58.3% (14) 41.7% (10) 52.0% (13) 48% (12)
Stanislaus 29.4% (35) 70.6% (84) 19.7% (15) 80.3% (61)
Tulare 26.3% (25) 30.4% (24) 30.4% (24) 69.6% (55)
Ventura 28.3% (15) 71.7% (38) 7.1% (50) 92.9% (653)
Yolo 13.3% (6) 86.7% (39) 15.0% (3) 85.0% (17)
Small Counties 26.4% (115) 72.6% (320) 21.8% (92) 78.2% (330)
Total 26.1% (1,210) 73.9% (3,428) 20.1% (1,119) 79.9% (4,458)
Black shading indicates where data was unavailable to calculate an indicator.
31
Table 4-8 – Proportion of older adults who were arrested 12 months prior to beginning services
FY 2008-09 FY 2009-10
County
Yes No Yes No
Alameda
Butte 0.0% (0) 100.0% (2) 6.7% (2) 93.3% (28)
Contra Costa 0.0% (0) 100.0% (6) 0.0% (0) 100.0% (6)
Fresno 12.5% (1) 87.5% (7) 0.0% (0) 100.0% (3)
Kern 0.0% (0) 100.0% (17) 17.6% (3) 82.4% (14)
Los Angeles 10.2% (16) 89.8% (141) 11.1% (9) 88.9% (72)
Marin
Merced 0.0% (0) 100.0% (1)
Monterey
Orange 11.5% (3) 88.5% (23) 7.5% (3) 92.5% (37)
Placer 18.2% (2) 81.8% (9) 25.0% (1) 75.0% (3)
Riverside
Sacramento 1.9% (1) 98.1% (51) 1.0% (1) 99.0% (103)
San Bernardino 0.0% (0) 100.0% (7) 9.5% (2) 90.5% (19)
San Diego 3.2% (2) 96.8% (60) 5.1% (5) 94.9% (93)
San Francisco 8.8% (3) 91.2% (31) 6.3% (1) 93.8% (15)
San Joaquin 2.3% (2) 97.7% (84) 4.1% (3) 95.9% (70)
San Luis Obispo 16.7% (1) 83.3% (5) 25.0% (2) 75.0% (6)
San Mateo
Santa Barbara 0.0% (0) 100.0% (18) 0.0% (0) 100.0% (25)
Santa Clara 9.1% (1) 90.9% (10) 28.6% (2) 71.4% (5)
Santa Cruz 0.0% (0) 100.0% (2)
Solano 9.1% (1) 90.9% (10) 22.2% (2) 77.8% (7)
Sonoma 100.0% (1) 0.0% (0) 0.0% (0) 100.0% (50)
Stanislaus 0.0% (0) 100.0% (8) 0.0% (0) 100.0% (8)
Tulare 0.0% (0) 100.0% (1) 0.0% (0) 100.0% (3)
Ventura 4.8% (3) 95.2% (59) 2.5% (2) 97.5% (79)
Yolo 0.0% (0) 100.0% (7) 0.0% (0) 100.0% (1)
Small Counties 5.8% (4) 94.2% (65) 11.3% (9) 88.8% (71)
Total 6.2% (41) 93.8% (624) 6.1% (47) 93.9% (718)
Black shading indicates where data was unavailable to calculate an indicator.
32
Table 4-9 – Proportion of consumers/clients who were arrested 12 months prior to beginning services –
Unknown and Missing Data
County
FY 2008-09 FY 2009-10
Alameda
Butte 2.5% (2) 0% (0)
Contra Costa 1.7% (3) 0% (0)
Fresno 3.4% (13) 12.1% (44)
Kern 0.4% (1) 0.4% (1)
Los Angeles 0% (0) 0% (0)
Marin
Merced 1.5% (1) 0% (0)
Monterey
Orange 1.0% (2) 3.1% (8)
Placer 0% (0) 0% (0)
Riverside
Sacramento 5.7% (14) 2.4% (23)
San Bernardino 28.6% (400) 0% (0)
San Diego 1.5% (8) 2.6% (47)
San Francisco 0.5% (2) 0% (0)
San Joaquin 0.5% (3) 0.1% (1)
San Luis Obispo 1.9% (1) 0% (0)
San Mateo 12.1% (4) 2.3% (1)
Santa Barbara 17.4% (42) 19.2% (56)
Santa Clara 1.1% (3) 4.4% (13)
Santa Cruz 4.9% (2)
Solano 3.3% (2) 4.7% (5)
Sonoma 0% (0) 0% (0)
Stanislaus 0% (0) 0% (0)
Tulare 0% (0) 2.9% (4)
Ventura 1.7% (4) 0.4% (4)
Yolo 0% (0) 0% (0)
Small Counties 3.0% (27) 2.6% (25)
Total 5.2% (534) 1.8% (232)
Black shading indicates where data was unavailable to calculate an indicator.
33
Priority Indicator 5: Demographic Profile of Consumers Served
Table 5-1 - Race/ethnicity of mental health consumers by county
County White Hispanic / Latino Asian Pacific Islander Black American Indian Multirace Other
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
- - - - - - - - - - - - - - - -
8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
Alameda 25.5% 25.1% 9.1% 9.3% 8.5% 8.8% 0.2% 0.2% 39.9% 39.2% 0.6% 0.5% 11.6% 11.8% 4.6% 5.1%
(8,248) (8,407) (2,961) (3,106) (2,757) (2,942) (78) (79) (12,914) (13,165) (183) (174) (3,742) (3,971) (1,491) (1,707)
Butte 70.3% 67.9% 4.6% 6.2% 7.1% 7.4% 0.1% 0.1% 2.7% 2.9% 2.0% 1.9% 11.9% 13.0% 1.3% 0.6%
(4,150) (3,286) (274) (302) (419) (356) (5) (6) (162) (139) (118) (91) (702) (628) (77) (31)
Contra Costa 39.6% 38.5% 2.0% 1.7% 6.2% 5.7% 0.2% 0.3% 25.6% 25.5% 0.4% 0.5% 24.2% 26.2% 1.8% 1.8%
(6,293) (6,749) (319) (291) (987) (997) (27) (53) (4,071) (4,465) (68) (81) (3,841) (4,587) (280) (313)
Fresno 34.1% 32.6% 40.4% 42.6% 8.2% 7.5% 0.0% 0.0% 13.7% 13.7% 1.0% 0.9% 1.9% 2.1% 0.6% 0.6%
(5,537) (5,024) (6,557) (6,576) (1,332) (1,162) (8) (3) (2,227) (2,116) (157) (136) (307) (321) (99) (92)
Kern 46.7% 44.7% 34.8% 36.4% 1.1% 1.0% 0.1% 0.1% 11.3% 11.6% 0.9% 0.9% 3.4% 3.4% 1.7% 1.9%
(8,184) (7,555) (6,098) (6,142) (188) (169) (15) (10) (1,987) (1,960) (166) (150) (597) (579) (296) (329)
Los Angeles 22.7% 22.0% 47.5% 48.9% 0.9% 0.9% 0.0% 0.0% 28.0% 27.5% 0.6% 0.6% 0.1% 0.1% 0.2% 0.1%
(38,619) (37,638) (80,693) (83,760) (1,609) (1,499) (67) (63) (47,530) (47,193) (987) (945) (169) (179) (260) (173)
Marin 65.4% 64.7% 13.2% 14.8% 2.3% 2.5% 0.1% 0.1% 8.5% 7.5% 0.4% 0.3% 9.4% 9.1% 0.8% 1.1%
(2,110) (1,954) (427) (448) (74) (74) (2) (2) (273) (225) (12) (8) (305) (275) (25) (33)
Merced 41.6% 40.8% 29.8% 27.6% 8.7% 8.8% 0.0% 0.0% 9.8% 9.8% 0.8% 0.5% 7.3% 9.9% 2.0% 2.5%
(1,868) (1,733) (1,339) (1,174) (391) (376) (2) (2) (439) (418) (36) (23) (329) (420) (88) (105)
Monterey 31.3% 28.2% 29.5% 52.3% 2.3% 2.4% 0.4% 0.1% 5.8% 4.6% 0.6% 0.4% 9.5% 10.8% 20.7% 1.1%
(1,790) (1,357) (1,685) (2,515) (132) (117) (20) (5) (329) (223) (34) (20) (541) (521) (1,183) (52)
Orange 42.4% 41.6% 33.6% 35.2% 9.7% 9.2% 0.2% 0.2% 4.3% 4.4% 0.5% 0.4% 4.7% 4.9% 4.7% 4.1%
(17,523) (17,338) (13,876) (14,653) (3,998) (3,816) (90) (87) (1,778) (1,812) (193) (174) (1,925) (2,048) (1,954) (1,725)
Placer 74.7% 73.8% 9.7% 9.6% 1.2% 1.2% 0.1% 0.1% 2.2% 2.5% 1.3% 1.1% 9.4% 10.0% 1.4% 1.7%
(2,009) (1,555) (260) (203) (32) (25) (2) (3) (59) (52) (34) (23) (254) (210) (38) (35)
Riverside 42.2% 43.2% 28.0% 28.0% 1.4% 1.5% 0.1% 0.1% 12.9% 12.9% 0.5% 0.5% 12.6% 11.0% 2.3% 2.1%
(16,460) (16,386) (10,901) (10,615) (546) (580) (31) (34) (5,011) (5,150) (211) (184) (4,929) (4,153) (886) (811)
Sacramento 43.2% 42.6% 12.8% 14.0% 7.6% 6.4% 0.2% 0.2% 23.7% 23.7% 0.7% 0.7% 10.4% 10.6% 1.5% 2.1%
(13,226) (22,319) (3,917) (7,337) (2,342) (3,360) (46) (91) (7,251) (12,216) (214) (376) (3,171) (5,543) (463) (1,105)
San Bernardino 40.9% 39.1% 22.7% 23.6% 2.0% 1.9% 0.2% 0.4% 18.1% 17.4% 0.7% 0.6% 12.8% 14.1% 2.6% 2.8%
(15,558) (14,433) (8,617) (8,706) (756) (708) (95) (143) (6,868) (6,418) (259) (235) (4,866) (5,218) (998) (1,024)
San Diego 45.2% 44.4% 25.9% 26.4% 4.9% 4.7% 0.2% 0.2% 12.5% 12.3% 0.7% 0.6% 9.2% 10.0% 1.4% 1.3%
(22,248) (21,363) (12,739) (12,683) (2,419) (2,274) (74) (95) (6,156) (5,915) (354) (300) (4,510) (4,821) (690) (637)
San Francisco 34.5% 34.8% 16.1% 17.8% 13.3% 12.8% 0.4% 0.3% 25.1% 23.9% 0.7% 0.7% 6.7% 6.4% 3.2% 3.3%
(6,487) (6,440) (3,025) (3,295) (2,500) (2,357) (69) (56) (4,708) (4,415) (133) (126) (1,254) (1,181) (607) (615)
San Joaquin 38.1% 36.9% 19.9% 20.2% 10.4% 10.6% 0.1% 0.1% 16.3% 17.1% 0.8% 0.9% 12.9% 12.8% 1.4% 1.3%
(4,872) (4,663) (2,540) (2,555) (1,334) (1,340) (16) (15) (2,087) (2,157) (108) (116) (1,654) (1,610) (183) (164)
Black shading indicates where data was unavailable to calculate an indicator.
34
County White Hispanic / Latino Asian Pacific Islander Black American Indian Multirace Other
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
- - - - - - - - - - - - - - - -
8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
San Luis Obispo 71.5% 69.5% 15.7% 16.4% 1.0% 1.0% 0.0% 0.0% 2.2% 2.1% 0.4% 0.3% 8.3% 9.3% 0.9% 1.3%
(3,162) (3,135) (696) (739) (46) (45) (1) (1) (96) (96) (16) (13) (365) (421) (41) (58)
San Mateo 37.1% 36.5% 34.5% 35.9% 7.5% 8.0% 0.3% 0.3% 10.5% 9.6% 0.3% 0.4% 5.1% 4.9% 4.7% 4.5%
(3,905) (3,973) (3,630) (3,905) (791) (866) (34) (39) (1,103) (1,043) (35) (39) (539) (538) (496) (488)
Santa Barbara 40.6% 36.8% 43.4% 50.8% 0.9% 0.7% 0.1% 0.1% 3.9% 3.4% 0.8% 0.6% 10.3% 7.6% 0.1% 0.0%
(2,258) (1,970) (2,411) (2,714) (48) (38) (4) (4) (218) (181) (43) (32) (575) (405) (3) (2)
Santa Clara 39.8% 39.0% 24.6% 24.0% 17.5% 19.0% 0.2% 0.2% 6.7% 6.8% 0.8% 0.7% 5.3% 5.1% 5.2% 5.1%
(3,458) (2,766) (2,135) (1,703) (1,521) (1,348) (19) (13) (581) (482) (66) (48) (465) (363) (450) (362)
Santa Cruz 53.7% 52.3% 32.5% 33.0% 0.8% 1.0% 0.0% 0.0% 2.5% 2.5% 0.6% 0.5% 8.5% 9.5% 1.3% 1.1%
(2,240) (2,079) (1,357) (1,314) (35) (40) (1) (1) (105) (101) (26) (21) (355) (379) (54) (42)
Solano 40.8% 40.4% 13.8% 13.5% 4.7% 5.1% 0.2% 0.2% 27.7% 27.3% 0.8% 0.5% 10.5% 11.6% 1.4% 1.5%
(2,097) (1,853) (711) (617) (241) (232) (9) (9) (1,425) (1,252) (42) (24) (542) (530) (71) (70)
Sonoma 67.5% 67.9% 10.4% 10.2% 1.7% 1.8% 0.2% 0.2% 3.7% 3.4% 1.0% 0.8% 14.6% 14.9% 0.9% 0.8%
(2,808) (2,986) (433) (450) (69) (77) (8) (9) (155) (149) (42) (37) (607) (655) (37) (35)
Stanislaus 44.1% 43.7% 23.3% 23.5% 4.1% 4.4% 0.1% 0.1% 4.5% 4.4% 0.7% 0.6%) 19.9% 20.4% 3.3% 3.0%
(4,024) (3,889) (2,125) (2,095) (377) (394) (11) (6) (408) (393) (61) (50) (1,818) (1,817) (303) (263)
Tulare 32.4% 30.8% 48.8% 50.6% 2.5% 2.4% 0.0% 0.0% 3.0% 2.8% 0.6% 0.5% 11.4% 11.5% 1.2% 1.3%
(2,897) (2,768) (4,365) (4,550) (228) (219) (2) (0) (272) (255) (52) (41) (1,023) (1,035) (107) (116)
Ventura 49.8% 46.6% 30.8% 31.3% 1.5% 1.5% 0.0% 0.0% 3.9% 3.8% 0.5% 0.5% 12.1% 14.5% 1.3% 1.8%
(5,261) (4,603) (3,249) (3,096) (157) (148) (3) (4) (416) (379) (55) (45) (1,276) (1,432) (137) (177)
Yolo 64.8% 63.4% 7.1% 6.3% 2.6% 3.0% 0.0% 0.2% 5.3% 5.5% 0.7% 0.7% 18.1% 19.5% 1.3% 1.4%
(1,787) (1,946) (197) (193) (71) (91) (1) (6) (147) (170) (20) (21) (500) (597) (36) (44)
Small Counties 64.0% 62.9% 19.0% 19.2% 1.9% 1.9% 0.1% 0.1% 3.3% 3.2% 2.3% 2.5% 8.4% 9.2% 1.0% 1.0%
(30,040) (28,162) (8,896) (8,607) (905) (863) (42) (52) (1,564) (1,425) (1,076) (1,107) (3,927) (4,125) (476) (438)
Total 38.3% 37.3% 29.8% 30.4% 4.2% 4.2% 0.1% 0.1% 17.7% 17.9% 0.8% 0.7% 7.2% 7.6% 1.9% 1.9%
(239,174) (238,330) (186,432) (194,344) (26,305) (26,513) (782) (885) (110,340) (113,965) (4,801) (4,640) (45,108) (48,562) (11,829) (11,046)
Black shading indicates where data was unavailable to calculate an indicator.
35
Table 5-2 - Race/ethnicity of new mental health consumers by county/Unknown and Missing
Unknown/Missing
County
FY 08-09 FY 09-10
Alameda 3.8% (1,275) 3.6% (1,257)
Butte 5.2% (322) 3.6% (181)
Contra Costa 2.7% (446) 2.3% (417)
Fresno 6.2% (1,065) 5.9% (968)
Kern 0.7% (116) 0.6% (96)
Los Angeles 11.2% (21,363) 10.0% (19,045)
Marin 2.9% (97) 3.6% (112)
Merced 12.7% (656) 5.0% (222)
Monterey 7.7% (478) 10.5% (567)
Orange 7.4% (3,306) 6.7% (3,014)
Placer 26.2% (956) 23.9% (661)
Riverside 7.1% (2,962) 8.0% (3,312)
Sacramento 1.5% (456) 20.4% (13,444)
San Bernardino 4.1% (1,630) 3.7% (1,425)
San Diego 4.4% (2,276) 4.6% (2,331)
San Francisco 19.5% (4,545) 24.1% (5,861)
San Joaquin 5.0% (677) 4.8% (643)
San Luis Obispo 0.5% (20) 0.8% (36)
San Mateo 7.3% (825) 7.5% (887)
Santa Barbara 26.4% (1,993) 29.9% (2,277)
Santa Clara 6.3% (583) 6.3% (475)
Santa Cruz 2.5% (109) 2.8% (116)
Solano 1.2% (65) 1.4% (63)
Sonoma 2.0% (85) 1.6% (70)
Stanislaus 2.1% (199) 1.9% (169)
Tulare 0.1% (12) 0.2% (21)
Ventura 3.3% (365) 3.4% (349)
Yolo 5.7% (168) 6.0% (196)
Small Counties 4.6% (2,253) 4.8% (2,275)
Total 7.3% (49,303) 9.6% (60,490)
Black shading indicates where data was unavailable to calculate an indicator.
36
Table 5-3 - Race/ethnicity of FSP consumers by county
County Hispanic / Pacific American
White Asian Black Multirace Other
Latino Islander Indian
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
- - - - - - - - - - - - - - - -
8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
Alameda
Butte 80.0% 81.8% 0.9% 3.5% 0.0% 0.05 0.0% 0.0% 4.3% 2.0% 3.5% 3.0% 10.4% 8.1% 0.9% 1.5%
(92) (162) (1) (7) (0) (0) (0) (0) (5) (4) (4) (6) (12) (16) (1) (3)
Contra Costa 20.9% 24.0% 1.9% 1.8% 6.6% 5.7% 0.0% 0.0% 29.8% 27.8% 0.0% 0.0% 39.7% 39.9% 1.1% 0.9%
(76) (109) (7) (8) (24) (26) (0) (0) (108) (126) (0) (0) (144) (181) (4) (4)
Fresno 40.6% 39.4% 39.8% 40.6% 3.6% 3.9% 0.0% 0.05 13.7% 13.6% 0.4% 0.45 1.8% 2.1% 0.0% 0.0%
(201) (276) (197) (284) (18) (27) (0) (0) (68) (95) (2) (3) (9) (15) (0) (0)
Kern 56.0% 34.4% 22.1% 19.4% 1.6% 0.8% 0.2% 0.1% 13.1% 8.7% 1.4% 0.9% 3.9% 34.3% 1.7% 1.6%
(358) (320) (141) (181) (10) (7) (1) (1) (84) (81) (9) (8) (25) (320) (11) (15)
Los Angeles 24.6% 23.4% 36.0% 38.6% 5.2% 5.2% 0.2% 0.2% 31.3% 30.0% 1.0% 0.9% 0.2% 0.2% 1.5% 1.5%
(1,950) (2,275) (2,859) (3,743) (415) (509) (17) (21) (2,481) (2,915) (80) (86) (15) (18) (120) (141)
Marin
Merced 31.8% 41.3% 44.2% 34.8% 3.1% 3.2% 0.0% 0.0% 11.6% 8.4% 0.8% 0.6% 7.8% 8.4% 0.8% 3.2%
(41) (64) (57) (54) (4) (5) (0) (0) (15) (13) (1) (1) (10) (13) (1) (5)
Monterey
Orange 45.8% 45.3% 25.3% 26.9% 9.1% 9.1% 0.4% 0.4% 6.2% 5.9% 0.6% 0.5% 10.7% 10.3% 1.9% 1.7%
(739) (756) (408) (449) (146) (152) (6) (6) (100) (98) (10) (9) (172) (172) (31) (28)
Placer 71.7% 73.4% 11.5% 8.3% 0.9% 0.9% 0.0% 0.0% 4.4% 3.7% 2.7% 0.9% 8.0% 11.0% 0.9% 1.8%
(81) (80) (13) (9) (1) (1) (0) (0) (5) (4) (3) (1) (9) (12) (1) (2)
Riverside
Sacramento 34.5% 45.7% 6.1% 7.5% 27.9% 16.4% 0.1% 0.1% 14.7% 17.7% 1.2% 0.4% 13.2% 10.2% 2.2% 2.0%
(230) (659) (41) (108) (186) (237) (1) (2) (98) (255) (8) (6) (88) (147) (15) (29)
San 40.3% 39.2% 23.7% 23.4% 0.9% 0.8% 0.1% 0.2% 19.4% 18.6% 0.8% 0.5% 13.3% 15.6% 1.4% 1.7%
Bernardino (728) (1,034) (429) (617) (17) (21) (1) (4) (351) (490) (15) (14) (241) (411) (25) (46)
San Diego 45.9% 44.6% 19.2% 23.3% 3.7% 3.4% 0.2% 0.2% 17.7% 13.9% 0.7% 0.6% 11.7% 13.1% 0.9% 0.9%
(630) (1,228) (263) (641) (51) (94) (3) (5) (243) (383) (9) (17) (160) (360) (13) (25)
San Francisco 28.8% 26.9% 14.0% 15.9% 4.6% 5.3% 0.7% 0.7% 39.3% 39.0% 0.2% 0.3% 10.3% 10.0% 2.0% 1.8%
(156) (162) (76) (96) (25) (32) (4) (4) (213) (235) (1) (2) (56) (60) (11) (11)
San Joaquin 17.1% 26.2% 26.5% 20.0% 18.4% 16.3% 0.0% 0.1% 21.5% 20.6% 2.1% 3.6% 1.0% 11.9% 1.5% 1.2%
(124) (357) (193) (273) (134) (222) (0) (2) (156) (281) (15) (49) (7) (162) (11) (17)
San Luis 77.0% 73.3% 2.7% 3.5% 0.0% 0.0% 0.0% 0.0% 3.5% 3.0% 0.0% 0.0% 15.9% 18.8% 0.9% 1.5%
Obispo (87) (148) (3) (7) (0) (0) (0) (0) (4) (6) (0) (0) (18) (38 (1) (3)
San Mateo 42.1% 37.3% 23.4% 22.9% 8.4% 9.3% 0.0% 0.0% 14.0% 16.1% 0.0% 1.7% 9.3% 8.5% 2.8% 4.2%
(45) (44) (25) (27) (9) (11) (0) (0) (15) (19) (0) (2) (10) (10) (3) (5)
Santa Barbara
Black shading indicates where data was unavailable to calculate an indicator.
37
County Hispanic / Pacific American
White Asian Black Multirace Other
Latino Islander Indian
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
- - - - - - - - - - - - - - - -
8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
Santa Clara 38.5% 36.8% 29.6% 29.3% 7.5% 9.9% 0.3% 0.3% 10.9% 10.9% 2.3% 1.6% 8.0% 8.5% 2.9% 2.7%
(134) (138) (103) (110) (26) (37) (1) (1) (38) (41) (8) (6) (28) (32) (10) (10)
Santa Cruz 67.7% 67.3% 24.8% 23.5% 0.0% 0.0% 0.0% 0.0% 3.0% 4.1% 2.3% 2.0% 1.5% 3.1% 0.8% 0.0%
(90) (66) (33) (23) (0) (0) (0) (0) (4) (4) (3) (2) (2) (3) (1) (0)
Solano 44.4% 44.0% 7.8% 7.1% 2.6% 6.0% 0.0% 0.0% 28.7% 25.5% 2.65 1.1% 5.2% 15.2% 1.7% 1.1%
(59) (81) (9) (13) (3) (11) (0) (0) (33) (47) (3) (2) (6) (28) (2) (2)
Sonoma 63.2% 66.3% 6.0% 5.6% 1.9% 1.3% 0.0% 0.2% 2.2% 2.7% 0.6% 0.9% 25.7% 22.5% 0.3% 0.4%
(199) (295) (19) (25) (6) (6) (0) (1) (7) (12) (2) (4) (81) (100) (1) (2)
Stanislaus 54.1% 51.7% 20.8% 21.9% 4.6% 5.5% 0.0% 0.0% 9.6% 8.2% 0.8% 1.4% 8.3% 10.0% 1.9% 1.4%
(260) (227) (100) (96) (22) (24) (0) (0) (46) (36) (4) (6) (40) (44) (9) (6)
Tulare 42.9% 34.9% 36.5% 42.6% 0.0% 0.8% 0.0% 0.0% 8.4% 8.1% 0.5% 0.4% 10.8% 12.4% 1.0% 0.8%
(87) (90) (74) (110) (0) (2) (0) (0) (17) (21) (1) (1) (22) (32) (2) (2)
Ventura 58.3% 55.4% 27.0% 26.6% 2.6% 2.2% 0.0% 0.0% 6.7% 6.2% 0.3% 0.6% 10.6% 7.5% 0.3% 1.4%
(179) (740) (83) (355) (8) (30) (0) (0) (22) (83) (1) (8) (35) (100) (1) (19)
Yolo 66.7% 65.2% 3.1% 2.1% 3.1% 1.4% 0.0% 0.0% 5.7% 5.7% 0.6% 0.0% 19.5% 24.1% 1.3% 1.4%
(106) (92) (5) (3) (5) (2) (0) (0) (9) (8) (1) (0) (31) (34) (2) (2)
Small Counties 64.7% 58.3% 18.1% 24.7% 1.0% 0.8% 0.1% 0.0% 3.5% 3.8% 2.2% 2.0% 9.9% 9.4% 0.4% 0.9%
(1,026) (1,360) (287) (575) (16) (19) (2) (1) (56) (89) (35) (47) (157) (218) (7) (22)
Total 37.7% 37.5% 26.4% 26.9% 5.6% 5.2% 0.2% 0.2% 20.7% 18.8% 1.1% 1.0% 6.9% 9.0% 1.4% 1.4%
(7,477) (10,487) (5,229) (7,530) (1,108) (1,448) (36) (48) (4,110) (5,251) (213) (277) (1,369) (2,511) (283) (399)
Black shading indicates where data was unavailable to calculate an indicator.
38
Table 5-4 - Race/ethnicity of FSP consumers by county – Unknown and Missing Data
Unknown/Other
County
FY 08-09 FY 09-10
Alameda
Butte 12.4% (17) 6.7% (15)
Contra Costa 0.0% (0) 0.2% (1)
Fresno 18.0% (113) 17.7% (156)
Kern 2.6% (17) 3.0% (20)
Los Angeles 0.0% (2) 0.0% (4)
Marin
Merced 0.8% (1) 0.6% (1)
Monterey
Orange 2.7% (46) 6.3% (115)
Placer 0.0% (0) 0.0% (0)
Riverside
Sacramento 0.7% (5) 6.0% (93)
San Bernardino 0.5% (9) 0.3% (9)
San Diego 7.5% (113) 3.1% (84)
San Francisco 0.3% (2) 0.4% (3)
San Joaquin 0.0% (0) 0.1% (1)
San Luis Obispo 0.0% (0) 0.0% (0)
San Mateo 6.0% (7) 9.6% (13)
Santa Barbara
Santa Clara 30.0% (171) 41.5% (298)
Santa Cruz 4.8% (7) 2.9% (3)
Solano 6.0% (8) 5.6% (11)
Sonoma 1.5% (5) 1.1% (5)
Stanislaus 0.0% (0) 0.2% (1)
Tulare 0.0% (0) 1.1% (3)
Ventura 16.5% (66) 3.5% (50)
Yolo 0.6% (1) 0.0% (0)
Small Counties 4.1% (70) 3.6% (88)
Total 3.1% (660) 3.3% (979)
Black shading indicates where data was unavailable to calculate an indicator.
39
Table 5-5 - Mental health consumers by age group and county
Children TAY Adults Older Adults
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
Alameda 24.8% (8,349) 26.1% (9,078) 18.0% (6,067) 18.3% (6,378) 50.9% (17,127) 49.4% (17,189) 6.3% (2,106) 6.2% (2,163)
Butte 27.7% (1,727) 29.3% (1,470) 16.8% (1,048) 16.3% (819) 49.3% (3,069) 47.6% (2,389) 6.2% (385) 6.8% (342)
Contra Costa 23.9% (3,910) 24.6% (4,413) 19.5% (3,178) 19.6% (3,512) 50.3% (8,217) 49.3% (8,858) 6.3% (1,026) 6.5% (1,169)
Fresno 27.6% (4,771) 29.0% (4,755) 19.2% (3,323) 18.9% (3,098) 48.5% (8,393) 47.3% (7,756) 4.6% (802) 4.8% (789)
Kern 31.3% (5,513) 33.3% (5,644) 19.8% (3,489) 21.7% (3,676) 44.7% (7,866) 41.2% (6,998) 4.2% (744) 3.8% (650)
Los Angeles 31.0% (59,344) 32.4% (61,802) 18.6% (35,657) 18.8% (35,732) 44.5% (85,129) 42.9% (81,696) 5.8% (11,167) 5.9% (11,265)
Marin 22.5% (748) 23.7% (741) 16.0% (532) 14.6% (458) 50.6% (1,683) 49.5% (1,550) 10.9% (362) 12.2% (382)
Merced 15.9% (820) 18.6% (827) 20.2% (1,040) 20.1% (894) 58.4% (3,004) 54.7% (2,432) 5.4% (278) 6.6% (293)
Monterey 33.9% (2,097) 32.2% (1,729) 20.4% (1,261) 21.7% (1,169) 40.9% (2,532) 40.5% (2,176) 4.9% (303) 5.6% (302)
Orange 23.0% (10,271) 24.0% (10,726) 20.8% (9,263) 21.7% (9,706) 48.2% (21,538) 46.9% (20,943) 7.9% (3,539) 7.4% (3,292)
Placer 21.9% (797) 25.4% (702) 18.6% (677) 19.3% (535) 53.8% (1,962) 50.0% (1,383) 5.7% (208) 5.3% (147)
Riverside 18.6% (7,966) 19.3% (7,966) 24.1% (10,112) 23.5% (9,684) 52.4% (21,989) 51.8% (21,361) 4.8% (2,015) 5.4% (2,214)
Sacramento 28.9% (8,969) 17.8% (5,548) 47.6% (14,808) 5.7% (1,761)
San Bernardino 27.8% (11,020) 28.1% (10,765) 21.4% (8,476) 22.3% (8,547) 46.9% (18,576) 45.4% (17,405) 4.0% (1,575) 4.2% (1,592)
San Diego 25.3% (12,995) 26.5% (13,317) 17.3% (8,873) 17.8% (8,961) 50.2% (25,807) 48.4% (24,340) 7.3% (3,728) 7.3% (3,692)
San Francisco 15.5% (3,621) 14.6% (3,566) 12.3% (2,866) 12.5% (3,043) 58.6% (13,666) 59.0% (14,355) 13.6% (3,174) 13.9% (3,380
San Joaquin 19.5% (2,624) 18.3% (2,428) 18.9% (2,546) 19.4% (2,568) 53.6% (7,216) 54.1% (7,176) 8.1% (1,085) 8.2% (1,091)
San Luis Obispo 27.5% (1,224) 28.1% (1,278) 19.3% (858) 19.2% (871) 47.2% (2,095) 47.0% (2,134) 6.0% (266) 5.7% (261)
San Mateo 20.5% (2,330) 21.7% (2,554) 18.4% (2,094) 18.5% (2,183) 49.6% (5,633) 48.4% (5,693) 11.5% (1,301) 11.4% (1,342)
Santa Barbara 28.4% (2,148) 28.0% (2,133) 18.7% (1,411) 18.5% (1,410) 46.5% (3,515) 46.6% (3,553) 6.3% (479) 6.9% (527)
Santa Clara 10.8% (1,001) 8.8% (665) 12.1% (1,125) 11.8% (894) 62.6% (5,806) 63.8% (4,824) 14.5% (1,346) 15.6% (1,177)
Santa Cruz 31.1% (1,332) 31.9% (1,304) 22.7% (970) 21.7% (889) 42.5% (1,821) 42.2% (1,727) 3.7% (159) 4.2% (173)
Solano 28.2% (1,465) 30.3% (1,407) 17.8% (928) 16.6% (772) 48.0% (2,498) 46.9% (2,179) 6.0% (312) 6.3% (292)
Sonoma 24.1% (1,024) 25.6% (1,144) 20.1% (854) 20.3% (906) 47.6% (2,021) 45.8% (2,048) 8.1% (345) 8.3% (370)
Stanislaus 40.9% (3,814) 43.1% (3,907) 18.2% (1,695) 19.2% (1,740) 36.8% (3,436) 34.0% (3,089) 4.1% (381) 3.7% (339)
Tulare 45.8% (4,099) 46.8% (4,213) 17.4% (1,556) 18.1% (1,634) 33.4% (2,989) 31.4% (2,831) 3.5% (314) 3.6% (327)
Ventura 28.4% (3,113) 30.6% (3,133) 20.6% (2,257) 21.0% (2,154) 44.6% (4,890) 42.4% (4,339) 6.5% (714) 6.0% (616)
Yolo 17.6% (514) 17.4% (568) 16.8% (491) 19.0% (620) 56.7% (1,660) 55.1% (1,799) 9.0% (262) 8.5% (277)
Small Counties 27.2% (13,368) 27.6% (12,989) 17.3% (8,527) 18.0% (8,465) 48.9% (24,058) 47.6% (22,401) 6.5% (3,219) 6.8% (3,186)
Total 26.8% (180,829) 27.7% (175,224) 18.8% (126,752) 19.2% (121,309) 47.9% (323,004) 46.6% (294,624) 6.4% (43,356) 6.6% (41,650)
Black shading indicates where data was unavailable to calculate an indicator.
40
Table 5-6 - FSP consumers by age group and county
County Children TAY Adults Older Adults
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
Alameda
Butte 8.0% (11) 2.2% (5) 32.1% (44) 20.1% (45) 57.7% (79) 63.8% (143) 2.2% (3) 13.8% (31)
Contra Costa 29.6% (112) 28.4% (133) 25.9% (98) 28.6% (134) 42.3% (160) 40.1% (188) 2.1% (8) 3.0% (14)
Fresno 21.0% (132) 29.3% (259) 24.8% (156) 27.6% (244) 52.6% (331) 41.8% (369) 1.6% (10) 1.2% (11)
Kern 8.0% (53) 8.1% (53) 27.5% (182) 31.7% (208) 52.5% (347) 48.4% (318) 12.0% (79) 11.9% (78)
Los Angeles 27.7% (2,223) 32.3% (3,166) 15.7% (1,257) 17.3% (1,702) 52.0% (4,176) 46.3% (4,541) 4.6% (373) 4.1% (406)
Marin
Merced 44.6% (58) 45.5% (71) 26.2% (34) 28.8% (45) 28.5% (37) 25.0% (39) 0.8% (1) 0.6% (1)
Monterey
Orange 17.1% (291) 15.2% (278) 35.3% (599) 37.2% (680) 40.1% (681) 39.7% (725) 7.5% (127) 7.8% (143)
Placer 13.2% (20) 9.0% (13) 21.9% (33) 20.7% (30) 49.7% (75) 53.1% (77) 15.2% (23) 17.2% (25)
Riverside
Sacramento 17.3% (117) 8.0% (124) 10.1% (68) 8.4% (130) 51.5% (75) 69.5% (1,073) 21.2% (143) 14.1% (217)
San Bernardino 23.9% (449) 24.7% (673) 36.4% (685) 37.3% (1,018) 37.9% (712) 36.2% (988) 1.8% (34) 1.9% (51)
San Diego 18.8% (284) 26.5% (770) 27.0% (408) 22.8% (662) 43.6% (658) 42.9% (1,248) 10.5% (159) 7.8% (226)
San Francisco 24.4% (155) 26.8% (196) 22.9% (145) 25.1% (184) 42.1% (267) 38.8% (284) 10.6% (67) 9.3% (68)
San Joaquin 3.8% (28) 4.3% (59) 16.6% (122) 16.3% (224) 66.1% (485) 68.2% (937) 13.5% (99) 11.1% (153)
San Luis Obispo 19.3% (23) 35.2% (75) 25.2% (30) 27.7% (59) 48.7% (58) 30.0% (64) 6.7% (8) 7.0% (15
San Mateo 31.9% (37) 31.9% (43) 68.1% (79) 68.1% (92) 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
Santa Barbara
Santa Clara 11.8% (67) 12.4% (89) 23.3% (133) 25.1% (180) 60.0% (342) 58.5% (420) 4.9% (28) 4.0% (29)
Santa Cruz 0.0% (0) 0.0% (0) 43.4% (63) 35.3% (36) 28.3% (41) 35.3% (36) 28.3% (41) 29.4% (30)
Solano 27.1% (36) 23.0% (45) 18.8% (25) 18.4% (36) 28.6% (38) 41.8% (82) 25.6% (34) 16.8% (33)
Sonoma 25.7% (84) 25.2% (116) 17.7% (58) 18.4% (85) 54.7% (179) 44.3% (204) 1.8% (6) 12.1% (56
Stanislaus 6.6% (32) 6.8% (30) 21.7% (105) 24.0% (106) 62.1% (300) 59.5% (263) 9.5% (46) 9.75 (43)
Tulare 4.4% (9) 3.8% (10) 31.9% (65) 38.2% (100) 61.3% (125) 55.3% (145) 2.5% (5) 2.7% (7)
Ventura 20.0% (80) 2.7% (38) 26.9% (108) 29.6% (418) 17.0% (68) 54.2% (766) 36.2% (145) 13.5% (190)
Yolo 1.2% (2) 1.4% (2) 19.8% (33) 19.0% (28) 70.7% (118) 70.7% (104) 8.4% (14) 8.8% (13)
Small Counties 22.9% (386) 22.8% (564) 23.4% (395) 23.1% (571) 45.7% (771) 45.6% (1,127) 8.1% (136) 8.4% (207)
Total 21.7% (4,689) 22.7% (6,812) 22.8% (4,925) 23.4% (7,017) 48.1% (10,396) 47.1% (14,141) 7.4% (1,589) 6.8% (2,047)
Black shading indicates where data was unavailable to calculate an indicator.
41
Table 5-7 - Mental health consumers by gender and county
Female Male
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10
Alameda 48.5% (16,265) 48.8% (16,913) 51.5% (17,256) 51.2% (17,762)
Butte 53.3% (3,316) 52.4% (2,629) 46.7% (2,900) 47.6% (2,385)
Contra Costa 52.9% (8,647) 52.4% (9,411) 47.1% (7,684) 47.6% (8,541)
Fresno 47.4% (8,183) 47.3% (7,737) 52.6% (9,069) 52.7% (8,619)
Kern 47.8% (8,438) 45.2% (7,681) 52.2% (9,201) 54.8% (9,302)
Los Angeles 46.2% (88,361) 46.7% (88,924) 53.8% (102,884) 53.3% (101,521)
Marin 51.1% (1,699) 51.1% (1,597) 48.9% (1,625) 48.9% (1,531)
Merced 51.2% (2,647) 55.7% (2,492) 48.8% (2,519) 44.3% (1,981)
Monterey 50.7% (3,139) 49.1% (2,635) 49.3% (3,054) 50.9% (2,728)
Orange 47.3% (20,791) 47.1% (20,935) 52.7% (23,154) 52.9% (23,519)
Placer 51.2% (1,860) 49.7% (1,372) 48.8% (1,772) 50.3% (1,388)
Riverside 43.9% (18,374) 45.0% (18,516) 56.1% (23,463) 55.0% (22,620)
Sacramento 49.8% (15,464) 47.7% (31,357) 50.2% (15,616) 52.3% (34,418)
San Bernardino 47.5% (18,793) 47.3% (18,082) 52.5% (20,802) 52.7% (20,182)
San Diego 50.2% (25,785) 49.7% (25,051) 49.8% (25,548) 50.3% (25,309)
San Francisco 45.1% (10,494) 44.8% (10,869) 54.9% (12,776) 55.2% (13,414)
San Joaquin 52.5% (7,067) 52.1% (6,913) 47.5% (6,404) 47.9% (6,350)
San Luis Obispo 51.5% (2,288) 51.2% (2,325) 48.5% (2,155) 48.8% (2,219)
San Mateo 54.5% (6,190) 53.2% (6,262) 45.5% (5,166) 46.8% (5,510)
Santa Barbara 48.8% (3,624) 48.6% (3,621) 51.2% (3,803) 51.4% (3,828)
Santa Clara 49.3% (4,573) 48.3% (3,651) 50.7% (4,705) 51.7% (3,908)
Santa Cruz 41.4% (1,771) 40.8% (1,668) 58.6% (2,511) 59.2% (2,424)
Solano 47.7% (2,478) 47.6% (2,214) 52.3% (2,722) 52.4% (2,434)
Sonoma 46.9% (1,984) 45.4% (2,025) 53.1% (2,243) 54.6% (2,431)
Stanislaus 49.6% (4,624) 49.0% (4,440) 50.4% (4,700) 51.0% (4,628)
Tulare 48.5% (4,344) 47.9% (4,312) 51.5% (4,614) 52.1% (4,693)
Ventura 46.7% (5,124) 46.9% (4,784) 53.3% (5,848) 52.8% (5,408)
Yolo 54.9% (1,608) 53.9% (1,760) 45.1% (1,319) 46.1% (1,504)
Small Counties 52.7% (25,880) 51.9% (24,358) 47.3% (23,195) 48.1% (22,604)
Total 48.1% (323,811) 47.9% (334,534) 51.9% (348,708) 52.1% (363,161)
Black shading indicates where data was unavailable to calculate an indicator.
42
Table 5-8 - Gender of new mental health consumers by county – Unknown and Missing Data
Unknown/Missing
County
FY 08-09 FY 09-10
Alameda 0.4% (128) 0.4% (133)
Butte 0.2% (13) 0.1% (6)
Contra Costa 0.0% (1) 0.0% (1)
Fresno 0.2% (37) 0.3% (42)
Kern 0.0% (8) 0.0% (7)
L os Angeles 0.0% (52) 0.0% (50)
Marin 0.0% (1) 0.1% (3)
Merced 0.0% (0) 0.0% (0)
Monterey 0.0% (1) 0.3% (14)
Orange 1.6% (697) 0.5% (213)
Placer 0.3% (12) 0.3% (7)
Riverside 0.2% (100) 0.2% (89)
Sacramento 0.0% (6) 0.0% (16)
San Bernardino 0.1% (52) 0.1% (46)
San Diego 0.3% (133) 0.1% (59)
San Francisco 0.2% (58) 0.3% (63)
San Joaquin 0.0% (0) 0.0% (0)
San Luis Obispo 0.0% (0) 0.0% (0)
San Mateo 0.0% (2) 0.0% (0)
Santa Barbara 1.7% (126) 2.3% (174)
Santa Clara 0.0% (0) 0.0% (1)
Santa Cruz 0.0% (0) 0.0% (1)
Solano 0.1% (3) 0.0% (1)
Sonoma 0.4% (17) 0.3% (12)
Stanislaus 0.0% (2) 0.1% (8)
Tulare 0.0% (0) 0.0% (0)
Ventura 0.0% (2) 0.4% (41)
Yolo 0.0% (0) 0.0% (0)
Small Counties 0.2% (104) 0.2% (92)
Total 0.2% (1,555) 0.2% (1,079)
Black shading indicates where data was unavailable to calculate an indicator.
43
Table 5-9 - Consumers by gender and county (FSP)
County Female Male
FY 08-09 FY 09-10 FY 08-09 FY 09-10
Alameda
Butte 50.0% (60) 46.4% (97) 50.0% (60) 53.6% (112)
Contra Costa 46.8% (177) 47.2% (221) 53.2% (201) 52.8% (247)
Fresno 40.9% (211) 41.1% (299) 59.1% (305) 58.9% (428)
Kern 54.5% (351) 51.0% (325) 45.5% (293) 49.0% (312)
Los Angeles 42.5% (3,413) 43.2% (4,234) 57.5% (4,614) 56.8% (5,577)
Marin
Merced 45.7% (59) 44.5% (69) 54.3% (70) 55.5% (86)
Monterey
Orange 41.5% (686) 41.7% (713) 58.5% (966) 58.3% (998)
Placer 38.4% (58) 41.4% (60) 61.6% (93) 85 (58.6%)
Riverside
Sacramento 56.6% (380) 51.3% (745) 43.4% (291) 48.7% (706)
San Bernardino 43.9% (822) 45.8% (1,245) 56.1% (1,049) 54.2% (1,476)
San Diego 42.3% (590) 41.6% (1,172) 57.7% (806) 58.4% (1,645)
San Francisco 29.3% (185) 32.0% (233) 70.7% (447) 68.05 (496)
San Joaquin 60.5% (444) 53.9% (740) 39.5% (290) 46.1% (632)
San Luis Obispo 44.5% (53) 44.6% (95) 55.5% (66) 55.4% (118)
San Mateo 36.7% (40) 32.8% (40) 63.3% (69) 67.2% (82)
Santa Barbara
Santa Clara 41.1% (164) 38.3% (161) 58.9% (235) 61.7% (259)
Santa Cruz 43.5% (60) 42.4% (42) 56.5% (78) 57.6% (57)
Solano 43.2% (54) 44.9% (83) 56.8% (71) 55.1% (102)
Sonoma 37.6% (121) 40.1% (183) 62.4% (201) 59.9% (273)
Stanislaus 52.6% (254) 51.7% (228) 47.4% (229) 48.3% (213)
Tulare 48.0% (98) 46.7% (121) 52.0% (106) 53.3% (138)
Ventura 47.5% (159) 41.9% (571) 52.5% (176) 58.1% (791)
Yolo 54.2% (90) 54.4% (80) 45.8% (76) 45.6% (67)
Small Counties 45.7% (740) 45.5% (1,083) 54.3% (878) 54.5% (1,298)
Total 44.3% (9,269) 44.2% (12,840) 55.7% (11,670) 55.8% (16,198)
Black shading indicates where data was unavailable to calculate an indicator.
44
Table 5-10 – Consumers by Gender and County – Unknown and Missing Data
Unknown/Missing
County
FY 08-09 FY 09-10
Alameda
Butte 16.1% (22) 11.6% (26)
Contra Costa 4.0% (15) 3.2% (15)
Fresno 21.3% (134) 20.7% (183)
Kern 3.3% (22) 3.2% (21)
Los Angeles 1.1% (92) 1.1% (107)
Marin
Merced 0.8% (1) 0.6% (1)
Monterey
Orange 4.9% (84) 8.5% (156)
Placer 25.2% (38) 24.8% (36)
Riverside
Sacramento 1.3% (9) 6.5% (101)
San Bernardino 3.9% (73) 3.4% (93)
San Diego 9.1% (137) 5.3% (153)
San Francisco 14.5% (92) 17.8% (130)
San Joaquin 1.0% (7) 0.5% (7)
San Luis Obispo 5.0% (6) 5.2% (11)
San Mateo 7.8% (9) 12.6% (17)
Santa Barbara
Santa Clara 38.9% (222) 47.8% (343)
Santa Cruz 6.2% (9) 3.9% (4)
Solano 6.0% (8) 6.1% (12)
Sonoma 3.7% (12) 3.5% (16)
Stanislaus 0.4% (2) 0.7% (3)
Tulare 0.5% (1) 1.5% (4)
Ventura 18.0% (72) 5.5% (77)
Yolo 4.8% (8) 4.1% (6)
Small Counties 6.0% (102) 5.6% (138)
Total 7.1% (1,403) 5.3% (1,477)
Black shading indicates where data was unavailable to calculate an indicator.
45
Priority Indicator 6: Demographic Profile of New Consumers
Table 6-1 - New and continuing mental health consumers by county (CSI)
New Consumers Continuing Consumers
FY 08-09 FY 09-10 FY 08-09 FY 09-10
County
Alameda 34.2% (19,528) 27.9% (19,510) 65.8% (37,504) 72.1% (50,377)
Butte 30.7% (3,713) 15.5% (2,094) 69.3% (8,372) 84.5% (11,401)
Contra Costa 37.1% (10,720) 28.7% (10,335) 62.9% (18,194) 71.3% (25,697)
Fresno 28.3% (10,380) 19.4% (8,232) 71.7% (26,357) 80.6% (34,270)
Kern 37.5% (10,920) 31.0% (11,193) 62.5% (18,170) 69.0% (24,935)
Los Angeles 32.3% (111,920) 24.0% (97,981) 67.7% (234,145) 76.0% (310,839)
Marin 28.3% (1,616) 25.0% (1,691) 71.7% (4,090) 75.0% (5,063)
Merced 35.4% (3,627) 24.4% (2,928) 64.6% (6,619) 75.6% (9,060)
Monterey 35.6% (3,695) 25.1% (3,134) 64.4% (6,670) 74.9% (9,344)
Orange 34.3% (28,720) 26.1% (26,612) 65.7% (55,006) 73.9% (75,524)
Placer 30.2% (1,986) 19.7% (1,483) 69.8% (4,601) 80.3% (6,054)
Riverside 43.3% (32,411) 29.1% (26,979 56.7% (42,526) 70.9% (65,862)
Sacramento 17.8% (9,983) 82.2% (45,978)
San Bernardino 38.0% (25,608) 28.3% (23,293) 62.0% (41,744) 71.7% (59,067)
San Diego 36.0% (30,874) 26.6% (27,394) 64.0% (54,929) 73.4% (75,514)
San Francisco 27.6% (10,722) 21.6% (9,959) 72.4% (28,061) 78.4% (36,200)
San Joaquin 34.0% (7,976) 25.9% (7,294) 66.0% (15,496) 74.1% (20,898
San Luis Obispo 35.9% (2,892) 27.2% (2,658) 64.1% (5,163) 72.8% (7,113)
San Mateo 34.9% (6,736) 27.9% (6,556) 65.1% (12,551) 72.1% (16,934)
Santa Barbara 29.8% (4,120) 24.7% (4,077) 70.2% (9,696) 75.3% (12,419)
Santa Clara 6.0% (955) 3.9% (626) 94.0% (14,931) 96.1% (15,631)
Santa Cruz 33.2% (2,649) 25.1% (2,378) 66.8% (5,319) 74.9% (7,105)
Solano 34.6% (3,218) 21.8% (2,347) 65.4% (6,086) 78.2% (8,430)
Sonoma 32.0% (2,603) 26.2% (2,603) 68.0% (5,541) 73.8% (7,341)
Stanislaus 32.7% (6,373) 25.4% (5,909) 67.3% (13,112) 74.6% (17,310)
Tulare 33.4% (5,301) 24.8% (4,765) 66.6% (10,592) 75.2% (14,463)
Ventura 36.2% (6,752) 24.7% (5,452) 63.8% (11,879) 75.3% (16,653)
Yolo 30.8% (1,990) 23.7% (1,846) 69.2% (4,462) 76.3% (5,940)
Small Counties 33.2% (29,410) 24.5% (25,923) 66.8% (59,296) 75.5% (79,728)
Total 33.0% (397,398) 25.1% (345,252) 67.0% (807,090) 74.9% (1,029,172)
Black shading indicates where data was unavailable to calculate an indicator.
46
Table 6-2 - New and continuing mental health consumers by county (CSI) – Missing and Unknown Data
Unknown/Missing
FY 08-09 FY 09-10
County
Alameda 18.4% (12,855) 0.05 (0)
Butte 10.4% (1,410) 0.0% (0)
Contra Costa 19.8% (7,118) 0.0% (0)
Fresno 13.6% (5,765) 0.0% (0)
Kern 19.5% (7,038) 0.0% (0)
Los Angeles 15.4% (62,755) 0.0% (0)
Marin 15.5% (1,048) 0.0% (0)
Merced 14.5% (1,742) 0.0% (0)
Monterey 16.9% (2,113) 0.0% (0)
Orange 18.0% (18,410) 0.0% (0)
Placer 12.6% (950) 0.0% (0)
Riverside 19.3% (17,904) 0.0% (0)
Sacramento 14.9% (9,830)
San Bernardino 18.2% (15,008) 0.0% (0)
San Diego 16.6% (17,105) 0.0% (0)
San Francisco 16.0% (7,376) 0.0% (0)
San Joaquin 16.7% (4,720) 0.0% (0)
San Luis Obispo 17.6% (1,716) 0.0% (0)
San Mateo 17.9% (4,203) 0.0% (0)
Santa Barbara 16.2% (2,680) 0.0% (0)
Santa Clara 2.3% (371) 0.0% (0)
Santa Cruz 16.0% (1,515) 0.0% (0)
Solano 13.7% (1,473) 0.0% (0)
Sonoma 18.1% (1,800) 0.0% (0)
Stanislaus 16.1% (3,734) 0.0% (0)
Tulare 17.3% (3,335) 0.0% (0)
Ventura 15.7% (3,474) 0.0% (0)
Yolo 17.1% (1,334) 0.0% (0)
Small Counties 16.0% (16,945) 0.0% (0)
Total 19.6% (235,727) 0.0% (0)
Black shading indicates where data was unavailable to calculate an indicator.
47
Table 6-2 - Race/ethnicity of new mental health consumers by county
White Hispanic / Latino Asian Pacific Black American Multirace Other
Islander Indian
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9-
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
County
25.4% 25.6% 11.8% 12.4% 7.7% 8.1% 0.2% 0.3% 36.3% 34.1% 0.6% 0.4% 11.3% 11.2% 6.7% 8.0%
Alameda
(4,836) (4,836) (2,243) (2,362) (1,469) (1,537) (46) (48) (6,903) (6,482) (107) (82) (2,144) (2,122) (1,270) (1,523)
73.5% 71.2% 4.8% 3.5% 2.5% 4.9% 0.0% 0.1% 3.0% 2.7% 1.9% 2.1% 11.9% 12.2% 2.3% 3.3%
Butte
(2,598) (7,767) (168) (383) (88) (537) (1) (6) (106) (292) (67) (234) (422) (1,336) (83) (356)
Contra 38.3% 37.0% 2.0% 1.7% 5.8% 4.5% 0.3% 0.5% 24.8% 24.5% 0.2% 0.3% 26.4% 29.3% 2.1% 2.2%
Costa (3,972) (3,710) (210) (166) (598) (453) (33) (48) (2,570) (2,451) (23) (33) (2,738) (2,932) (219) (222)
31.7% 29.4% 47.7% 51.1% 4.2% 4.3% 0.0% 0.0% 12.7% 11.7% 1.1% 1.0% 2.1% 2.1% 0.5% 0.5%
Fresno
(3,148) (2,309) (4,744) (4,013) (422) (334) (3) (1) (1,259) (919) (108) (75) (206) (166) (51) (37)
41.9% 40.9% 39.5% 40.3% 0.9% 0.9% 0.1% 0.1% 11.7% 11.8% 0.8% 0.7% 2.9% 2.8% 2.2% 2.4%
Kern
(4,544) (4,550) (4,281) (4,481) (97) (104) (7) (7) (1,270) (1,313) (85) (81) (315) (313) (240) (272)
21.0% 20.4% 52.6% 55.1% 0.5% 0.5% 0.0% 0.0% 25.4% 23.4% 0.5% 0.5% 0.0% 0.0% 0.0% 0.05
Los Angeles
(19,522) (17,345) (48,901) (46,793) (444) (456) (23) (21) (23,609) (19,882) (460) (400) (6) (8) (4) (0)
61.3% 65.2% 17.1% 13.9% 2.0% 2.3% 0.2% 0.1% 8.6% 8.6% 0.4% 0.3% 9.2% 8.8% 1.2% 0.8%
Marin
(955) (3,195) (267) (680) (31) (111) (3) (6) (134) (419) (6) (14) (144) (431) (18) (41)
41.6% 43.1% 34.2% 30.5% 4.4% 3.7% 0.1% 0.1% 8.6% 8.6% 0.7% 0.4% 8.0% 10.5% 2.4% 3.2%
Merced
(1,212) (1,114) (997) (787) (129) (96) (3) (3) (249) (221) (20) (10) (232) (271) (69) (82)
25.6% 22.3% 23.3% 51.2% 2.0% 2.1% 0.6% 0.3% 5.4% 3.6% 0.4% 0.4% 7.2% 9.5% 35.5% 10.7%
Monterey
(862) (616) (786) (1,414) (66) (57) (21) (8) (183) (99) (12) (12) (241) (262) (1,196) (296)
42.1% 40.6% 37.5% 39.9% 6.5% 6.1% 0.3% 0.2% 4.8% 5.0% 0.4% 0.4% 4.4% 4.5% 4.0% 3.4%
Orange
(11,251) (10,102) (10,020) (9,930) (1,740) (1,511) (74) (53) (1,279) (1,238) (118) (96) (1,181) (1,112) (1,063) (844)
75.5% 75.5% 7.9% 8.1% 1.6% 1.2% 0.1% 0.1% 2.3% 3.0% 1.2% 1.0% 9.6% 9.9% 1.9% 1.3%
Placer
(1,182) (872) (123) (93) (25) (14) (1) (1) (36) (35) (18) (11) (151) (114) (29) (15)
36.9% 39.1% 29.6% 32.8% 1.3% 1.7% 0.1% 0.1% 12.4% 13.1% 0.6% 0.5% 16.3% 10.0% 2.7% 2.8%
Riverside
(11,065) (115) (8,892) (8,020) (403) (405) (28) (24) (3,718) (3,218) (176) (115) (4,894) (2,452) (814) (675)
40.2% 22.8% 1.3% 0.4% 17.8% 0.6% 13.0% 3.8%
Sacramento
(9,773) (5,539) (318) (94) (4,340) (154) (3,169) (935)
San 40.2% 38.0% 22.8% 24.7% 1.3% 1.2% 0.4% 0.7% 17.8% 16.4% 0.6% 0.6% 13.0% 14.4% 3.8% 4.1%
Bernardino (9,773) (8,477) (5,539) (5,511) (318) (273) (94) (152) (4,340) (3,668) (154) (139) (3,169) (3,207) (935) (906)
42.9% 40.6% 29.7% 31.1% 3.8% 3.7% 0.2% 0.2% 12.0% 11.6% 0.7% 0.6% 9.1% 10.8% 1.6% 1.4%
San Diego
(12,534) (10,537) (8,676) (8,076) (1,115) (949) (45) (63) (3,511) (3,003) (192) (158) (2,669) (2,792) (479) (361)
San 32.8% 34.2% 17.0% 18.5% 12.4% 12.5% 0.6% 0.4% 24.2% 21.4% 0.8% 0.9% 6.6% 6.4% 5.6% 5.9%
Francisco (3,060) (2,729) (1,587) (1,478) (1,159) (995) (53) (31) (2,262) (1,712) (79) (69) (619) (509) (524) (468)
34.6% 33.1% 25.1% 26.2% 6.4% 6.2% 0.2% 0.2% 16.9% 18.0% 0.6% 0.6% 14.0% 13.3% 2.3% 2.3%
San Joaquin
(2,686) (2,346) (1,947) (1,858) (496) (438) (14) (15) (1,308) (1,278) (49) (46) (1,086) (939) (176) (161)
San Luis 70.0% 69.1% 17.8% 17.7% 1.4% 1.4% 0.0% 0.0% 1.8% 1.8% 0.4% 0.2% 7.3% 8.4% 1.3% 1.4%
Obispo (2,005) (1,813) (511) (464) (39) (38) (1) (0) (53) (47) (11) (5) (209) (220) (37) (37)
30.1% 29.2% 42.5% 45.7% 7.2% 7.6% 0.5% 0.4% 8.7% 7.1% 0.2% 0.3% 4.8% 4.4% 6.1% 5.3%
San Mateo
(1,792) (1,685) (2,533) (2,642) (427) (442) (28) (23) (519) (409) (10) (15) (285) (253) (366) (309)
Black shading indicates where data was unavailable to calculate an indicator.
48
White Hispanic / Latino Asian Pacific Black American Multirace Other
Islander Indian
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9-
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
County
Santa 21.9% 17.3% 68.1% 75.4% 0.2% 0.1% 0.0% 0.0% 1.7% 1.0% 0.2% 0.3% 7.8% 5.7% 0.0% 0.0%
Barbara (483) (365) (1,505) (1,588) (5) (3) (0) (0) (37) (22) (5) (7) (173) (120) (1) (0)
39.3% 39.8% 30.7% 32.7% 6.5% 7.6% 0.3% 0.2% 10.3% 9.2% 0.9% 0.8% 10.3% 8.7% 1.6% 1.0%
Santa Clara
(358) (237) (280) (195) (59) (45) (3) (1) (94) (55) (8) (5) (94) (52) (15) (6)
51.8% 51.3% 33.3% 32.6% 0.7% 0.9% 0.0% 0.0% 2.7% 2.7% 0.7% 0.6% 9.5% 10.6% 1.4% 1.3%
Santa Cruz
(1,342) (1,183) (862) (751) (17) (20) (1) (1) (69) (63) (17) (13) (246) (245) (36) (31)
40.5% 37.5% 15.2% 15.9% 4.5% 4.7% 0.2% 0.3% 26.0% 27.6% 0.8% 0.3% 11.1% 11.5% 1.8% 2.1%
Solano
(1,294) (872) (485) (370) (143) (109) (6) (7) (829) (643) (24) (7) (356) (268) (56) (50)
62.7% 64.4% 13.2% 13.0% 1.8% 1.8% 0.2% 0.2% 3.8% 3.3% 1.2% 0.8% 16.0% 15.5% 1.2% 1.0%
Sonoma
(1,587) (1,639) (335) (332) (45) (45) (6) (6) (95) (83) (30) (21) (404) (395) (30) (25)
37.2% 36.5% 24.3% 24.8% 4.8% 5.7% 0.1% 0.1% 4.0% 4.1% 0.7% 0.4% 24.6% 25.0% 4.3% 3.4%
Stanislaus
(2,338) (2,130) (1,528) (1,444) (301) (331) (6) (3) (249) (237) (43) (25) (1,542) (1,457) (271) (201)
31.8% 30.1% 52.8% 54.5% 1.2% 1.4% 0.0% 0.0% 3.0% 2.8% 0.6% 0.3% 9.7% 9.7% 0.9% 1.2%
Tulare
(1,679) (1,427) (2,791) (2,587) (64) (65) (1) (0) (157) (134) (31) (14) (513) (462) (50) (58)
48.0% 44.4% 32.3% 31.9% 1.4% 1.6% 0.0% 0.1% 3.0% 2.7% 0.4% 0.2% 13.3% 16.7% 1.4% 2.4%
Ventura
(3,101) (2,280) (2,087) (1,635) (93) (80) (3) (4) (195) (141) (23) (12) (860) (856) (92) (122)
61.9% 61.3% 8.6% 7.3% 2.2% 3.0% 0.0% 0.2% 5.5% 5.4% 0.5% 0.5% 19.3% 20.5% 2.1% 1.8%
Yolo
(1,156) (1,061) (160) (126) (41) (52) (0) (4) (102) (93) (9) (9) (361) (354) (40) (32)
Small 62.6% 61.7% 20.4% 20.4% 1.1% 1.0% 0.1% 0.1% 3.1% 2.8% 2.4% 2.7% 9.1% 10.0% 1.1% 1.2%
Counties (17,423) (15,061) (5,687) (4,988) (316) (256) (26) (24) (870) (680) (670) (664) (2,538) (2,434) (310) (285)
11.4% 8.0% 10.3% 8.2% 0.9% 0.7% 0.1% 0.0% 5.0% 3.6% 0.2% 0.2% 2.6% 1.9% 0.8% 0.5%
Total
(137,531) (110,373) (123,684) (113,167) (10,468) (9,756) (624) (560) (60,346) (48,837) (2,709) (2,372) (30,967) (26,082) (9,409) (7,415)
Black shading indicates where data was unavailable to calculate an indicator.
49
Table 6-3 - Race/ethnicity of new mental health consumers by county (CSI) – Unknown and Missing
Data
Unknown/Missing
FY 08-09 FY 09-10
County
Alameda 2.6% (510) 2.5% (493)
Butte 4.8% (180) 3.5% (490)
Contra Costa 3.3% (357) 3.1% (320)
Fresno 4.2% (439) 4.6% (378)
Kern 0.7% (81) 0.6% (72)
Los Angeles 16.9% (18,951) 13.3% (13,076)
Marin 3.6% (58) 3.3% (166)
Merced 19.7% (716) 11.7% (344)
Monterey 8.9% (328) 11.8% (370)
Orange 6.9% (1,994) 6.5% (1,726)
Placer 21.2% (421) 22.1% (328)
Riverside 7.5% (2,420) 9.3% (2,506)
Sacramento 5.0% (1,286)
San Bernardino 5.0% (1,286) 4.1% (960)
San Diego 5.4% (1,653) 5.3% (10,537)
San Francisco 12.9% (1,379) 19.8% (1,968)
San Joaquin 2.7% (214) 2.9% (213)
San Luis Obispo 0.9% (26) 1.3% (34)
San Mateo 11.5% (776) 11.9% (778)
Santa Barbara 46.4% (1,911) 48.4% (1,972)
Santa Clara 4.6% (44) 4.0% (25)
Santa Cruz 2.2% (59) 3.0% (71)
Solano 0.8% (25) 0.9% (21)
Sonoma 2.7% (71) 2.2% (57)
Stanislaus 1.5% (95) 1.4% (81)
Tulare 0.3% (15) 0.4% (18)
Ventura 4.4% (298) 5.9% (322)
Yolo 6.1% (121) 6.2% (115)
Small Counties 5.3% (1,570) 5.9% (1,531)
Total 9.4% (37,284) 11.3% (38,972)
Black shading indicates where data was unavailable to calculate an indicator.
50
Table 6-3 - New mental health consumers by age group and county (CSI)
Children TAY Adults Older Adults
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
Alameda 26.8% (5,237) 29.2% (5,696) 21.9% (4,275) 21.8% (4,246) 47.0% (9,175) 45.3% (8,833) 4.3% (841) 3.8% (735)
Butte 29.3% (1,089) 35.2% (737) 21.1% (784) 21.0% (439) 45.4% (1,685) 40.2% (842) 4.2% (155) 3.6% (76)
Contra Costa 24.6% (2,642) 28.0% (2,893) 23.4% (2,510) 23.4% (2,415) 46.6% (4,999) 44.0% (4,549) 5.3% (568) 4.6% (478)
Fresno 32.9% (3,413) 36.3% (2,985) 23.5% (2,443) 22.1% (1,817) 41.9% (4,346) 39.8% (3,274) 1.7% (176) 1.9% (156)
Kern 33.7% (3,668) 35.5% (3,963) 22.7% (2,474) 24.0% (2,682) 40.5% (4,406) 37.3% (4,161) 3.1% (34) 3.2% (361)
Los Angeles 35.2% (39,403) 39.7% (38,936) 20.9% (23,375) 20.4% (19,971) 39.6% (44,314) 35.7% (34,998) 4.3% (4,828) 4.2% (4,076)
Marin 26.4% (426) 28.0% (474) 19.2% (311) 18.2% (307) 45.2% (731) 43.5% (735) 9.2% (148) 10.3% (175)
Merced 18.0% (652) 21.7% (635) 24.5% (887) 25.1% (734) 53.3% (1,930) 48.7% (1,422) 4.3% (154) 4.5% (131)
Monterey 35.8% (1,322) 35.6% (1,117) 23.0% (851) 24.0% (752) 38.5% (1,422) 36.8% (1,152) 2.7% (100) 3.6% (113)
Orange 25.6% (7,352) 27.6% (7,355) 23.5% (6,742) 23.9% (6,360) 44.3% (12,732) 42.9% (11,408) 6.6% (1,893) 5.6% (1,489)
Placer 25.0% (497) 27.6% (409) 23.0% (457) 21.6% (320) 48.8% (969) 47.9% (711) 3.2% (63) 2.9% (43)
Riverside 18.3% (5,917) 21.0% (5,672) 27.4% (8,865) 26.6% (7,163) 50.9% (16,492) 48.6% (13,124) 3.5% (1,137) 3.8% (1,020)
Sacramento 34.3% (3,426) 21.2% (2,118) 39.7% (3,962) 4.8% (477)
San Bernardino 31.1% (7,965) 32.6% (7,595) 25.4% (6,500) 26.7% (6,210) 40.8% (10,444) 37.8% (8,811) 2.7% (699) 2.9% (676)
San Diego 29.6% (9132) 32.8% (8955) 21.0% (6475) 21.7% (5910) 43.4% (13363) 40.7% (11115) 6.0% (1847) 4.8% (1308)
San Francisco 19.1% (2,049) 17.6% (1,755) 18.7% (2,002) 18.0% (1,796) 54.6% (5,854) 56.8% (5,654) 7.6% (817) 7.6% (753)
San Joaquin 26.2% (2,091) 25.6% (1,866) 25.7% (2,048) 26.0% (1,895) 43.4% (3,458) 44.4% (3,237) 4.8% (379) 4.1% (296)
San Luis Obispo 26.1% (756) 26.9% (716) 22.1% (638) 22.4% (596) 44.9% (1,298) 45.0% (1,195) 6.9% (200) 5.7% (151)
San Mateo 25.4% (1,712) 29.1% (1,908) 22.0% (1,484) 22.3% (1,464) 44.8% (3,020) 41.4% (2,712) 7.7% (520) 7.2% (472)
Santa Barbara 36.6% (1,507) 37.6% (1,533) 21.6% (889) 21.1% (862) 37.8% (1,558) 36.7% (1,498) 4.0% (166) 4.5% (184)
Santa Clara 19.5% (186) 17.9% (112) 26.0% (248) 23.0% (144) 49.2% (470) 54.2% (339) 5.3% (51) 5.0% (31)
Santa Cruz 32.7% (865) 32.6% (776) 22.6% (598) 21.9% (521) 41.8% (1,106) 41.9% (997) 3.0% (80) 3.5% (84)
Solano 28.2% (909) 34.8% (816) 20.2% (650) 18.6% (437) 46.5% (1,497) 42.0% (986) 5.0% (162) 4.6% (108)
Sonoma 28.0% (729) 29.6% (771) 25.0% (650) 24.5% (637) 42.2% (1,098) 41.3% (1,075) 4.8% (126) 4.6% (120)
Stanislaus 45.6% (2,904) 46.9% (2,773) 19.8% (1,259) 21.1% (1,247) 32.4% (2,067) 30.3% (1,790) 2.2% (143) 1.7% (98)
Tulare 48.0% (2,549) 50.8% (2,419) 19.3% (1,024) 18.8% (897) 29.9% (1,587) 28.0% (1,332) 2.7% (144) 2.5% (117)
Ventura 33.9% (2,287) 38.0% (2,070) 23.0% (1,551) 24.0% (1,307) 37.8% (2,549) 33.4% (1,821) 5.4% (365) 4.7% (254)
Yolo 20.5% (408) 19.9% (368) 22.5% (448) 23.7% (437) 50.1% (997) 50.4% (930) 6.9% (137) 6.0% (111)
Small Counties 30.3% (8,912) 31.3% (8,120) 21.1% (6,194) 21.3% (5,515) 44.0% (12,939) 42.6% (11,026) 4.6% (1,359) 4.8% (1,252)
Total 30.2% (120,005) 32.9% (113,425) 22.4% (88,750) 22.3% (77,081) 42.9% (170,468) 40.5% (139,727) 4.5% (17,769) 4.3% (120,005)
Black shading indicates where data was unavailable to calculate an indicator.
51
Table 6-4 - New mental health consumers by age group and county (CSI)– Missing and Unknown Data
Unknown/Missing
FY 2008-09 FY 2009-10
County
Alameda 0.0% (0) 0.0% (0)
Butte 0.0% (0) 0.0% (0)
Contra Costa 0.0% (1) 0.0% (0)
Fresno 0.0% (2) 0.0% (0)
Kern 0.3% (32) 0.2% (26)
Los Angeles 0.0% (0) 0.0% (0)
Marin 0.0% (0) 0.0% (0)
Merced 0.1% (4) 0.2% (6)
Monterey 0.0% (0) 0.0% (0)
Orange 0.0% (1) 0.0% (0)
Placer 0.0% (0) 0.0% (0)
Riverside 0.0% (0) 0.0% (0)
Sacramento 0.0% (0)
San Bernardino 0.0% (0) 0.0% (1)
S an Diego 0.2% (57) 0.4% (106)
San Francisco 0.0% (0) 0.0% (1)
San Joaquin 0.0% (0) 0.0% (0)
San Luis Obispo 0.0% (0) 0.0% (0)
San Mateo 0.0% (0) 0.0% (0)
Santa Barbara 0.0% (0) 0.0% (0)
Santa Clara 0.0% (0) 0.0% (0)
Santa Cruz 0.0% (0) 0.0% (0)
Solano 0.0% (0) 0.0% (0)
Sonoma 0.0% (0) 0.0% (0)
Stanislaus 0.0% (0) 0.0% (1)
Tulare 0.0% (0) 0.0% (0)
Ventura 0.0% (0) 0.0% (0)
Yolo 0.0% (0) 0.0% (0)
Small Counties 0.0% (6) 0.0% (10)
Total 0.0% (103) 0.0% (151)
Black shading indicates where data was unavailable to calculate an indicator.
52
Table 6-5 - New mental health consumers by gender and county (CSI)
Female Male
County
FY 2008-09 FY 2009-10 FY 2008-09 FY 2009-10
Alameda 46.6% (4,814) 46.2% (3,787) 53.4% (5,525) 53.8% (4,402)
Butte 53.4% (1,974) 51.0% (1,061) 46.6% (1,726) 49.0% (1,021)
Contra Costa 51.6% (9,221) 51.4% (13,064) 48.4% (5,188) 48.6% (5,024)
Fresno 46.6% (4,814) 46.2% (3,787) 53.4% (5,525) 53.8% (4,402)
Kern 47.0% (5,126) 44.8% (5,013) 53.0% (5,787) 55.2% (6,171)
Los Angeles 43.5% (48,681) 45.9% (44,955) 56.5% (63,197) 54.1% (52,985)
Marin 52.4% (846) 51.7% (873) 47.6% (770) 48.3% (816)
Merced 49.8% (1,805) 52.9% (1,550) 50.2% (1,822) 47.1% (1,378)
Monterey 52.9% (1,954) 50.9% (1,588) 47.1% (1,741) 49.1% (1,533)
Orange 46.1% (13,049) 46.0% (12,219) 53.9% (15,270) 54.0% (14,346)
Placer 51.8% (1,022) 52.1% (767) 48.2% (950) 47.9% (706)
Riverside 39.8% (12,866) 41.1% (11,062) 60.2% (19,468) 58.9% (15,845)
Sacramento 49.5% (4,939) 50.5% (5,039)
San Bernardino 46.2% (11,827) 46.1% (10,732) 53.8% (13,749) 53.9% (12,543)
San Diego 48.6% (14,931) 48.4% (13,246) 51.4% (15,788) 51.6% (14,123)
San Francisco 44.1% (4,710) 43.5% (4,321) 55.9% (5,981) 56.5% (5,611)
San Joaquin 51.6% (4,113) 51.9% (3,788) 48.4% (3,863) 48.1% (3,506)
San Luis Obispo 51.9% (1,500) 52.2% (1,387) 48.1% (1,392) 47.8% (1,271)
San Mateo 56.4% (3,798) 54.5% (3,573) 43.6% (2,935) 45.5% (2,983)
Santa Barbara 48.0% (1,898) 47.0% (1,814) 52.0% (2,054) 53.0% (2,042)
Santa Clara 48.3% (461) 49.0% (306) 51.7% (494) 51.0% (319)
Santa Cruz 42.8% (1,134) 44.2% (1,050) 57.2% (1,515) 55.8% (1,327)
Solano 50.4% (1,621) 51.2% (1,200) 49.6% (1,596) 48.8% (1,146)
Sonoma 49.3% (1,276) 47.9% (1,239) 50.7% (1,310) 52.1% (1,350)
Stanislaus 50.7% (3,227) 50.9% (3,003) 49.3% (3,143) 49.1% (2,897)
Tulare 50.3% (2,668) 49.9% (2,380) 49.7% (2,633) 50.1% (2,385)
Ventura 46.4% (3,133) 47.4% (2,566) 53.6% (3,618) 52.6% (2,846)
Yolo 53.0% (1,055) 53.5% (988) 47.0% (935) 46.5% (858)
Small Counties 52.4% (15,358) 51.5% (13,304) 47.6% (13,945) 48.5% (12,549)
Total 47.0% (183,821) 48.3% (164,623) 53.0% (206,959) 51.7% (176,385)
Black shading indicates where data was unavailable to calculate an indicator.
53
Table 6-5 - New mental health consumers by gender and county (CSI) – Missing and Unknown Data
Unknown/Other
County
FY 2008-09 FY 2009-10
.A lameda 0.4% (41) 0.5% (43)
.Butte 0.4% (13) 0.6% (12)
.Contra Costa 0.0% (1) 0.1% (1)
.Fresno 0.4% (41) 0.5% (43)
.Kern 0.1% (7) 0.1% (9)
.Los Angeles 0.0% (0) 0.0% (0)
.Marin 0.0% (0) 0.1% (2)
.Merced 0.0% (0) 0.0% (0)
.Monterey 0.0% (0) 0.4% (13)
.Orange 1.4% (401) 0.2% (47)
.Placer 0.7% (14) 0.7% (10)
.Riverside 0.2% (77) 0.3% (72)
.Sacramento 0.1% (5)
.San Bernardino 0.1% (32) 0.1% (18)
.San Diego 0.5% (155) 0.1%(23)
.San Francisco 0.3% (31) 0.3% (27)
.San Joaquin 0.0% (0) 0.0% (0)
.San Luis Obispo 0.0% (0) 0.0% (0)
.San Mateo 0.0% (3) 0.0% (0)
.Santa Barbara 4.1% (168) 5.4% (220)
.Santa Clara 0.0% (0) 0.2% (1)
.Santa Cruz 0.0% (0) 0.0% (1)
.Solano 0.0% (1) 0.0% (1)
.Sonoma 0.7% (17) 0.5% (14)
.Stanislaus 0.0% (3) 0.2% (9)
.Tulare 0.0% (0) 0.0% (0)
.Ventura 0.0% (1) 0.7% (40)
.Yolo 0.0% (0) 0.0% (0)
Small Counties 0.4% (94) 0.3%(60)
Total 0.3% (1,105) 0.2% (666)
Black shading indicates where data was unavailable to calculate an indicator.
54
Table 6-6 - New and continuing consumers by county (FSP)
County New Consumers Continuing Consumers
FY 08-09 FY 09-10 FY 08-09 FY 09-10
.Alameda
.Butte 58.4% (80) 60.3% (135) 41.6% (57) 140.4% (89)
.Contra Costa 47.9% (181) 31.3% (147) 52.1% (197) 91.9% (322)
.Fresno 61.7% (388) 40.8% (360) 38.3% (241) 161.0% (523)
.Kern 35.7% (236) 37.9% (249) 64.3% (425) 55.5% (408)
.Los Angeles 40.2% (3,230) 29.0% (2,844) 59.8% (4,799) 67.3% (6,971)
.Marin 51.5% (67) 40.4% (63) 48.5% (63) 106.3% (93)
.Merced 58.4% (80) 60.3% (135) 41.6% (57) 140.4% (89)
.Monterey
.Orange 39.2% (666) 21.1% (386) 60.8% (1,032) 64.5% (1,440)
.Placer 39.7% (60) 29.7% (43) 60.3% (91) 65.9% (102)
.Riverside
.Sacramento 36.2% (245) 63.3% (977) 63.8% (431) 56.8% (567)
.San Bernardino 74.5% (1,400) 49.7% (1,356) 25.5% (480) 291.7% (1,374)
.San Diego 35.7% (539) 62.6% (1,820) 64.3% (970) 55.6% (1,086)
.San Francisco 58.8% (373) 35.1% (257) 41.2% (261) 142.9% (475)
.San Joaquin 76.3% (560) 56.8% (780) 23.7% (174) 321.8% (593)
.San Luis Obispo 43.7% (52) 66.7% (142) 56.3% (67) 77.6% (71)
.San Mateo 26.7% (31) 31.9% (43) 73.3% (85) 36.5% (92)
.Santa Barbara
.Santa Clara 47.4% (270) 41.2% (296) 52.6% (300) 90.0% (422)
.Santa Cruz 29.7% (43) 0.0% (0) 70.3% (102) 42.2% (102)
.Solano 45.9% (61) 54.1% (106) 54.1% (72) 84.7% (90)
.Sonoma 21.1% (69) 29.1% (134) 78.9% (258) 26.7% (327)
.Stanislaus 39.8% (192) 33.7% (149) 60.2% (291) 66.0% (293)
.Tulare 66.7% (136) 53.4% (140) 33.3% (68) 200.0% (122)
.Ventura 59.1% (237) 80.4% (1,135) 40.9% (164) 144.5% (277)
.Yolo 40.1% (67) 15.0% (22) 59.9% (100) 67.0% (125)
Small Counties 64.8% (1,094) 48.3% (1,193) 35.2% (594) 184.2% (1276)
Total 47.6% (10,277) 42.6% (12,777) 52.4% (11,322) 90.8% (17,240)
Black shading indicates where data was unavailable to calculate an indicator.
55
Table 6-7 - Race/ethnicity of new FSP consumers by county
White Hispanic / Latino Asian Pacific Islander Black American Indian Multirace Other
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
County 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 -
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
.Alameda
79.3% 81.8% 0.9% 3.5% 0.0% 0.0% 0.9% 0.0% 4.3% 2.0% 3.4% 3.0% 10.3% 8.1% 0.9% 1.5%
.Butte
(92) (162) (1) (7) (0) (0) (1) (0) (5) (4) (4) (6) (12) (16) (1) (3)
20.9% 24.0% 1.9% 1.8% 6.6% 5.7% 0.0% 0.0% 29.8% 27.8% 0.0% 0.0% 39.7% 39.9% 1.1% 0.9%
.Contra Costa
(76) (109) (7) (8) (24) (26) (0) (0) (108) (126) (0) (0) (144) (181) (4) (4)
40.6% 39.4% 39.8% 40.6% 3.6% 3.9% 0.0% 0.0% 13.7% 13.6% 0.4% 0.4% 1.8% 2.1% 0.0% 0.0%
.Fresno
(201) (276) (197) (284) (18) (27) (0) (0) (68) (95) (2) (3) (9) (15) (0) (0)
56.0% 50.3% 22.1% 28.5% 1.6% 1.1% 0.2% 0.2% 13.1% 12.7% 1.4% 1.3% 3.9% 3.6% 1.7% 2.4%
.Kern
(358) (320) (141) (181) (10) (7) (1) (1) (84) (81) (9) (8) (25) (23) (11) (15)
24.6% 23.4% 36.0% 38.6% 5.2% 5.2% 0.2% 0.2% 31.3% 30.0% 1.0% 0.9% 0.2% 0.2% 1.5% 1.5%
.Los Angeles
(1,950) (2,275) (2,859) (3,743) (415) (509) (17) (21) (2,481) (2,915) (80) (86) (15) (18) (120) (141)
.Marin
31.8% 41.3% 44.2% 34.8% 3.1% 3.2% 0.0% 0.0% 11.6% 8.4% 0.8% 0.6% 7.8% 8.4% 0.8% 3.2%
.Merced
(41) (64) (57) (54) (4) (5) (0) (0) (15) (13) (1) (1) (10) (13) (1) (5)
.Monterey
45.8% 45.3% 26.0% 26.9% 8.5% 9.1% 0.4% 0.4% 6.2% 5.9% 0.6% 0.5% 10.7% 10.3% 1.9% 1.7%
.Orange
(739) (756) (419) (449) (137) (152) (6) (6) (100) (98) (10) (9) (172) (172) (31) (28)
71.7% 73.4% 11.5% 8.3% 0.9% 0.9% 0.0% 0.0% 4.4% 3.7% 2.7% 0.9% 8.0% 11.0% 0.9% 1.8%
.Placer
(81) (80) (13) (9) (1) (1) (0) (0) (5) (4) (3) (1) (9) (12) (1) (2)
.Riverside
34.5% 45.7% 6.1% 7.5% 27.9% 16.4% 0.1% 0.1% 14.7% 17.7% 1.2% 0.4% 13.2% 10.2% 2.2% 2.0%
.Sacramento
(230) (659) (41) (108) (186) (237) (1) (2) (98) (255) (8) (6) (88) (147) (15) (29)
40.3% 39.2% 23.7% 23.4% 0.9% 0.8% 0.1% 0.2% 19.4% 18.6% 0.8% 0.5% 13.3% 15.6% 1.4% 1.7%
.San Bernardino
(728) (1034) (429) (617) (17) (21) (1) (4) (351) (490) (15) (14) (241) (411) (25) (46)
45.9% 44.6% 19.2% 23.3% 3.7% 3.4% 0.2% 0.2% 17.7% 13.9% 0.7% 0.6% 11.7% 13.1% 0.9% 0.9%
.San Diego
(630) (1228) (263) (641) (51) (94) (3) (5) (243) (383) (9) (17) (160) (360) (13) (25)
28.8% 26.8% 14.0% 16.0% 4.6% 5.2% 0.7% 0.7% 39.3% 39.2% 0.2% 0.3% 10.3% 10.0% 2.0% 1.8%
.San Francisco
(156) (161) (76) (96) (25) (31) (4) (4) (213) (235) (1) (2) (56) (60) (11) (11)
17.1% 26.1% 26.5% 20.0% 18.4% 16.3% 0.0% 0.1% 21.5% 20.6% 2.1% 3.6% 12.9% 12.1% 1.5% 1.2%
.San Joaquin
(124) (357) (193) (273) (134) (222) (0) (2) (156) (281) (15) (49) (94) (165) (11) (17)
77.0% 73.3% 2.7% 3.5% 0.0% 0.0% 0.0% 0.0% 3.5% 3.0% 0.0% 0.0% 15.9% 18.8% 0.9% 1.5%
.San Luis Obispo
(87) (148) (3) (7) (0) (0) (0) (0) (4) (6) (0) (0) (18) (38) (1) (3)
42.1% 37.3% 23.4% 22.9% 8.4% 9.3% 0.0% 0.0% 14.0% 16.1% 0.0% 1.7% 9.3% 8.5% 2.8% 4.2%
.San Mateo
(45) (44) (25) (27) (9) (11) (0) (0) (15) (19) (0) (2) (10) (10) (3) (5)
.Santa Barbara
38.5% 36.8% 29.6% 29.3% 7.5% 9.9% 0.3% 0.3% 10.9% 10.9% 2.3% 1.6% 8.0% 8.5% 2.9% 2.7%
.Santa Clara
(134) (138) (103) (110) (26) (37) (1) (1) (38) (41) (8) (6) (28) (32) (10) (10)
.Santa Cruz 67.2% 67.3% 24.6% 23.5% 0.0% 0.0% 0.0% 0.0% 3.0% 4.1% 2.2% 2.0% 3.0% 3.1% 0.0% 0.0%
Black shading indicates where data was unavailable to calculate an indicator.
56
White Hispanic / Latino Asian Pacific Islander Black American Indian Multirace Other
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
County 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 - 8 0 - 9 1 -
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
(90) (66) (33) (23) (0) (0) (0) (0) (4) (4) (3) (2) (4) (3) (0) (0)
47.2% 44.0% 7.2% 7.1% 2.4% 6.0% 0.0% 0.0% 26.4% 25.5% 2.4% 1.1% 12.8% 15.2% 1.6% 1.1%
.Solano
(59) (81) (9) (13) (3) (11) (0) (0) (33) (47) (3) (2) (16) (28) (2) (2)
63.2% 66.3% 6.0% 5.6% 1.9% 1.3% 0.0% 0.2% 2.2% 2.7% 0.6% 0.9% 25.7% 22.5% 0.3% 0.4%
.Sonoma
(199) (295) (19) (25) (6) (6) (0) (1) (7) (12) (2) (4) (81) (100) (1) (2)
54.1% 48.2% 20.8% 23.5% 4.6% 5.9% 0.0% 0.0% 9.6% 8.8% 0.8% 1.5% 8.3% 10.8% 1.9% 1.5%
.Stanislaus
(260) (197) (100) (96) (22) (24) (0) (0) (46) (36) (4) (6) (40) (44) (9) (6)
42.9% 34.9% 36.5% 42.6% 0.0% 0.8% 0.0% 0.0% 8.4% 8.1% 0.5% 0.4% 10.8% 12.4% 1.0% 0.8%
.Tulare
(87) (90) (74) (110) (0) (2) (0) (0) (17) (21) (1) (1) (22) (32) (2) (2)
58.5% 55.6% 19.6% 26.7% 2.6% 2.3% 0.0% 0.0% 7.2% 6.0% 0.3% 0.6% 11.4% 7.5% 0.3% 1.4%
.Ventura
(179) (740) (60) (355) (8) (30) (0) (0) (22) (80) (1) (8) (35) (100) (1) (19)
66.7% 65.2% 3.1% 2.1% 3.1% 1.4% 0.0% 0.0% 5.7% 5.7% 0.6% 0.0% 19.5% 24.1% 1.3% 1.4%
.Yolo
(106) (92) (5) (3) (5) (2) (0) (0) (9) (8) (5) (3) (31) (34) (2) (2)
64.7% 58.3% 18.1% 24.7% 1.0% 0.8% 0.1% 0.0% 3.5% 3.8% 2.2% 2.0% 9.9% 9.4% 0.4% 0.9%
Small Counties
(1,026) (1,360) (287) (575) (16) (19) (2) (1) (56) (89) (35) (47) (157) (218) (7) (22)
37.6% 37.9% 26.5% 27.6% 5.5% 5.2% 0.2% 0.2% 20.5% 18.9% 1.1% 1.0% 7.2% 7.9% 1.4% 1.4%
Total
(7,678) (10,732) (5,414) (7,814) (1,117) (1,474) (37) (48) (4,178) (5,343) (219) (283) (1,477) (2,232) (282) (399)
Black shading indicates where data was unavailable to calculate an indicator.
57
Table 6-8 - Race/ethnicity of new FSP consumers by county
Unknown
County
FY 2008-09 FY 2009-10
.Alameda
.Butte 15.9% (22) 11.6% (26)
.Contra Costa 4.0% (15) 3.2% (15)
.Fresno 21.3% (134) 20.7% (183)
.Kern 3.3% (22) 3.2% (21)
.Los Angeles 1.1% (92) 1.1% (107)
.Marin
.Merced 0.8% (1) 0.6% (1)
.Monterey
.Orange 4.9% (84) 8.5% (156)
.Placer 25.2% (38) 24.8% (36)
.Riverside
.Sacramento 1.3% (9) 6.5% (101)
.San Bernardino 3.9% (73) 3.4% (93)
.San Diego 9.1% (137) 5.3% (153)
.San Francisco 14.5% (92) 17.8% (130)
.San Joaquin 1.0% (7) 0.5% (7)
.San Luis Obispo 5.0% (6) 5.2% (11)
. San Mateo 7.8% (9) 12.6% (17)
.Santa Barbara
.Santa Clara 38.9% (222) 47.8% (343)
. Santa Cruz 6.3% (9) 3.9% (4)
. Solano 6.0% (8) 6.1% (12)
.Sonoma 3.7% (12) 3.5% (16)
.Stanislaus 0.4% (2) 7.5% (33)
.Tulare 0.5% (1) 1.5% (4)
.Ventura 19.0% (72) 5.5% (77)
.Yolo 4.8% (8) 4.1% (6)
Small Counties 6.0% (102) 5.6% (138)
Total 5.5% (1,177) 5.6% (1,690)
Black shading indicates where data was unavailable to calculate an indicator.
58
Table 6-9 - New FSP consumers by age group and county
County Children TAY Adults Older Adults
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
.Alameda
.Butte 8.0% (11) 2.2% (5) 32.1% (44) 20.1% (45) 57.7% (79) 63.8% (143) 2.2% (3) 13.8% (31)
.Contra Costa 29.6% (112) 28.4% (133) 25.9% (98) 28.6% (134) 42.3% (160) 40.1% (188) 2.1% (8) 3.0% (14)
.Fresno 21.0% (132) 29.3% (259) 24.8% (156) 27.6% (244) 52.6% (331) 41.8% (369) 1.6% (10) 1.2% (11)
.Kern 8.0% (53) 8.1% (53) 27.5% (182) 31.7% (208) 52.5% (347) 48.4% (318) 12.0% (79) 11.9% (78)
.Los Angeles 27.7% (2,223) 32.3% (3,166) 15.7% (1,257) 17.3% (1,702) 52.0% (4,176) 46.3% (4,541) 4.6% (373) 4.1% (406)
.Marin
.Merced 44.6% (58) 45.5% (71) 26.2% (34) 28.8% (45) 28.5% (37) 25.0% (39) 0.8% (1) 0.6% (1)
.Monterey
.Orange 17.1% (291) 15.2% (278) 35.3% (599) 37.2% (680) 40.1% (681) 39.7% (725) 7.5% (127) 7.8% (143)
.Placer 13.2% (20) 9.0% (13) 21.9% (33) 20.7% (30) 49.7% (75) 53.1% (77) 15.2% (23) 17.2% (25)
.Riverside
.Sacramento 17.3% (117) 8.0% (124) 10.1% (68) 8.4% (130) 51.5% (348) 69.5% (1073) 21.2% (143) 14.1% (217)
.San Bernardino 23.9% (449) 24.7% (673) 36.4% (685) 37.3% (1,018) 37.9% (712) 36.2% (988) 1.8% (34) 1.9% (51)
.San Diego 18.8% (284) 26.5% (770) 27.0% (408) 22.8% (662) 43.6% (658) 42.9% (1248) 10.5% (159) 7.8% (226)
.San Francisco 24.4% (155) 26.8% (196) 22.9% (145) 25.1% (184) 42.1% (267) 38.8% (284) 10.6% (67) 9.3% (68)
.San Joaquin 3.8% (28) 4.3% (59) 16.6% (122) 16.3% (224) 66.1% (485) 68.2% (937) 13.5% (99) 11.1% (153)
.San Luis Obispo 19.3% (23) 35.2% (75) 25.2% (30) 27.7% (59) 48.7% (58) 30.0% (64) 6.7% (8) 7.0% (15)
.San Mateo 31.9% (37) 31.9% (43) 68.1% (79) 68.1% (92) 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
.Santa Barbara
.Santa Clara 11.8% (67) 12.4% (89) 23.3% (133) 25.1% (180) 60.0% (342) 58.5% (420) 4.9% (28) 4.0% (29)
.Santa Cruz 0.0% (0) 0.0% (0) 43.4% (63) 35.3% (36) 28.3% (41) 35.3% (36) 28.3% (41) 29.4% (30)
.Solano 27.1% (36) 23.0% (45) 18.8% (25) 18.4% (36) 28.6% (38) 41.8% (82) 25.6% (34) 16.8% (33)
.Sonoma 25.7% (84) 25.2% (116) 17.7% (58) 18.4% (85) 54.7% (179) 44.3% (204) 1.8% (6) 12.1% (56)
.Stanislaus 6.6% (32) 6.8% (30) 21.7% (105) 24.0% (106) 62.1% (300) 59.5% (263) 9.5% (46) 9.7% (43)
.Tulare 4.4% (9) 3.8% (10) 31.9% (65) 38.2% (100) 61.3% (125) 55.3% (145) 2.5% (5) 2.7% (7)
.Ventura 20.0% (80) 2.7% (38) 26.9% (108) 29.6% (418) 17.0% (68) 54.2% (766) 36.2% (145) 13.5% (190)
.Yolo 1.2% (2) 1.4% (2) 19.8% (33) 19.0% (28) 70.7% (118) 70.7% (104) 8.4% (14) 8.8% (13)
Small Counties 22.9% (386) 22.8% (564) 23.4% (395) 23.1% (571) 45.7% (771) 45.6% (1127) 8.1% (136) 8.4% (207)
Total 21.7% (4,689) 22.7% (6,812) 22.8% (4,925) 23.4% (7,017) 48.1% (10,396) 47.1% (14,141) 7.4% (1,589) 6.8% (2,047)
Black shading indicates where data was unavailable to calculate an indicator.
59
Table 6-10 - FSP consumers by gender and county
Female Male
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10
.Alameda
.Butte 50.0% (60) 46.4% (97) 50.0% (60) 53.6% (112)
.Contra Costa 46.8% (177) 47.2% (221) 53.2% (201) 52.8% (247)
.Fresno 40.9% (211) 41.1% (299) 59.1% (305) 58.9% (428)
.Kern 54.5% (351) 51.0% (325) 45.5% (293) 49.0% (312)
.Los Angeles 42.5% (3,413) 43.2% (4,234) 57.5% (4,614) 56.8% (5,577)
.Marin
.Merced 45.7% (59) 44.5% (69) 54.3% (70) 55.5% (86)
.Monterey
.Orange 41.5% (686) 41.7% (713) 58.5% (966) 58.3% (998)
.Placer 38.4% (58) 41.4% (60) 61.6% (93) 58.6% (85)
.Riverside
.Sacramento 56.6% (380) 51.3% (745) 43.4% (291) 48.7% (706)
.San Bernardino 43.9% (822) 45.8% (1,245) 56.1% (1,049) 54.2% (1,476)
.San Diego 42.3% (590) 41.6% (1,172) 57.7% (806) 58.4% (1,645)
.San Francisco 29.3% (185) 32.0% (233) 70.7% (447) 68.0% (496)
.San Joaquin 60.5% (444) 53.9% (740) 39.5% (290) 46.1% (632)
.San Luis Obispo 44.5% (53) 44.6% (95) 55.5% (66) 55.4% (118)
.San Mateo 36.7% (40) 32.8% (40) 63.3% (69) 67.2% (82)
.Santa Barbara
.Santa Clara 41.1% (164) 38.3% (161) 58.9% (235) 61.7% (259)
.Santa Cruz 43.5% (60) 42.4% (42) 56.5% (78) 57.6% (57)
.Solano 43.2% (54) 44.9% (83) 56.8% (71) 55.1% (102)
.Sonoma 37.6% (121) 40.1% (183) 62.4% (201) 59.9% (273)
.Stanislaus 52.6% (254) 51.7% (228) 47.4% (229) 48.3% (213)
.Tulare 48.0% (98) 46.7% (121) 52.0% (106) 53.3% (138)
.Ventura 47.5% (159) 41.9% (571) 52.5% (176) 58.1% (791)
.Yolo 54.2% (90) 54.4% (80) 45.8% (76) 45.6% (67)
Small Counties 45.7% (740) 45.5% (1,083) 54.3% (878) 54.5% (1,298)
Total 44.3% (9,269) 44.2% (12,840) 55.7% (11,670) 55.8% (16,198)
Black shading indicates where data was unavailable to calculate an indicator.
60
Table 6-11 - FSP consumers by gender and county – Unknown and Missing Data
Unknown
County
FY 2008-09 FY 2009-10
.Alameda
.Butte 12.4% (17) 6.7% (15)
. Contra Costa 0.0% (0) 0.2% (1)
. Fresno 18.0% (113) 17.7% (156)
. Kern 2.6% (17) 3.0% (20)
. Los Angeles 0.0% (2) 0.0% (4)
. Marin
.Merced 0.8% (1) 0.6% (1)
. Monterey
.Orange 2.7% (46) 6.3% (115)
. Placer 0.0% (0) 0.0% (0)
. Riverside
.Sacramento 0.7% (5) 6.0% (93)
. San Bernardino 0.5% (9) 0.3% (9)
. San Diego 7.5% (113) 3.1% (89)
. San Francisco 0.3% (2) 0.4% (3)
. San Joaquin 0.0% (0) 0.1% (1)
. San Luis Obispo 0.0% (0) 0.0% (0)
. San Mateo 6.0% (7) 9.6% (13)
. Santa Barbara
.Santa Clara 30.0% (171) 41.5% (298)
. Santa Cruz 4.8% (7) 2.9% (3)
. Solano 6.0% (8) 5.6% (11)
. Sonoma 1.5% (5) 1.1% (5)
. Stanislaus 0.0% (0) 0.2% (1)
. Tulare 0.0% (0) 1.1% (3)
. Ventura 16.5% (66) 3.5% (50)
. Yolo 0.6% (1) 0.0% (0)
S mall Counties 4.1% (70) 3.6% (88)
T otal 3.1% (660) 3.3% (979)
Black shading indicates where data was unavailable to calculate an indicator.
61
Priority Indicator 7: Penetration of Mental Health Services
Table 7-1 - Penetration of mental health services by county
Penetration Rate
FY 2008-09 FY 2009-10
County
.Alameda 119.9% (33521/27964) 123.5% (34675/28080)
.Butte 80.1% (6216/7759) 63.8% (5014/7862)
.Contra Costa 99.6% (16331/16398) 108.4% (17952/16556)
.Fresno 46.4% (17252/37177) 43.2% (16356/37900)
.Kern 55.1% (17639/32020) 51.9% (16983/32751)
.Los Angeles 58.7% (191245/326066) 58.4% (190445/326127)
.Marin 95.9% (3324/3467) 89.2% (3128/3507)
.Merced 49.5% (5166/10431) 41.9% (4473/10674)
.Monterey 51.0% (6193/12149) 43.7% (5363/12273)
.Orange 64.9% (43945/67665) 64.8% (44454/68587)
.Placer 74.0% (3632/4907) 55.1% (2760/5008)
.Riverside 68.0% (41837/61545) 65.1% (41136/63235)
.Sacramento 81.8% (31080/38015) 172.0% (65775/38239)
.San Bernardino 60.8% (39595/65164) 57.7% (38264/66296)
.San Diego 68.3% (51333/75201) 66.5% (50360/75751)
.San Francisco 168.6% (23270/13801) 175.4% (24283/13844)
.San Joaquin 59.2% (13471/22741) 56.9% (13263/23327)
.San Luis Obispo 73.0% (4443/6084) 74.1% (4544/6130)
.San Mateo 132.4% (11356/8574) 136.8% (11772/8606)
.Santa Barbara 67.3% (7427/11042) 67.0% (7449/11112)
.Santa Clara 39.3% (9278/23637) 31.8% (7559/23760)
.Santa Cruz 65.5% (4282/6535) 62.2% (4092/6580)
.Solano 68.6% (5200/7575) 60.9% (4648/7632)
.Sonoma 45.6% (4227/9265) 47.6% (4456/9365)
.Stanislaus 51.6% (9324/18058) 49.3% (9068/18397)
.Tulare 47.2% (8958/18968) 46.4% (9005/19418)
.Ventura 66.4% (10972/16513) 61.1% (10192/16678)
.Yolo 55.8% (2927/5248) 61.2% (3264/5333)
Small Counties 75.3% (49075/65165) 71.0% (46962/66148)
Total 66.0% (672519/1019134) 67.8% (697695/1029176)
Black shading indicates where data was unavailable to calculate an indicator.
62
Table 7-2 - Penetration of services by race/ethnicity and county
White Hispanic / Latino Asian Pacific Islander Black American Indian Multirace Other
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
- - - - - - - - - - - - - - - -
8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
County
Alameda 129.5% 134.0% 31.9% 32.8% 69.4% 72.8% 40.2% 39.9% 199.7% 205.4% 75.3% 69.3% 295.8% 312.4% 955.8% 1094.2%
(8248/6370) (8407/6274) (2961/9294) (3106/9477) (2757/3974) (2942/4043) (78/194) (79/198) (12914/6468) (13165/6411) (183/243) (174/251) (3742/1265) (3971/1271) (1491/156) (1707/156)
Butte 74.9% 58.7% 21.3% 22.6% 161.8% 139.6% 55.6% 75.0% 99.4% 84.2% 54.1% 40.4% 273.2% 244.4% 366.7% 147.6%
(4150/5543) (3286/5594) (274/1289) (302/1337) (419/259) (356/255) (5/9) (6/8) (162/163) (139/165) (118/218) (91/225) (702/257) (628/257) (77/21) (31/21)
Contra Costa 109.7% 118.2% 5.1% 4.5% 91.6% 90.9% 50.0% 93.0% 156.8% 172.7% 54.0% 62.3% 810.3% 963.7% 329.4% 368.2%
(6293/5736) (6749/5709) (319/6249) (291/6417) (987/1078) (997/1097) (27/54) (53/57) (4071/2596) (4465/2585) (68/126) (81/130) (3841/474) (4587/476) (280/85) (313/85)
Fresno 74.3% 67.4% 28.3% 27.7% 42.5% 36.3% 28.6% 10.7% 96.4% 90.5% 33.2% 28.0% 57.3% 60.2% 122.2% 113.6%
(5537/7455) (5024/7458) (6557/23160) (6576/23778) (1332/3133) (1162/3197) (8/28) (3/28) (2227/2310) (2116/2339) (157/473) (136/485) (307/536) (321/533) (99/81) (92/81)
Kern 80.7% 73.7% 33.0% 32.2% 30.1% 26.6% 75.0% 50.0% 105.9% 101.7% 51.2% 46.3% 128.9% 125.6% 435.3% 483.8%
(8184/10146) (7555/10251) (6098/18497) (6142/19065) (188/624) (169/635) (15/20) (10/20) (1987/1877) (1960/1928) (166/324) (150/324) (597/463) (579/461) (296/68) (329/68)
Los Angeles 78.0% 77.1% 37.3% 38.6% 9.1% 8.4% 9.3% 8.6% 145.3% 145.9% 70.4% 67.2% 2.6% 2.7% 20.5% 14.1%
(38619/49499) (37638/48831) (80693/216270) (83760/217105) (1609/17758) (1499/17916) (67/722) (63/731) (47530/32704) (47193/32348) (987/1402) (945/1407) (169/6444) (179/6523) (260/1266) (179/1266)
Marin 131.4% 123.7% 28.5% 28.7% 85.1% 86.0% 66.7% 50.0% 213.3% 174.4% 80.0% 53.3% 287.7% 259.4% 96.2% 126.9%
(2110/1606) (1954/1579) (427/1496) (448/1562) (74/87) (74/86) (2/3) (2/4) (273/128) (225/129) (12/15) (8/15) (305/106) (275/106) (25/26) (33/26)
Merced 76.9% 71.2% 19.4% 16.5% 71.2% 68.5% 33.3% 33.3% 140.3% 134.8% 67.9% 44.2% 197.0% 251.5% 366.7% 437.5%
(1868/2428) (1733/2435) (1339/6890) (1174/7131) (391/549) (376/549) (2/6) (2/6) (439/313) (418/310) (36/53) (23/52) (329/167) (420/167) (88/24) (105/24)
Monterey 99.8% 77.6% 17.8% 26.1% 42.3% 37.4% 58.8% 14.7% 175.0% 121.2% 53.1% 31.3% 213.0% 204.3% 2150.9% 94.5%
(1790/1794) (1357/1749) (1685/9448) (2515/9618) (132/312) (117/313) (20/34) (5/34) (329/188) (223/184) (34/64) (20/64) (541/254) (521/255) (1183/55) (52/55)
Orange 113.8% 113.6% 32.3% 33.4% 65.3% 61.1% 46.2% 43.5% 201.4% 205.9% 49.4% 43.3% 136.0% 142.8% 628.3% 554.7%
(17523/15399) (17338/15256) (13876/42947) (14653/43864) (3998/6125) (3816/6241) (90/195) (87/200) (1778/883) (1812/880) (193/391) (174/402) (1925/1415) (2048/1434) (1954/311) (1725/311)
Placer 59.1% 45.2% 21.2% 15.8% 37.2% 27.8% 66.7% 75.0% 295.0% 260.0% 141.7% 100.0% 186.8% 151.1% 253.3% 233.3%
(2009/3397) (1555/3437) (260/1225) (203/1282) (32/86) (25/90) (2/3) (3/4) (59/20) (52/20) (34/24) (23/23) (254/136) (210/139) (38/15) (35/15)
Riverside 82.1% 80.5% 32.0% 30.1% 45.0% 45.6% 35.6% 38.6% 113.2% 114.4% 42.7% 36.1% 461.1% 381.0% 594.6% 544.3%
(16460/20058) (16386/20353) (10901/34050) (10615/35274) (546/1213) (580/1271) (31/87) (34/88) (5011/4425) (5150/4501) (211/494) (184/510) (4929/1069) (4153/1090) (886/149) (811/149)
Sacramento 83.3% 141.0% 40.1% 74.1% 57.5% 81.6% 14.6% 28.3% 140.8% 235.8% 51.0% 89.3% 140.9% 241.9% 278.9% 665.7%
(13226/15878) (22319/15830) (3917/9759) (7337/9908) (2342/4076) (3360/4120) (46/316) (91/321) (7251/5150) (12216/5181) (214/420) (376/421) (3171/2251) (5543/2291) (463/166) (1105/166)
San Bernardino 88.2% 82.1% 23.9% 23.6% 48.5% 44.4% 79.2% 116.3% 91.6% 83.7% 39.3% 35.2% 325.7% 343.3% 486.8% 499.5%
(15558/17643) (14433/17577) (8617/35987) (8706/36942) (756/1559) (708/1593) (95/120) (143/123) (6868/7497) (6418/7670) (259/659) (235/667) (4866/1494) (5218/1520) (998/205) (1024/205)
San Diego 83.9% 80.6% 34.7% 34.0% 63.6% 59.0% 24.8% 31.0% 138.4% 135.6% 36.8% 30.1% 208.8% 222.7% 233.1% 215.2%
(22248/26512) (21363/26518) (12739/36722) (12683/37255) (2419/3802) (2274/3855) (74/298) (95/306) (6156/4449) (5915/4362) (354/962) (300/996) (4510/2160) (4821/2165) (690/296) (637/296)
San Francisco 130.6% 128.5% 101.9% 111.1% 85.9% 80.8% 53.1% 42.7% 230.3% 218.1% 130.4% 120.0% 228.0% 210.9% 474.2% 480.5%
(6487/4966) (6440/5012) (3025/2969) (3295/2967) (2500/2911) (2357/2917) (69/130) (56/131) (4708/2044) (4415/2024) (133/102) (126/105) (1254/550) (1181/560) (607/128) (615/128)
San Joaquin 82.0% 78.1% 23.8% 23.2% 40.7% 39.2% 44.4% 41.7% 116.1% 116.0% 46.8% 49.6% 228.1% 220.2% 290.5% 260.3%
(4872/5944) (4663/5971) (2540/10672) (2555/11013) (1334/3274) (1340/3421) (16/36) (15/36) (2087/1797) (2157/1859) (108/231) (116/234) (1654/725) (1610/731) (183/63) (164/63)
San Luis 87.1% 86.7% 33.8% 35.0% 48.9% 47.4% 33.3% 33.3% 112.9% 111.6% 41.0% 33.3% 231.0% 266.5% 256.3% 362.5%
(3162/3630) (3135/3618) (696/2058) (739/2114) (46/9)4 (45/95) (1/3) (1/3) (96/85) (96/86) (16/39) (13/39) (365/158) (421/158) (41/16) (58/16)
San Mateo 162.0% 167.1% 82.8% 88.0% 95.4% 103.5% 28.3% 32.5% 240.3% 225.3% 68.6% 76.5% 211.4% 212.6% 775.0% 762.5%
(3905/2410) (3973/2378) (3630/4386) (3905/4440) (791/829) (866/837) (34/120) (39/120) (1103/459) (1043/463) (35/51) (39/51) (539/255) (538/253) (496/64) (488/64)
Santa Barbara 59.8% 52.1% 36.8% 41.1% 22.4% 17.5% 80.0% 80.0% 99.1% 79.0% 50.6% 37.2% 361.6% 256.3% 8.8% 5.9%
(2258/3778) (1970/3784) (2411/6548) (2714/6600) (48/214) (38/217) (4/5) (4/5) (218/220) (181/229) (43/85) (32/86) (575/159) (405/158) (3/34) (2/34)
Santa Clara 57.5% 9.6% 18.0% 6.9% 40.6% 10.0% 20.7% 2.9% 79.3% 21.4% 29.5% 9.3% 60.7% 14.2% 272.7% 108.1%
(3458/6012) (2766/28745) (2135/11894) (1703/24622) (1521/3750) (1348/13484) (19/92) (13/443) (581/733) (482/2250) (66/224) (48/517) (465/766) (363/2563) (450/165) (362/335)
Santa Cruz 89.6% 84.2% 37.6% 35.7% 29.4% 33.1% 33.3% 33.3% 123.5% 117.4% 104.0% 84.0% 241.5% 259.6% 114.9% 89.4%
(2240/2501) (2079/2470) (1357/3608) (1314/3682) (35/119) (40/121) (1/3) (1/3) (105/85) (101/86) (26/25) (21/25) (355/147) (379/146) (54/47) (42/47)
Solano 73.0% 64.7% 30.5% 25.9% 46.1% 43.1% 23.1% 22.5% 122.6% 109.2% 38.2% 21.1% 107.5% 103.9% 221.9% 218.8%
(2097/2874) (1853/2865) (711/2332) (617/2384) (241/523) (232/538) (9/39) (9/40) (1425/1162) (1252/1147) (42/110) (24/114) (542/504) (530/510) (71/32) (70/32)
Sonoma 58.0% 62.1% 12.2% 12.3% 29.2% 31.0% 66.7% 81.8% 73.5% 69.0% 31.3% 27.0% 263.9% 283.5% 92.5% 87.5%
(2808/4845) (2986/4812) (433/3557) (450/3668) (69/236) (77/248) (8/12) (9/11) (155/211) (149/216) (42/134) (37/137) (607/230) (655/231) (37/40) (35/40)
Stanislaus 59.7% 26.7% 22.3% 14.7% 61.4% 41.9% 22.9% 7.5% 75.6% 43.5% 35.1% 16.5% 481.0% 273.6% 797.4% 309.4%
(4024/6740) (3889/14544) (2125/9526) (2095/14262) (377/614) (394/940) (11/48) (6/80) (408/540) (393/903) (61/174) (50/303) (1818/378) (1817/664) (303/38) (263/85)
Black shading indicates where data was unavailable to calculate an indicator.
63
White Hispanic / Latino Asian Pacific Islander Black American Indian Multirace Other
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
- - - - - - - - - - - - - - - -
8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
County
.Tulare 64.8% 61.5% 32.5% 32.9% 63.2% 58.6% 33.3% 0.0% 123.6% 115.4% 23.6% 18.1% 465.0% 468.3% 411.5% 446.2%
(2897/4474) (2768/4500) (4365/13441) (4550/13843) (228/361) (219/374) (2/6) (0/6) (272/220) (255/221) (52/220) (41/227) (1023/220) (1035/221) (107/26) (116/26)
Ventura 102.5% 89.7% 31.4% 29.4% 46.2% 43.5% 15.0% 19.0% 180.9% 166.2% 56.7% 46.4% 425.3% 474.2% 297.8% 384.8%
(5261/5131) (4603/5129) (3249/10350) (3096/10516) (157/340) (148/340) (3/20) (4/21) (416/230) (379/228) (55/97) (45/97) (1276/300) (1432/302) (137/46) (177/46)
.Yolo 74.1% 80.4% 10.2% 9.7% 15.7% 19.7% 9.1% 54.5% 79.0% 87.2% 54.1% 58.3% 256.4% 297.0% 180.0% 220.0%
(1787/2411) (1946/2421) (197/1938) (193/1988) (71/451) (91/461) (1/11) (6/11) (147/186) (170/195) (20/37) (21/3)6 (500/195) (597/201) (36/20) (44/20)
Small Counties 86.6% 80.9% 36.9% 34.7% 86.1% 80.3% 82.4% 98.1% 174.0% 155.7% 45.8% 46.4% 211.8% 219.4% 254.5% 234.2%
(30040/34676) (28162/34824) (8896/24093) (8607/24829) (905/1051) (863/1075) (42/51) (52/53) (1564/899) (1425/915) (1076/2349) (1107/2385) (3927/1854) (4125/1880) (476/187) (438/187)
Total 85.5% 76.9% 33.3% 33.1% 44.3% 37.7% 29.3% 28.6% 141.4% 142.8% 49.3% 44.9% 180.9% 178.1% 308.9% 272.9%
(239174/279856) (238330/309924) (186432/560655) (194344/586943) (26305/59402) (26513/70329) (782/2665) (885/3091) (110340/78042) (113965/79835) (4801/9746) (4640/10328) (45108/24932) (48562/27266) (11829/3830) (11046/4047)
Black shading indicates where data was unavailable to calculate an indicator.
64
Table 7-3 - Penetration of mental health services by age group and county
Children TAY Adults Older Adults
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
99.3% 107.8% 158.9% 165.2% 123.2% 123.8% 114.7% 113.5%
Alameda
(8349/8410) (9078/8425) (6067/3819) (6378/3860) (17127/13899) (17189/13889) (2106/1836) (2163/1905)
98.5% 83.4% 62.5% 48.8% 81.6% 62.3% 67.8% 58.3%
Butte
(1727/1753) (1470/1763) (1048/1676) (819/1680) (3069/3762) (2389/3833) (385/568) (342/587)
78.6% 88.4% 125.1% 137.0% 106.7% 114.1% 86.5% 94.9%
Contra Costa
(3910/4972) (4413/4994) (3178/2541) (3512/2564) (8217/7699) (8858/7766) (1026/1186) (1169/1232)
35.6% 35.0% 59.5% 55.0% 50.7% 45.7% 49.7% 46.9%
Fresno
(4771/13413) (4755/13602) (3323/5583) (3098/5634) (8393/16567) (7756/16980) (802/1614) (789/1684)
47.8% 47.9% 75.4% 78.6% 54.7% 47.4% 50.6% 42.4%
Kern
(5513/11531) (5644/11776) (3489/4629) (3676/4678) (7866/14389) (6998/14764) (744/1471) (650/1533)
52.6% 55.7% 85.3% 82.7% 55.1% 52.8% 66.5% 64.9%
Los Angeles
(59344/112830) (61802/110915) (35657/41823) (35732/43206) (85129/154630) (81696/154653) (11167/16783) (11265/17353)
68.7% 65.9% 110.8% 92.9% 104.3% 97.2% 127.0% 129.1%
Marin
(748/1089) (741/1124) (532/480) (458/493) (1683/1613) (1550/1595) (362/28)5 (382/296)
21.6% 21.4% 66.2% 56.3% 64.9% 50.9% 64.2% 65.5%
Merced
(820/3796) (827/3857) (1040/1571) (894/1588) (3004/4632) (2432/4782) (278/433) (293/447)
45.1% 36.9% 77.2% 71.2% 47.7% 40.6% 54.1% 51.7%
Monterey
(2097/4651) (1729/4685) (1261/1634) (1169/1643) (2532/5305) (2176/5360) (303/560) (302/584)
45.6% 47.3% 101.3% 103.9% 65.8% 63.1% 108.3% 97.2%
Orange
(10271/22507) (10726/22660) (9263/9141) (9706/9342) (21538/32749) (20943/33200) (3539/3268) (3292/3386)
58.2% 50.4% 91.1% 69.1% 84.4% 58.8% 44.3% 30.2%
Placer
(797/1369) (702/1394) (677/743) (535/774) (1962/2325) (1383/2353) (208/469) (147/487)
38.4% 37.6% 110.2% 102.3% 77.4% 73.0% 62.4% 66.2%
Riverside
(7966/20722) (7966/21166) (10112/9179) (9684/9463) (21989/28418) (21361/29263) (2015/3227) (2214/3342)
70.6% 0.0% 100.5% 0.0% 83.8% 0.0% 82.9% 0.0%
Sacramento
(8969/12698) (0/12683) (5548/5520) (0/5596) (14808/17672) (0/17741) (1761/2125) (0/2219)
49.2% 47.7% 90.6% 89.6% 61.3% 56.3% 50.5% 48.8%
San Bernardino
(11020/22380) (10765/22577) (8476/9352) (8547/9536) (18576/30313) (17405/30920) (1575/3118) (1592/3264)
52.5% 53.6% 89.7% 89.1% 70.8% 66.5% 91.1% 86.9%
San Diego
(12995/24754) (13317/24850) (8873/9887) (8961/10060) (25807/36467) (24340/36592) (3728/4092) (3692/4249)
128.4% 125.4% 236.7% 257.0% 162.0% 170.0% 237.9% 246.5%
San Francisco
(3621/2819) (3566/2844) (2866/1211) (3043/1184) (13666/8437) (14355/8444) (3174/1334) (3380/1371)
27.8% 24.9% 79.5% 78.3% 80.7% 78.8% 93.5% 90.2%
San Joaquin
(2624/9440) (2428/9735) (2546/3202) (2568/3279) (7216/8939) (7176/9105) (1085/1160) (1091/1209)
82.4% 84.8% 57.9% 58.8% 79.2% 80.4% 56.5% 53.5%
San Luis Obispo
(1224/1485) (1278/1507) (858/1482) (871/1481) (2095/2646) (2134/2654) (266/471) (261/488)
95.5% 104.7% 188.0% 194.2% 129.2% 130.3% 197.4% 198.8%
San Mateo
(2330/2440) (2554/2439) (2094/1114) (2183/1124) (5633/4361) (5693/4369) (1301/659) (1342/675)
59.8% 59.2% 73.9% 73.1% 70.4% 70.9% 86.9% 92.9%
Santa Barbara
(2148/3589) (2133/3606) (1411/1910) (1410/1930) (3515/4991) (3553/5009) (479/551) (527/567)
12.6% 2.4% 36.7% 10.6% 53.3% 15.1% 77.4% 24.4%
Santa Clara
(1001/7937) (665/27790) (1125/3063) (894/8444) (5806/10899) (4824/31906) (1346/1738) (1177/4818)
Black shading indicates where data was unavailable to calculate an indicator.
65
Children TAY Adults Older Adults
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
75.4% 72.8% 91.3% 84.6% 54.3% 51.2% 45.3% 47.1%
Santa Cruz
(1332/1767) (1304/1790) (970/1062) (889/1051) (1821/3355) (1727/3372) (159/351) (173/367)
59.1% 56.6% 85.5% 70.4% 70.8% 61.3% 65.1% 58.5%
Solano
(1465/2480) (1407/2484) (928/1086) (772/1097) (2498/3530) (2179/3552) (312/479) (292/499)
39.6% 43.3% 60.3% 63.6% 45.0% 45.5% 45.2% 46.6%
Sonoma
(1024/2589) (1144/2644) (854/1416) (906/1424) (2021/4496) (2048/4503) (345/764) (370/794)
57.0% 32.7% 68.8% 41.4% 43.2% 22.4% 40.2% 18.0%
Stanislaus
(3814/6692) (3907/11931) (1695/2462) (1740/4198) (3436/7955) (3089/13765) (381/948) (339/1886)
58.2% 58.7% 56.9% 59.3% 35.8% 32.9% 37.2% 37.2%
Tulare
(4099/7041) (4213/7182) (1556/2736) (1634/2757) (2989/8347) (2831/8599) (314/843) (327/879)
57.0% 57.0% 95.6% 91.1% 63.5% 55.7% 72.5% 60.1%
Ventura
(3113/5465) (3133/5499) (2257/2360) (2154/2365) (4890/7703) (4339/7790) (714/985) (616/1025)
34.8% 37.8% 38.8% 48.4% 74.2% 79.3% 97.4% 98.6%
Yolo
(514/1478) (568/1502) (491/1266) (620/1281) (1660/2236) (1799/2270) (262/269) (277/281)
71.8% 68.9% 87.6% 86.4% 75.2% 68.9% 66.9% 63.7%
Small Counties
(13368/18616) (12989/18851) (8527/9734) (8465/9798) (24058/32012) (22401/32498) (3219/4811) (3186/5000)
Total 53.1% 47.8% 89.5% 80.1% 67.2% 57.6% 76.9% 66.7%
(180829/340713) (175224/366275) (126752/141682) (121309/151530) (323004/480347) (294624/511527) (43356/56398) (41650/62427)
Black shading indicates where data was unavailable to calculate an indicator.
66
Table 7-4 - Penetration of mental health services by gender and county
Female Male
County FY 08-09 FY 09-10 FY 08-09 FY 09-10
Alameda 98.5% (16265/16509) 101.9% (16913/16592) 150.6% (17256/11455) 154.6% (17762/11488)
Butte 72.6% (3316/4567) 56.8% (2629/4631) 90.9% (2900/3192) 73.8% (2385/3232)
Contra Costa 88.9% (8647/9732) 95.8% (9411/9822) 115.3% (7684/6665) 126.8% (8541/6734)
Fresno 39.0% (8183/20972) 36.2% (7737/21382) 56.0% (9069/16206) 52.2% (8619/16518)
Kern 46.0% (8438/18347) 40.9% (7681/18780) 67.3% (9201/13674) 66.6% (9302/13971)
Los Angeles 47.6% (88361/185545) 47.8% (88924/185913) 73.2% (102884/140521) 72.4% (101521/140214)
Marin 83.2% (1699/2043) 77.4% (1597/2062) 114.0% (1625/1425) 106.0% (1531/1444)
Merced 45.0% (2647/5886) 41.4% (2492/6025) 55.4% (2519/4545) 42.6% (1981/4649)
Monterey 46.1% (3139/6809) 38.3% (2635/6883) 57.2% (3054/5340) 50.6% (2728/5390)
Orange 54.5% (20791/38122) 54.1% (20935/38679) 78.4% (23154/29543) 78.6% (23519/29908)
Placer 60.0% (1860/3101) 43.4% (1372/3161) 98.1% (1772/1806) 75.1% (1388/1847)
Riverside 51.8% (18374/35455) 50.8% (18516/36438) 89.9% (23463/26090) 84.4% (22620/26797)
Sacramento 69.3% (15464/22307) 139.7% (31357/22450) 99.4% (15616/15708) 218.0% (34418/15789)
San Bernardino 49.4% (18793/38067) 46.6% (18082/38762) 76.8% (20802/27097) 73.3% (20182/27534)
San Diego 59.0% (25785/43702) 56.9% (25051/44049) 81.1% (25548/31499) 79.8% (25309/31703)
San Francisco 137.3% (10494/7644) 141.8% (10869/7665) 207.5% (12776/6157) 217.1% (13414/6179)
San Joaquin 53.7% (7067/13159) 51.2% (6913/13498) 66.8% (6404/9582) 64.6% (6350/9830)
San Luis Obispo 64.3% (2288/3560) 64.9% (2325/3585) 85.4% (2155/2524) 87.2% (2219/2545)
San Mateo 123.2% (6190/5026) 124.1% (6262/5046) 145.6% (5166/3548) 154.8% (5510/3560)
Santa Barbara 57.3% (3624/6327) 56.8% (3621/6374) 80.7% (3803/4715) 80.8% (3828/4738)
Santa Clara 33.8% (4573/13528) 9.2% (3651/39490) 46.5% (4705/10109) 11.7% (3908/33468)
Santa Cruz 46.3% (1771/3827) 43.3% (1668/3852) 92.7% (2511/2708) 88.9% (2424/2727)
Solano 55.1% (2478/4496) 48.8% (2214/4536) 88.4% (2722/3079) 78.6% (2434/3096)
Sonoma 35.9% (1984/5523) 36.3% (2025/5577) 59.9% (2243/3742) 64.2% (2431/3788)
Stanislaus 44.1% (4624/10496) 24.8% (4440/17893) 62.2% (4700/7562) 33.3% (4628/13887)
Tulare 41.0% (4344/10583) 39.8% (4312/10834) 55.0% (4614/8384) 54.7% (4693/8583)
Ventura 54.7% (5124/9364) 50.6% (4784/9458) 81.8% (5848/7149) 74.9% (5408/7220)
Yolo 52.7% (1608/3051) 56.8% (1760/3096) 60.0% (1319/2197) 67.2% (1504/2237)
Small Counties 67.7% (25880/38224) 62.8% (24358/38805) 86.1% (23195/26940) 82.7% (22604/27347)
Total
59.1% (323811/547748) 57.0% (334534/586533) 85.8% (348708/406222) 82.7% (363161/439076)
Black shading indicates where data was unavailable to calculate an indicator.
67
Priority Indicator 8: Access to a Primary Care Physician
Table 8-1 - FSP access to a primary care physician by county
County Access to a Primary Care Physician
FY 2008-09 FY 2009-10
.Alameda
.Butte 65.5% (57) 62.8% (49)
.Contra Costa 52.0% (140) 56.5% (212)
.Fresno 43.9% (126) 57.5% (350)
.Kern 75.6% (306) 66.8% (261)
.Los Angeles 54.1% (2,794) 60.5% (3,763)
.Marin
.Merced 87.3% (69) 82.4% (84)
.Monterey
.Orange 53.1% (637) 60.2% (737)
.Placer 62.8% (81) 76.6% (59)
.Riverside
.Sacramento 65.5% (357) 75.9% (971)
.San Bernardino 50.9% (387) 52.9% (347)
.San Diego 49.7% (556) 71.8% (1,391)
.San Francisco 66.3% (344) 76.2% (422)
.San Joaquin 59.7% (283) 71.1% (811)
.San Luis Obispo 80.2% (69) 74.3% (113)
.San Mateo 68.4% (52) 56.4% (53)
.Santa Barbara
.Santa Clara 60.9% (265) 64.8% (346)
.Santa Cruz 84.2% (96) 92.0% (46)
.Solano 94.8% (109) 93.6% (147)
.Sonoma 75.0% (174) 86.0% (276)
.Stanislaus 68.1% (228) 70.6% (240)
.Tulare 84.3% (113) 82.6% (138)
.Ventura 87.4% (180) 74.2% (853)
.Yolo 74.2% (95) 93.0% (107)
Small Counties 76.0% (818) 76.5% (1,276)
Total 59.7% (8,336) 67.3% (13,052)
Black shading indicates where data was unavailable to calculate an indicator.
68
Table 8-2 - FSP access to a primary care physician by race/ethnicity and county
County White Hispanic / Asian Pacific Black American Multirace Other
Latino Islander Indian
9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0
0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9- 8- 9-
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
F F F F F F F F F F F F F F F F
.Alameda
78.4% 81.8% 0.0% 4.5% 0.0% 0.0% 0.0% 0.0% 5.9% 2.3% 3.9% 2.3% 9.8% 6.8% 2.0% 2.3%
.Butte
(40) (36) (0) (2) (0) (0) (0) (0) (3) (1) (2) (1) (5) (3) (1) (1)
26.3% 28.1% 2.3% 2.0% 8.3% 4.9% 0.0% 0.0% 32.3% 28.6% 0.0% 0.0% 30.1% 35.0% 0.8% 1.5%
.Contra Costa
(35) (57) (43) (4) (11) (10) (0) (0) (43) (58) (0) (0) (40) (71) (1) (3)
40.5% 35.3% 36.2% 46.7% 5.2% 3.5% 0.0% 0.0% 16.4% 12.6% 0.9% 0.3% 0.9% 1.6% 0.0% 0.0%
.Fresno
(47) (112) (42) (148) (6) (11) (0) (0) (19) (40) (1) (1) (1) (5) (0) (0)
65.8% 58.3% 17.3% 22.8% 1.0% 1.2% 0.0% 0.0% 9.5% 9.8% 1.7% 2.0% 3.1% 2.4% 1.7% 3.5%
.Kern
(194) (148) (51) (58) (3) (3) (0) (0) (28) (25) (5) (5) (9) (6) (5) (9)
20.5% 21.9% 41.1% 42.0% 6.4% 6.0% 0.3% 0.1% 29.3% 28.0% 0.5% 0.6% 0.3% 0.1% 1.7% 1.3%
.Los Angeles
(566) (816) (1,136) (1,565) (177) (222) (8) (2) (811) (1,041) (15) (24) (7) (5) (46) (47)
.Marin
40.6% 46.4% 31.9% 31.0% 4.3% 0.0% 0.0% 0.0% 14.5% 9.5% 1.4% 1.2% 7.2% 10.7% 0.0% 1.2%
.Merced
(28) (39) (22) (26) (3) (0) (0) (0) (10) (8) (1) (1) (5) (9) (0) (1)
.Monterey
48.5% 48.4% 22.6% 24.1% 9.0% 8.3% 0.5% 0.4% 5.7% 6.4% 0.8% 0.6% 11.1% 10.4% 1.8% 1.3%
.Orange
(298) (331) (139) (165) (55) (57) (3) (3) (35) (44) (5) (4) (68) (71) (11) (9)
70.8% 75.6% 12.3% 7.3% 1.5% 0.0% 0.0% 0.0% 4.6% 2.4% 4.6% 0.0% 6.2% 12.2% 0.0% 2.4%
.Placer
(46) (31) (8) (3) (1) (0) (0) (0) (3) (1) (3) (0) (4) (5) (0) (1)
.Riverside
32.7% 45.2% 3.9% 7.4% 34.6% 17.0% 0.0% 0.0% 13.2% 18.4% 0.6% 0.3% 12.7% 9.8% 2.3% 1.9%
.Sacramento
(116) (423) (14) (69) (123) (159) (0) (0) (47) (172) (2) (3) (45) (92) (8) (18)
36.9% 44.8% 25.6% 19.5% 1.6% 1.8% 0.0% 0.0% 18.9% 21.2% 0.3% 0.0% 15.1% 11.8% 1.6% 0.9%
.San Bernardino
(137) (152) (95) (66) (6) (6) (0) (0) (70) (72) (1) (0) (56) (40) (6) (3)
41.4% 45.6% 23.0% 23.1% 3.6% 4.2% 0.2% 0.2% 23.0% 13.5% 0.8% 0.7% 11.3% 12.2% 0.6% 0.5%
.San Diego
(209) (604) (116) (306) (18) (55) (1) (3) (97) (179) (4) (9) (57) (162) (3) (7)
27.3% 30.3% 17.5% 16.6% 5.7% 5.0% 0.0% 0.0% 36.0% 35.9% 0.3% 0.3% 10.8% 9.6% 2.4% 2.3%
.San Francisco
(81) (104) (52) (57) (17) (17) (0) (0) (107) (123) (1) (1) (32) (33) (7) (8)
15.7% 29.2% 20.3% 18.0% 22.1% 18.2% 0.0% 0.1% 26.7% 18.6% 1.4% 4.3% 11.7% 10.4% 2.1% 1.1%
.San Joaquin
(44) (236) (57) (145) (62) (147) (0) (1) (75) (150) (4) (35) (33) (84) (6) (9)
.San Luis 78.8% 76.6% 3.0% 1.9% 0.0% 0.0% 0.0% 0.0% 1.5% 2.8% 0.0% 0.0% 16.7% 17.8% 0.0% 0.9%
Obispo (52) (82) (2) (2) (0) (0) (0) (0) (1) (3) (0) (0) (11) (19) (0) (1)
53.1% 48.9% 14.3% 20.0% 8.2% 6.7% 0.0% 0.0% 14.3% 11.1% 0.0% 2.2% 8.2% 4.4% 2.0% 6.7%
.San Mateo
(26) (22) (7) (9) (4) (3) (0) (0) (7) (5) (0) (1) (4) (2) (1) (3)
.Santa Barbara
38.5% 36.9% 28.7% 30.8% 9.2% 13.1% 0.6% 0.0% 10.3% 8.6% 2.9% 1.5% 5.7% 6.1% 4.0% 3.0%
.Santa Clara
(67) (73) (50) (61) (16) (26) (1) (0) (18) (17) (5) (3) (10) (12) (7) (6)
Black shading indicates where data was unavailable to calculate an indicator.
69
67.0% 57.1% 20.9% 33.3% 0.0% 0.0% 0.0% 0.0% 4.4% 4.8% 3.3% 2.4% 4.4% 2.4% 0.0% 0.0%
.Santa Cruz
(61) (24) (19) (14) (0) (0) (0) (0) (4) (2) (3) (1) (4) (1) (0) (0)
47.6% 44.6% 7.8% 7.2% 2.9% 7.2% 0.0% 0.0% 24.3% 25.2% 2.9% 1.4% 12.6% 13.7% 1.9% 0.7%
.Solano
(49) (62) (8) (10) (3) (10) (0) (0) (25) (35) (3) (2) (13) (19) (2) (1)
63.7% 67.7% 4.8% 4.6% 1.8% 1.5% 0.0% 0.4% 1.8% 4.2% 0.6% 0.4% 26.4% 20.5% 0.0% 0.8%
.Sonoma
(107) (178) (8) (12) (3) (4) (0) (1) (3) (11) (1) (1) (46) (54) (0) (2)
55.5% 48.6% 16.7% 23.6% 5.7% 4.5% 0.0% 0.0% 11.0% 9.1% 0.9% 2.3% 8.8% 10.0% 1.3% 1.8%
.Stanislaus
(126) (107) (38) (52) (13) (10) (0) (0) (25) (20) (2) (5) (20) (22) (3) (4)
46.0% 29.9% 31.9% 50.4% 0.0% 0.0% 0.0% 0.0% 9.7% 6.6% 0.9% 0.7% 10.6% 11.7% 0.9% 0.7%
.Tulare
(52) (41) (36) (69) (0) 90) (0) (0) (11) (9) (1) (1) (12) (16) (1) (1)
56.4% 57.9% 26.4% 24.5% 3.1% 3.3% 0.0% 0.0% 6.7% 5.9% 0.0% 0.6% 7.4% 6.3% 0.0% 1.6%
.Ventura
(92) (479) (43) (203) (5) (27) (0) (0) (11) (49) (0) (5) (12) (52) (0) (13)
67.4% 67.3% 2.1% 2.9% 2.1% 1.9% 0.0% 0.0% 5.3% 5.8% 0.0% 0.0% 21.1% 20.2% 2.1% 1.9%
.Yolo
(64) (70) (2) (3) (2) (2) (0) (0) (5) (6) (0) (0) (20) (21) (2) (2)
76.9% 59.6% 16.1% 24.1% 0.8% 0.5% 0.0% 0.1% 2.7% 2.6% 3.1% 2.1% 11.0% 9.9% 0.3% 1.0%
Small Counties
(543) (727) (114) (294) (6) (6) (0) (1) (19) (32) (22) (26) (78) (121) (2) (12)
32.3% 38.0% 25.2% 25.6% 6.4% 6.6% 0.2% 0.1% 17.7% 16.1% 1.0% 1.0% 7.1% 7.1% 1.3% 1.2%
Total
(2,692) (4,954) (2,102) (3,343) (534) (865) (13) (11) (1,477) (2,103) (81) (129) (592) (925) (112) (161)
Black shading indicates where data was unavailable to calculate an indicator.
70
Table 8-3 - Race/Ethnicity – Unknown/Missing Table
County Unknown/Missing
FY 2008-09 FY 2009-10
.Alameda
.Butte 10.5% (6) 10.2% (5)
.Contra Costa 5.0% (7) 4.2% (9)
.Fresno 7.9% (10) 9.4% (33)
.Kern 3.6% (11) 2.7% (7)
.Los Angeles 1.0% (28) 1.1% (41)
.Marin
.Merced 0.0% (0) 0.0% (0)
.Monterey
.Orange 3.6% (23) 7.2% (53)
.Placer 19.8% (16) 30.5% (18)
.Riverside
.Sacramento 0.6% (2) 3.6% (35)
.San Bernardino 4.1% (16) 2.3% (8)
.San Diego 9.2% (51) 4.7% (66)
.San Francisco 13.7% (47) 18.7% (79)
.San Joaquin 0.7% (2) 0.5% (4)
.San Luis Obispo 4.3% (3) 5.3% (6)
.San Mateo 5.8% (3) 15.1% (8)
.Santa Barbara
.Santa Clara 34.3% (91) 42.8% (148)
.Santa Cruz 5.2% (5) 4.3% (2)
.Solano 5.5% (6) 5.4% (8)
.Sonoma 3.4% (6) 4.7% (13)
.Stanislaus 0.4% (1) 1.3% (3)
.Tulare 0.0% (0) 0.7% (1)
.Ventura 9.4% (17) 2.9% (25)
.Yolo 2.1% (2) 2.8% (3)
Small Counties 4.2% (34) 4.5% (57)
Total 4.6% (387) 4.8% (632)
Black shading indicates where data was unavailable to calculate an indicator.
71
Table 8-3 - FSP access to a primary care physician by age group and county
Children TAY Adults Older Adults
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10 FY 08-09 FY 09-10
.Alameda
.Butte 7.0% (4) 6.1% (3) 14.0% (8) 16.3% (8) 77.2% (44) 69.4% (34) 1.8% (1) 8.2% (4)
.Contra Costa 25.0% (35) 31.6% (67) 22.1% (31) 18.4% (39) 52.1% (73) 45.3% (96) 0.7% (1) 4.7% (10)
.Fresno 16.7% (21) 30.0% (105) 16.7% (21) 23.7% (83) 63.5% (80) 44.6% (156) 3.2% (4) 1.7% (6)
.Kern 2.9% (9) 6.1% (16) 15.7% (48) 15.7% (41) 62.4% (191) 55.2% (144) 19.0% (58) 23.0% (60)
.Los Angeles 43.7% (1,221) 43.8% (1,649) 10.5% (293) 11.8% (445) 41.0% (1,145) 39.0% (1,468) 4.8% (135) 5.3% (201)
.Marin
.Merced 37.7% (26) 39.3% (33) 30.4% (21) 27.4% (23) 31.9% (22) 32.1% (27) 0.0% (0) 1.2% (1)
.Monterey
.Orange 21.8% (139) 19.0% (140) 20.7% (132) 18.3% (135) 46.2% (294) 50.3% (371) 11.3% (72) 12.3% (91)
.Placer 17.3% (14) 5.1% (3) 16.0% (13) 27.1% (16) 45.7% (37) 61.0% (36) 21.0% (17) 6.8% (4)
.Riverside
.Sacramento 20.2% (72) 7.2% (70) 5.6% (20) 5.9% (57) 46.2% (165) 69.5% (675) 28.0% (100) 17.4% (169)
.San Bernardino 21.7% (84) 8.4% (29) 25.3% (98) 16.7% (58) 49.1% (190) 70.0% (243) 3.9% (15) 4.9% (17)
.San Diego 27.3% (152) 29.3% (407) 18.7% (104) 17.7% (246) 41.7% (232) 45.5% (633) 12.2% (68) 7.5% (105)
.San Francisco 27.9% (96) 24.9% (105) 16.9% (58) 25.4% (107) 43.6% (150) 38.9% (164) 11.6% (40) 10.9% (46)
.San Joaquin 4.6% (13) 3.8% (31) 11.0% (31) 12.8% (104) 65.0% (184) 69.1% (560) 19.4% (55) 14.3% (116)
.San Luis Obispo 23.2% (16) 38.9% (44) 20.3% (14) 20.4% (23) 52.2% (36) 31.0% (35) 4.3% (3) 9.7% (11)
.San Mateo 28.8% (15) 43.4% (23) 71.2% (37) 56.6% (30) 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
.Santa Barbara
.Santa Clara 17.0% (45) 19.1% (66) 19.2% (51) 24.3% (84) 55.1% (146) 50.0% (173) 8.7% (23) 6.6% (23)
.Santa Cruz 0.0% (0) 0.0% (0) 41.7% (40) 58.7% (27) 22.9% (22) 0.0% (0) 35.4% (34) 41.3% (19)
.Solano 25.7% (28) 19.7% (29) 19.3% (21) 14.3% (21) 27.5% (30) 46.9% (69) 27.5% (30) 19.0% (28)
.Sonoma 24.1% (42) 19.2% (53) 20.1% (35) 14.1% (39) 53.4% (35) 47.8% (132) 2.3% (4) 18.8% (52)
.Stanislaus 7.5% (17) 7.9% (19) 14.0% (32) 15.8% (38) 63.6% (145) 62.1% (149) 14.9% (34) 14.2% (34)
.Tulare 3.5% (4) 6.5% (9) 25.7% (29) 33.3% (46) 69.0% (78) 58.7% (81) 1.8% (2) 1.4% (2)
.Ventura 12.8% (23) 1.1% (9) 16.7% (30) 13.2% (113) 8.9% (16) 575 (67.4%) 61.7% (111) 18.3% (156)
.Yolo 1.1% (1) 1.9% (2) 23.2% (22) 18.7% (20) 69.5% (66) 68.2% (73) 6.3% (6) 11.2% (12)
Small Counties 23.8% (195) 23.7% (303) 19.6% (160) 21.1% (269) 46.2% (378) 46.0% (587) 10.4% (85) 9.2% (117)
Total 27.3% (2,272) 24.6% (3,215) 16.2% (1,349) 15.9% (2,072) 45.8% (3,817) 49.7% (6,481) 10.8% (898) 9.8% (1,284)
Black shading indicates where data was unavailable to calculate an indicator.
72
Table 8-4 - FSP access to a primary care physician by gender and county
Female Male
County
FY 08-09 FY 09-10 FY 08-09 FY 09-10
.Alameda
.Butte 45.3% (24) 36.2% (17) 54.7% (29) 63.8% (30)
.Contra Costa 49.3% (69) 47.6% (101) 50.7% (71) 52.4% (111)
.Fresno 49.2% (59) 43.6% (143) 50.8% (61) 56.4% (185)
.Kern 60.5% (181) 54.7% (139) 39.5% (118) 45.3% (115)
.Los Angeles 43.3% (1,209) 44.9% (1,688) 56.7% (1,584) 55.1% (2,074)
.Marin
.Merced 44.9% (31) 42.9% (36) 55.1% (38) 57.1% (48)
.Monterey
.Orange 45.3% (287) 44.9% (318) 54.7% (346) 55.1% (391)
.Placer 46.9% (38) 33.9% (20) 53.1% (43) 66.1% (39)
.Riverside
.Sacramento 59.4% (212) 54.5% (512) 40.6% (145) 45.5% (428)
.San Bernardino 49.2% (189) 56.2% (195) 50.8% (195) 43.8% (152)
.San Diego 49.9% (257) 41.9% (568) 50.1% (258) 58.1% (787)
.San Francisco 31.4% (108) 32.8% (138) 68.6% (236) 67.2% (283)
.San Joaquin 65.7% (186) 56.2% (456) 34.3% (97) 43.8% (355)
.San Luis Obispo 43.5% (40) 51.3% (58) 56.5% (52) 48.7% (55)
.San Mateo 39.2% (20) 36.2% (17) 60.8% (31) 63.8% (30)
.Santa Barbara
.Santa Clara 49.5% (97) 43.0% (95) 50.5% (99) 57.0% (126)
.Santa Cruz 43.5% (40) 42.2% (19) 56.5% (52) 57.8% (26)
.Solano 44.7% (46) 43.6% (61) 55.3% (57) 56.4% (79)
.Sonoma 40.1% (69) 42.8% (116) 59.9% (103) 57.2% (155)
.Stanislaus 61.4% (140) 59.6% (143) 38.6% (88) 40.4% (97)
.Tulare 50.4% (57) 50.7% (70) 49.6% (56) 49.3% (68)
.Ventura 61.1% (102) 43.4% (367) 38.9% (65) 56.6% (478)
.Yolo 63.2% (60) 57.0% (61) 36.8% (35) 43.0% (46)
Small Counties 48.9% (390) 47.0% (588) 51.1% (408) 53.0% (663)
Total 47.8% (3,901) 46.5% (5,926) 52.2% (4,254) 53.5% (6,821)
Black shading indicates where data was unavailable to calculate an indicator.
73
Table 8-5 - Missing data
Unknown/Other
County
FY 2008-09 FY 2009-10
.Alameda
.Butte 7.0% (4) 4.1% (2)
.Contra Costa 0.0% (0) 0.0% (0)
.Fresno 4.8% (6) 6.3% (22)
.Kern 2.3% (7) 2.7% (7)
.Los Angeles 0.0% (1) 0.0% (1)
.Marin
.Merced 0.0% (0) 0.0% (0)
.Monterey
.Orange 0.6% (4) 3.8% (28)
.Placer 0.0% (0) 0.0% (0)
.Riverside
.Sacramento 0.0% (0) 3.2% (31)
.San Bernardino 0.8% (3) 0.0% (0)
.San Diego 7.4% (41) 2.6% (36)
.San Francisco 0.0% (0) 0.2% (1)
.San Joaquin 0.0% (0) 0.0% (0)
.San Luis Obispo 0.0% (0) 0.0% (0)
.San Mateo 1.9% (1) 11.3% (23)
.Santa Barbara
.Santa Clara 26.0% (69) 36.1% (125)
.Santa Cruz 4.2% (4) 2.2% (1)
.Solano 5.5% (6) 4.8% (7)
.Sonoma 1.1% (2) 1.8% (5)
.Stanislaus 0.0% (0) 0.0% (0)
.Tulare 0.0% (0) 0.0% (0)
.Ventura 7.2% (13) 0.9% (8)
.Yolo 0.0% (0) 0.0% (0)
Small Counties 2.4% (20) 2.0% (25)
Total 2.2% (181) 2.3% (305)
Black shading indicates where data was unavailable to calculate an indicator.
74
Priority Indicator 9: Perceptions of Access to Services
Table 9-1 - Perceptions of access to services by age group and county, FY 2008-091
Each cell contains the mean accompanied by the n in parentheses.
County Children TAY Adults Older Adults
.Alameda 4.39 (1,062) 3.87 (903) 4.17 (1,968) 4.19 (188)
.Butte 4.41 (806) 4.14 (409) 4.15 (504) 4.10 (31)
.Contra Costa 4.41 (382) 4.11 (415) 4.11 (6590 4.07 (35)
.Fresno 4.01 (783) 3.84 (498 4.13 (536) 4.45 (62)
.Kern 4.29 (591) 4.01 (549) 4.22 (1,112) 4.28 (104)
.Los Angeles 4.33 (11,102) 3.94 (6,741) 4.18 (12,726) 4.18 (974)
.Marin 4.11 (86) 3.90 (259) 4.24 (593) 4.15 (78)
.Merced 4.36 (22) 3.97 (33) 4.03 (414) 4.55 (16)
.Monterey 4.33 (161) 3.68 (331) 4.11 (546) 4.22 (50)
.Orange 4.32 (1,900) 4.01 (1,195) 4.26 (1,769) 4.23 (186)
.Placer 4.15 (229) 4.92 (2)
.Riverside 4.36 (798) 3.99 (623) 4.21 (1,461) 4.30 (343)
.Sacramento 4.36 (3,618) 4.09 (2,184) 4.08 (2,811) 4.24 (286)
.San Bernardino 4.38 (1,446) 4.11 (1,151) 4.21 (2,045) 4.34 (120)
.San Diego 4.43 (5,067) 4.01 (3,142) 4.26 (3,245) 4.35 (430)
.San Francisco 4.40 (1,178) 4.13 (724) 4.29 (4,575) 4.37 (833)
.San Joaquin 4.23 (153) 4.06 (112) 4.00 (649) 4.09 (45)
.San Luis Obispo 4.31 (98) 4.00 (57) 4.34 (398) 4.43 (13)
.San Mateo 3.62 (341) 3.90 (417) 4.33 (675) 4.61 (92)
.Santa Barbara 4.43 (104) 3.60 (82) 4.18 (185) 4.67 (2)
.Santa Clara 4.46 (2,079) 4.05 (1,348) 4.19 (2,701) 4.27 (291)
.Santa Cruz 4.47 (270) 4.17 (235) 4.22 (399) 4.15 (10)
.Solano 4.48 (237) 4.04 (180) 4.04 (224) 4.05 (16)
.Sonoma 4.20 (152) 4.05 (175) 4.25 (459) 4.34 (28)
.Stanislaus 4.37 (1,210) 4.03 (553) 4.18 (689) 4.59 (19)
.Tulare 4.30 (306) 4.08 (168) 3.95 (798) 4.21 (43)
.Ventura 4.35 (561) 4.06 (524) 4.15 (835) 4.34 (82)
.Yolo 4.61 (44) 4.02 (41) 3.90 (190) 4.44 (6)
Small Counties 4.31 (1,735) 4.06 (1,176) 4.10 (4,483) 4.26 (388)
Total 4.35 (36,292) 4.00 (24,225) 4.18 (47,878) 4.28 (4,773)
1 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
75
Table 9-2 - Family Member/Caregiver: Perceptions of access to services by race/ethnicity and county, FY 2008-092
Each cell contains the mean accompanied by the n in parentheses.
County White Hispanic / Latino Asian Pacific Islander Black American Indian Other
.Alameda 4.41 (791) 4.44 (384) 4.41 (43) 4.48 (22) 4.40 (679) 4.31 (57) 4.40 (156)
.Butte 4.40 (590) 4.49 (177) 4.60 (15) 4.42 (6) 4.32 (60) 4.44 (106) 4.37 (92)
.Contra Costa 4.34 (110) 4.51 (137) 4.44 (25) 4.50 (7) 4.44 (144) 4.21 (24) 4.56 (54)
.Fresno 4.05 (232) 4.01 (400) 3.89 (14) 2.83 (9) 3.96 (131) 3.84 (38) 4.10 (166)
.Kern 4.23 (287) 4.36 (247) 4.50 (2) 4.50 (3) 4.17 (69) 4.16 (37) 4.36 (106)
.Los Angeles 4.33 (2,433) 4.38 (6,428) 4.29 (234) 4.34 (73) 4.31 (2,117) 4.27 (307) 4.37 (2,619)
.Marin 3.84 (44) 4.58 (30) 4.50 (4) 3.67 (3) 4.25 (8) 4.43 (14)
.Merced 4.19 (8) 4.38 (12) 5.00 (1) 4.00 (1) 4.00 (1) 4.00 (2) 5.00 (1)
.Monterey 4.28 (62) 4.31 (103) 4.67 (6) 3.83 (3) 4.31 (16) 4.50 (9) 4.41 (33)
.Orange 4.30 (755) 4.31 (1,072) 4.03 (78) 4.13 (31) 4.42 (90) 4.11 (81) 4.37 (380)
.Placer
.Riverside 4.33 (325) 4.39 (411) 4.36 (7) 4.50 (5) 4.39 (97) 4.33 (18) 4.41 (167)
.Sacramento 4.35 (1,776) 4.43 (1,099) 4.39 (138) 4.40 (67) 4.40 (1,074) 4.33 (273) 4.42 (516)
.San Bernardino 4.45 (586) 4.36 (654) 4.61 (18) 4.50 (7) 4.40 (275) 4.42 (65) 4.31 (335)
.San Diego 4.42 (1,831) 4.47 (2,877) 4.33 (130) 4.45 (75) 4.38 (661) 4.29 (203) 4.49 (1,113)
.San Francisco 4.46 (193) 4.51 (354) 4.36 (281) 4.50 (37) 4.34 (374) 4.45 (42) 4.52 (200)
.San Joaquin 4.27 (66) 4.29 (63) 4.50 (1) 4.33 (3) 4.23 (24) 3.79 (12) 4.38 (28)
.San Luis Obispo 4.33 (64) 4.29 (17) 4.20 (5) 5.00 (1) 4.25 (12) 4.25 (8) 4.13 (12)
.San Mateo 4.37 (107) 2.78 (162) 4.88 (8) 4.45 (20) 4.33 (39) 4.50 (1) 2.80 (154)
.Santa Barbara 4.60 (40) 4.46 (67) 5.00 (1) 3.88 (4) 4.54 (13) 4.29 (12)
.Santa Clara 4.40 (682) 4.49 (1,209) 4.34 (144) 4.17 (38) 4.44 (223) 4.45 (112) 4.49 (553)
.Santa Cruz 4.50 (119) 4.47 (148) 4.08 (6) 4.79 (7) 4.18 (14) 4.36 (11) 4.45 (53)
.Solano 4.50 (116) 4.56 (87) 4.22 (9) 4.64 (7) 4.42 (75) 4.42 (19) 4.65 (52)
.Sonoma 4.23 (111) 4.16 (54) 3.63 (4) 4.00 (3) 4.10 (10) 4.47 (17) 4.17 (134)
.Stanislaus 4.41 (708) 4.37 (548) 4.62 (17) 4.24 (19) 4.18 (79) 4.43 (53) 4.35 (281)
.Tulare 4.32 (153) 4.27 (152) 4.25 (2) 4.00 (3) 4.17 (9) 4.33 (18) 4.26 (51)
.Ventura 4.38 (221) 4.39 (73) 4.10 (5) 4.50 (5) 4.30 (30) 4.41 (27) 4.42 (100)
.Yolo 4.67 (26) 4.63 (19) 4.25 (4) 5.00 (4) 4.65 (10)
Small Counties 4.35 (1,119) 4.32 (547) 4.23 (13) 4.33 (21) 4.29 (99) 4.37 (185) 4.29 (236)
2 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
76
Table 9-3 - TAY: Perceptions of access to services by race/ethnicity and county, FY 2008-093
Each cell contains the mean accompanied by the n in parentheses.
Hispanic / Pacific American
White Asian Black Other
County Latino Islander Indian
.Alameda 3.88 (211) 4.00 (227) 3.81 (62) 4.01 (36) 3.95 (400) 3.56 (61) 3.87 (174)
.Butte 4.12 (281) 4.23 (67) 3.50 (6) 3.86 (7) 4.14 (32) 4.11 (57) 4.06 (62)
.Contra Costa 4.01 (118) 4.19 (125) 4.25 (20) 4.00 (12) 4.12 (170) 3.80 (38) 4.03 (73)
.Fresno 3.89 (101) 3.87 (266) 3.95 (31) 3.88 (4) 3.92 (63) 4.07 (30) 3.77 (153)
.Kern 4.08 (220) 4.07 (230) 4.20 (5) 4.00 (7) 3.83 (56) 4.03 (44) 4.01 (129)
.Los Angeles 4.02 (1,325) 4.00 (3,521) 3.90 (173) 3.81 (84) 3.89 (1,477) 3.96 (317) 3.97 (2,071)
.Marin 3.93 (141) 3.96 (71) 3.47 (17) 1.25 (2) 3.97 (32) 3.32 (19) 3.74 (49)
.Merced 3.83 (12) 3.79 (12) 3.75 (2) 5.00 (1) 4.67 (3) 3.00 (5)
.Monterey 4.01 (77) 3.63 (209) 4.00 (9) 4.00 (6) 3.65 (24) 3.88 (12) 3.75 (102)
.Orange 4.01 (444) 4.04 (638) 3.72 (59) 3.85 (31) 4.04 (60) 4.04 (66) 3.99 (320)
.Placer
.Riverside 4.01 (208) 4.10 (304) 3.75 (10) 3.93 (7) 3.92 (79) 4.07 (23) 4.09 (162)
.Sacramento 4.14 (980) 4.17 (578) 4.00 (105) 4.07 (48) 4.03 (641) 4.14 (251) 4.03 (391)
.San Bernardino 4.19 (474) 4.13 (471) 3.78 (18) 3.94 (9) 4.06 (200) 4.10 (96) 4.00 (263)
.San Diego 4.02 (1,033) 4.09 (1,588) 3.88 (118) 4.14 (74) 3.87 (475) 3.97 (233) 4.07 (767)
.San Francisco 4.18 (92) 4.16 (191) 4.05 (159) 4.28 (30) 4.17 (267) 4.19 (26) 4.16 (134)
.San Joaquin 4.25 (46) 4.03 (44) 4.00 (1) 3.33 (3) 4.19 (18) 4.15 (13) 3.98 (24)
.San Luis Obispo 4.24 (36) 4.58 (6) 5.00 (1) 4.00 (1) 4.00 (4) 3.69 (8) 4.63 (4)
.San Mateo 3.87 (104) 3.92 (183) 4.29 (14) 4.20 (43) 3.90 (46) 4.00 (3) 3.93 (174)
.Santa Barbara 3.97 (19) 3.69 (40) 3.63 (4) 3.38 (8) 2.92 (6) 3.54 (26)
.Santa Clara 4.03 (355) 4.08 (751) 3.93 (117) 4.01 (40) 4.11 (167) 4.00 (114) 4.04 (430)
.Santa Cruz 4.14 (91) 4.19 (126) 4.38 (4) 4.50 (4) 4.09 (17) 4.09 (22) 4.24 (82)
.Solano 4.07 (88) 4.11 (40) 3.21 (12) 3.50 (3) 4.04 (57) 4.05 (20) 4.14 (32)
.Sonoma 4.09 (117) 4.07 (49) 3.86 (11) 4.17 (3) 4.12 (13) 4.02 (24) 3.94 (44)
.Stanislaus 4.10 (269) 3.95 (255) 4.18 (11) 4.63 (8) 4.08 (37) 4.06 (40) 4.00 (180)
.Tulare 4.13 (64) 4.20 (79) 4.00 (4) 4.17 (3) 3.91 (11) 4.12 (13) 4.09 (38)
.Ventura 4.10 (219) 4.05 (234) 4.43 (7) 4.00 (14) 3.96 (40) 4.16 (31) 4.06 (131)
.Yolo 3.95 (22) 4.17 (15) 4.00 (2) 4.38 (4) 4.50 (4) 4.13 (4)
Small Counties 4.12 (635) 3.98 (388) 4.11 (22) 3.94 (8) 3.97 (64) 4.05 (174) 3.98 (232)
3 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
77
Table 9-4 - Adult: Perceptions of access to services by race/ethnicity and county, FY 2008-094
Each cell contains the mean accompanied by the n in parentheses.
Hispanic / Pacific American
White Asian Black Other
County Latino Islander Indian
Alameda 4.14 (700) 4.31 (1,273) 4.19 (238) 4.08 (59) 4.18 (612) 4.08 (110) 4.27 (229)
Butte 4.13 (378) 4.16 (59) 4.37 (16) 3.87 (5) 3.78 (14) 4.14 (44) 4.22 (35)
Contra Costa 4.12 (267) 4.22 (138) 4.22 (48) 4.44 (12) 4.08 (146) 4.11 (40) 4.04 (68)
Fresno 4.08 (184) 4.16 (196) 4.14 (30) 3.51 (6) 4.22 (58) 4.22 (24) 4.29 (1270
Kern 4.20 (637) 4.32 (359) 3.95 (13) 4.13 (13) 4.08 (77) 4.12 (74) 4.26 (204)
Los Angeles 4.20 (3,480) 4.31 (3,769) 4.07 (736) 4.18 (163) 4.24 (2,740) 4.11 (605) 4.29 (2,130)
Marin 4.23 (441) 4.16 (49) 4.15 (19) 4.14 (11) 4.22 (34) 4.26 (45) 4.09 (54)
Merced 4.06 (153) 4.02 (129) 4.44 (20) 4.55 (8) 4.17 (41) 3.86 (39) 3.99 (72)
Monterey 4.16 (242) 4.12 (201) 4.22 (22) 4.06 (6) 4.01 (46) 3.81 (39) 3.99 (116)
Orange 4.27 (893) 4.32 (445) 4.22 (210) 4.48 (22) 4.28 (79) 4.39 (62) 4.30 (264)
Placer 4.14 (168) 4.24 (24) 4.67 (3) 4.83 (3) 4.33 (5) 4.34 (17) 4.18 (15)
Riverside 4.22 (766) 4.31 (432) 4.07 (25) 4.12 (17) 4.17 (164) 4.10 (60) 4.20 (252)
Sacramento 4.03 (1,321) 4.12 (398) 4.14 (219) 4.05 (49) 4.21 (546) 4.13 (196) 4.13 (287)
San Bernardino 4.24 (974) 4.24 (581) 4.40 (32) 4.15 (16) 4.29 (248) 4.19 (117) 4.20 (280)
San Diego 4.23 (1,662) 4.36 (901) 4.27 (177) 4.25 (56) 4.24 (366) 4.29 (150) 4.31 (534)
San Francisco 4.29 (850) 4.38 (695) 4.33 (756) 4.25 (1,099) 4.30 (678) 4.29 (156) 4.37 (501)
San Joaquin 3.94 (279) 4.00 (129) 4.05 (39) 4.49 (13) 3.94 (59) 3.91 (61) 3.78 (80)
San Luis Obispo 4.35 (311) 4.29 (48) 4.50 (8) 4.17 (2) 4.39 (15) 4.26 (32) 4.23 (35)
San Mateo 4.28 (378) 4.42 (158) 4.16 (29) 4.31 (54) 4.38 (55) 4.34 (10) 4.45 (128)
Santa Barbara 4.13 (87) 4.17 (59) 4.50 (4) 4.00 (1) 4.00 (7) 4.23 (8) 4.52 (35)
Santa Clara 4.21 (1,222) 4.26 (651) 4.21 (292) 4.29 (54) 4.22 (218) 4.15 (156) 4.24 (379)
Santa Cruz 4.21 (267) 4.19 (86) 4.12 (13) 4.04 (4) 4.21 (12) 3.94 (28) 4.12 (58)
Solano 4.09 (104) 4.01 (42) 4.28 (21) 3.82 (7) 4.05 (61) 4.07 (23) 3.95 (23)
Sonoma 4.25 (352) 4.47 (64) 3.83 (10) 4.61 (6) 4.38 (18) 4.28 (27) 4.13 (42)
Stanislaus 4.18 (431) 4.19 (151) 4.45 (26) 4.39 (13) 4.16 (34) 4.23 (51) 4.10 (87)
Tulare 3.99 (338) 4.15 (221) 4.14 (17) 4.23 (4) 4.06 (28) 4.04 (38) 4.18 (117)
Ventura 4.13 (516) 4.21 (208) 4.13 (13) 4.18 (13) 4.13 (29) 4.09 (37) 4.22 (130)
Yolo 3.84 (107) 4.07 (39) 4.06 (10) 3.50 (1) 3.66 (16) 3.93 (14) 4.05 (28)
Small Counties 4.15 (2,682) 4.21 (860) 4.21 (87) 4.20 (35) 4.14 (221) 4.12 (371) 4.14 (490)
4 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
78
Table 9-5 - Older Adult: Perceptions of access to services by race/ethnicity and county, FY 2008-095
Each cell contains the mean accompanied by the n in parentheses.
White Hispanic / Asian Pacific Black American Other
County Latino Islander Indian
Alameda 4.26 (86) 4.44 (18) 3.86 (177) 4.25 (1) 4.16 (54) 4.36 (10) 4.27 (13)
Butte 3.95 (25) 5.00 (1) 4.15 (5) 4.75 (2)
Contra Costa 4.12 (20) 3.60 (1) 4.01 (6) 4.04 (4) 4.50 (2)
Fresno 4.54 (40) 4.29 (12) 5.00 (3) 4.24 (6) 4.67 (2) 4.94 (3)
Kern 4.15 (56) 4.37 (30) 3.50 (1) 4.39 (7) 4.06 (6) 4.22 (14)
Los Angeles 4.28 (304) 4.43 (245) 4.36 (62) 2.72 (6) 4.29 (124) 4.18 (2) 4.42 (121)
Marin 4.04 (56) 4.60 (7) 4.25 (4) 3.00 (1) 4.23 (5)
Merced 4.52 (7) 4.92 (4) 4.20 (2) 4.67 (1) 4.83 (2)
Monterey 4.19 (31) 4.44 (9) 5.00 (1) 4.75 (4) 4.54 (4)
Orange 4.24 (90) 4.33 (43) 4.12 (22 5.00 (1) 4.08 (12) 4.75 (4) 4.44 (30)
Placer 4.92 (2)
Riverside 4.33 (207) 4.38 (82) 4.61 (3) 4.16 (29) 4.13 (13) 4.22 (43)
Sacramento 4.34 (154) 4.32 (19) 4.31 (23) 4.67 (1) 4.20 (39) 4.19 (15) 4.06 (20)
San Bernardino 4.24 (69) 4.51 (25) 3.92 (4) 4.60 (11) 4.17 (14) 4.56 (10)
San Diego 4.24 (211) 4.47 (142) 4.48 (18) 4.75 (2) 4.46 (34) 4.55 (11) 4.49 (62)
San Francisco 4.39 (369) 4.48 (96) 4.34 (125) 4.20 (9) 4.36 (101) 4.23 (31) 4.41 (69)
San Joaquin 3.91 (25) 4.29 (7) 5.00 (2) 3.50 (2) 4.33 (3) 4.53 (5)
San Luis Obispo 4.37 (11) 5.00 (1) 4.50 (1)
San Mateo 4.63 (61) 4.61 (17) 4.50 (2) 4.45 (11) 4.60 (3) 4.15 (2) 4.53 (6)
Santa Barbara 4.33 (1) 5.00 (1) 5.00 (1)
Santa Clara 4.23 (170) 4.47 (48) 4.32 (34) 4.75 (2) 4.27 (14) 3.98 (7) 4.54 (23)
Santa Cruz 4.17 (7) 4.00 (1) 4.17 (2) 4.17 (2)
Solano 4.06 (8) 3.50 (2) 4.00 (1) 3.87 (4) 5.00 (1) 4.33 (1)
Sonoma 4.38 (26) 5.00 (1)
Stanislaus 4.66 (15) 4.33 (1) 5.00 (1) 4.50 (1)
Tulare 4.21 (19) 4.35 (16) 4.83 (1) 4.16 (3) 4.14 (6) 3.95 (7)
Ventura 4.25 (50) 4.59 (25) 4.44 (3) 4.33 (3) 4.46 (4) 4.58 (4) 4.01 (7)
Yolo 4.46 (4) 4.00 (1) 4.80 (1)
Small Counties 4.26 (257) 4.51 (50) 4.50 (4) 3.38 (4) 4.18 (13) 4.29 (20) 4.28 (18)
5 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
79
Table 9-6 - Race/Ethnicity - Missing and Unknown Data
Family Member/
County TAY Adult Older Adults
Caregiver
.Alameda 7.6% (161) 19.9% (233) 12.0% (387) 11.1% (40)
.Butte 10.5% (110) 20.3% (104) 19.4% (107) 93.9% (31)
.Contra Costa 9.4% (47) 14.9% (83) 19.1% (137) 42.4% (14)
.Fresno 14.0% (139) 16.0% (104) 5.5% (98) 15.2% (10)
.Kern 14.9% (112) 18.5% (128) 11.4% (157) 15.8% (18)
.Los Angeles 11.4% (1,627) 14.5% (1,303) 20.8% (2,830) 34.7% (300)
.Marin 12.6% (13) 13.3% (44) 15.3% (100) 20.5% (15)
.Merced 11.5% (3) 28.6% (10) 21.9% (101) 31.3% (5)
.Monterey 7.8% (18) 13.7% (60) 12.4% (83) 20.4% (10)
.Orange 9.6% (238) 10.9% (176) 17.8% (352) 16.3% (33)
.Placer 0.0% (0) 0.0% (0) 22.6% (53) 50.0% (1)
.Riverside 9.6% (99) 16.5% (131) 14.5% (248) 13.3% (50)
.Sacramento 11.8% (582) 18.3% (547) 23.1% (698) 28.0% (76)
.San Bernardino 13.6% (264) 15.0% (230) 20.6% (464) 23.3% (31)
.San Diego 6.0% (413) 11.6% (499) 13.7% (527) 18.3% (88)
.San Francisco 13.0% (193) 14.7% (132) 33.2% (1,290) 32.0% (256)
.San Joaquin 14.2% (28) 18.8% (28) 32.0% (211) 34.1% (15)
.San Luis Obispo 14.3% (17) 31.7% (19) 16.2% (73) 15.4% (2)
.San Mateo 5.9% (29) 10.2% (58) 21.4% (174) 33.3% (34)
.Santa Barbara 8.8% (12) 29.1% (30) 20.4% (41) 0.0% (0)
.Santa Clara 10.0% (295) 10.6% (209) 20.6% (613) 22.5% (67)
.Santa Cruz 7.3% (26) 9.0% (31) 12.2% (57) 16.7% (2)
.Solano 6.0% (22) 17.1% (43) 17.4% (49) 17.6% (3)
.Sonoma 2.7% (9) 6.5% (17) 13.9% (72) 3.7% (1)
.Stanislaus 4.1% (70) 9.3% (74) 15.0% (119) 22.2% (4)
.Tulare 14.4% (56) 17.9% (38) 35.3% (269) 15.4% (8)
.Ventura 15.8% (73) 15.8% (107) 16.7% (158) 13.5% (13)
.Yolo 7.9% (5) 9.8% (5) 14.9% (32) 0.0% (0)
Small Counties 12.6% (279) 16.9% (257) 21.6% (1,025) 25.1% (92)
Total 10.2% (4,940 14.5% (4,700 19.6% (10,525 24.7% (1,219
Black shading indicates where data was unavailable to calculate an indicator.
80
Table 9-7 - Perceptions of access to services by gender and county, FY 2008-096
Each cell contains the mean accompanied by the n in parentheses.
County Children TAY Adult Older Adult
Female Male Female Male Female Male Female Male
.Alameda 4.34 (303) 4.42 (690) 4.05 (316) 3.86 (486) 4.21 (775) 4.17 (1,055) 4.18 (83) 4.22 (85)
.Butte 4.36 (313) 4.43 (450) 4.24 (183) 4.06 (192) 4.15 (238) 4.14 (204) 4.42 (14) 3.69 (15)
.Contra Costa 4.54 (127) 4.36 (238) 4.21 (179) 4.07 (218) 4.12 (306) 4.09 (264) 4.11 (17) 4.10 (9)
.Fresno 3.94 (281) 4.05 (425) 3.84 (212) 3.85 (218) 4.15 (255) 4.18 (220) 4.50 (44) 4.60 (13)
.Kern 4.33 (213) 4.24 (340) 4.10 (238) 4.00 (261) 4.26 (629) 4.18 (417) 4.28 (75) 4.21 (23)
.Los Angeles 4.34 (4,054) 4.35 (6,221) 4.04 (2,957) 3.90 (3,143) 4.26 (6,210) 4.21 (4,212) 4.30 (479) 4.36 (265)
.Marin 4.13 (31) 4.10 (53) 4.00 (68) 3.90 (156) 4.25 (281) 4.24 (258) 4.06 (37) 4.18 (37)
.Merced 4.50 (6) 4.27 (13) 3.75 (12) 4.13 (12) 4.08 (178) 3.95 (171) 4.71 (8) 4.46 (6)
.Monterey 4.41 (63) 4.28 (88) 4.11 (94) 3.45 (199) 4.18 (267) 4.04 (235) 4.39 (23) 4.25 (18)
.Orange 4.33 (705) 4.33 (1,065) 4.09 (519) 3.94 (578) 4.30 (875) 4.25 (696) 4.25 (96) 4.25 (96)
.Placer 4.21 (107) 4.18 (93) 4.92 (2)
.Riverside 4.23 (231) 4.42 (515) 3.93 (206) 4.07 (344) 4.28 (749) 4.18 (587) 4.32 (219) 4.29 (105)
.Sacramento 4.35 (1,429) 4.40 (1,976) 4.15 (959) 4.07 (1,020) 4.09 (1,469) 4.09 (1,013) 4.29 (153) 4.25 (93)
.San Bernardino 4.41 (475) 4.38 (863) 4.20 (429) 4.06 (627) 4.25 (1,108) 4.23 (648) 4.32 (85) 4.35 (24)
.San Diego 4.44 (1,853) 4.43 (3,196) 4.09 (1,398) 3.94 (1,738) 4.30 (1,624) 4.24 (1,382) 4.40 (244) 4.29 (147)
.San Francisco 4.40 (404) 4.40 (684) 4.23 (316) 4.05 (345) 4.33 (1,661) 4.28 (2,127) 4.39 (350) 4.38 (344)
.San Joaquin 4.12 (62) 4.38 (78) 4.08 (59) 4.11 (41) 4.01 (266) 3.99 (231) 4.04 (29) 4.12 (11)
.San Luis Obispo 4.22 (32) 4.35 (51) 4.00 (22) 4.17 (24) 4.36 (208) 4.33 (161) 4.12 (5) 4.63 (8)
.San Mateo 3.45 (125) 3.72 (216) 3.97 (165) 3.85 (252) 4.40 (389) 4.23 (286) 4.66 (61) 4.52 (31)
.Santa Barbara 4.38 (46) 4.50 (52) 3.79 (24) 3.65 (41) 4.05 (85) 4.25 (72) 4.33 (1) 5.00 (1)
.Santa Clara 4.44 (735) 4.47 (1,213) 4.16 (523) 4.00 (713) 4.27 (1,245) 4.18 (1,158) 4.24 (161) 4.36 (93)
.Santa Cruz 4.49 (103) 4.42 (146) 4.31 (102) 4.07 (117) 4.30 (184) 4.14 (183) 4.17 (9) 4.00 (1)
.Solano 4.47 (89) 4.51 (141) 4.15 (66) 3.95 (99) 4.16 (95) 3.98 (111) 4.22 (6) 3.77 (8)
.Sonoma 4.24 (48) 4.18 (103) 4.12 (98) 3.97 (75) 4.32 (201) 4.21 (234) 4.50 (14) 4.31 (13)
.Stanislaus 4.41 (403) 4.36 (774) 4.11 (214) 4.00 (306) 4.22 (369) 4.15 (276) 4.61 (15) 5.00 (1)
.Tulare 4.23 (91) 4.34 (176) 4.26 (76) 3.95 (70) 4.08 (342) 4.05 (251) 4.24 (26) 4.14 (11)
.Ventura 4.32 (208) 4.37 (303) 4.15 (205) 4.00 (269) 4.15 (361) 4.14 (371) 4.44 (50) 4.33 (26)
.Yolo 4.69 (8) 4.63 (34) 4.29 (12) 3.92 (25) 4.03 (66) 3.79 (109) 4.53 (5) 4.00 (1)
Small Counties 4.34 (614) 4.33 (1,011) 4.16 (524) 3.98 (547) 4.18 (2,372) 4.13 (1,461) 4.33 (22) 4.18 (106)
6 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
81
Table 9-8 - Gender – Unknown/Missing Table
Family Member/ TAY Adult Older Adult
County Caregiver
.Alameda 6.8% (68) 12.6% (101) 7.5% (138) 11.9% (20)
.Butte 5.6% (43) 9.1% (34) 14.0% (62) 6.9% (2)
.Contra Costa 4.7% (17) 4.5% (18) 15.6% (89) 34.6% (9)
.Fresno 10.9% (77) 15.8% (68) 12.8% (61 8.8% (5
.Kern 6.9% (38) 0.6% (3) 6.3% (66) 6.1% (6)
.Los Angeles 0.8% (82) 10.5% (641) 0.0% (1,634) 25.7% (191)
.Marin 2.4% (2) 15.6% (35) 10.0% (54) 5.4% (4)
.Merced 15.8% (3) 37.5% (9) 18.6% (65) 14.3% (2)
.Monterey 0.0% (0) 13.0% (38) 8.8% (44) 22.0% (9)
.Orange 7.3% (130) 8.9% (98) 12.6% (198) 6.8% (13)
.Placer 64.5% (129) 0.0% (0)
.Riverside 0.0% (0) 13.3% (73) 9.4% (125) 5.9% (19)
.Sacramento 14.9% (213) 21.4% (205) 22.4% (329) 16.3% (40)
.San Bernardino 8.1% (108) 9.0% (95) 0.0% (289) 10.1% (11)
.San Diego 0.2% (8) 0.2% (6) 8.0% (239) 35.5% (139)
.San Francisco 8.3% (90) 9.5% (63) 20.9% (790) 20.0% (139)
.San Joaquin 9.3% (13) 12.0% (12) 30.6% (152) 12.5% (5)
.San Luis Obispo 18.1% (15) 43.5% (20) 7.9% (29) 0.0% (0)
.San Mateo 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
.Santa Barbara 58.2% (57) 26.2% (17) 17.8% (28) 0.0% (0)
.Santa Clara 6.7% (131) 9.1% (112) 12.4% (298) 14.6% (37)
.Santa Cruz 8.4% (21) 7.3% (16) 8.7% (32) 0.0% (0)
.Solano 3.0% (7) 9.1% (15) 8.7% (18) 14.3% (2)
.Sonoma 0.7% (1) 1.2% (2) 5.5% (24) 3.7% (1)
.Stanislaus 2.8% (33) 6.3% (33) 7.4% (48) 18.8% (3)
.Tulare 14.6% (39) 15.1% (22) 34.6% (205) 16.2% (6)
.Ventura 9.8% (50) 10.5% (50) 14.1% (103) 7.9% (6)
.Yolo 4.8% (2) 10.8% (4) 8.6% (15) 0.0% (0)
Small Counties 6.8% (110) 9.9% (106) 17.0% (650) 46.9% (60)
Total 4.2% (1,358) 8.9% (1,896) 21.0% (5,914) 18.6% (729)
Black shading indicates where data was unavailable to calculate an indicator.
82
Priority Indicator 10: Involuntary Status
Table 10-1 - Involuntary status per 10,000 consumers, FY 2008-09
14-day Additional 14-day 72-hours evaluation 72-hours evaluation
intensive intensive treatment and treatment - Adult and treatment - Child
County treatment (suicidal)
.Alameda 0.0 48.2 39.8 0.0
.Butte 0.0 0.0 11.5 1.2
.Contra Costa 0.0 30.2 6.5 0.0
.Fresno 0.0 0.0 6.2 0.1
.Kern 0.0 16.1 11.5 0.1
.Los Angeles 0.0 21.1 35.4 0.0
.Marin 0.0 20.9 10.8 0.0
.Merced 0.0 1.4 8.2 0.0
.Monterey 0.0 0.3 11.1 0.0
.Orange 0.0 10.3 12.7 0.0
.Placer 0.0 0.0 10.4 0.0
.Riverside 0.0 10.6 12.5 0.0
.Sacramento 0.0 59.5 17.0 0.6
.San Bernardino 0.0 32.8 9.2 0.6
.San Diego 0.0 20.6 11.4 0.0
.San Francisco 0.0 52.3 29.6 0.7
.San Joaquin 0.0 0.4 15.6 0.0
.San Luis Obispo 0.0 26.1 2.1 0.0
.San Mateo 0.0 5.0 35.0 0.5
.Santa Barbara 0.0 0.0 8.4 0.0
.Santa Clara 0.0 0.0 8.8 0.0
.Santa Cruz 0.0 0.0 16.3 0.1
.Solano 0.0 56.8 63.3 1.8
.Sonoma 0.0 0.0 0.0 0.0
.Stanislaus 0.0 0.0 28.0 0.1
.Tulare 0.0 0.0 6.0 0.0
.Ventura 0.0 21.9 17.9 0.1
.Yolo 0.0 0.0 5.0 0.0
Small Counties 193.7 37.1 57.9 0.7
Total 193.7 471.6 508.1 6.7
Black shading indicates where data was unavailable to calculate an indicator.
83
Priority Indicator 11: Consumer Perceptions of Improvement in Well-
Being as a Result of Services
Table 11-1 - Wellbeing by age group and county, FY 2008-097
Each cell contains the mean accompanied by the n in parentheses.
County Children TAY Adults Older Adults
.Alameda 3.99 (1,073) 3.89 (926) 3.94 (1,948) 3.92 (185)
.Butte 3.91 (799) 3.93 (410) 3.87 (488) 3.91 (30)
.Contra Costa 4.11 (381) 4.09 (420) 3.92 (650) 4.04 (34)
.Fresno 3.90 (797) 3.84 (517) 3.73 (521) 3.92 (60)
.Kern 3.83 (591) 3.88 (551) 3.81 (1,096) 3.86 (102)
.Los Angeles 3.92 (11,144) 3.88 (6,828) 3.77 (12,594) 3.82 (912)
.Marin 3.84 (86) 3.83 (260) 3.99 (584) 3.98 (77)
.Merced 3.95 (23) 3.80 (33) 3.76 (405) 3.86 (16)
.Monterey 4.07 (164) 3.88 (335) 3.96 (534) 4.05 (46)
.Orange 3.93 (23) 3.95 (1,197) 3.91 (1,709) 3.97 (178)
.Placer 3.83 (220) 4.54 (2)
.Riverside 3.93 (796) 3.94 (633) 3.87 (1,441) 3.89 (326)
.Sacramento 3.96 (3,614) 3.98 (2,186) 3.76 (2,715) 3.88 (270)
.San Bernardino 3.86 (1,457) 3.99 (1,164) 3.79 (1,988) 3.91 (118)
.San Diego 4.00 (5,085) 3.97 (3,181) 3.91 (3,193) 3.96 (424)
.San Francisco 4.03 (1,222) 3.99 (747) 3.92 (4,584) 3.93 (758)
.San Joaquin 3.66 (151) 3.80 (113) 3.84 (614) 4.01 (43)
.San Luis Obispo 3.89 (102) 3.88 (59) 3.91 (399) 4.05 (12)
.San Mateo 3.41 (340) 3.88 (419) 3.99 (661) 4.25 (89)
.Santa Barbara 3.91 (108) 3.79 (102) 3.95 (176) 4.57 (2)
.Santa Clara 4.01 (2,074) 3.96 (1,358) 3.92 (2,659) 3.94 (281)
.Santa Cruz 4.06 (271) 4.03 (238) 3.93 (393) 3.85 (10)
.Solano 4.02 (238) 3.92 (182) 3.92 (218) 3.82 (16)
.Sonoma 3.96 (151) 3.92 (175) 3.95 (456) 4.16 (28)
.Stanislaus 3.94 (1,201) 3.94 (554) 3.85 (670) 4.36 (18)
.Tulare 3.88 (302) 3.91 (174) 3.63 (725) 3.75 (37)
.Ventura 4.01 (559) 3.97 (526) 3.89 (814) 4.08 (82)
.Yolo 3.96 (44) 3.95 (41) 3.88 (189) 4.26 (6)
Small Counties 3.92 (1,746) 3.91 (1,192) 3.76 (4,368) 3.94 (361)
Total 3.94 (36,427) 3.93 (24,521) 3.84 (47,012) 3.84 (47,012)
7 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
84
Table 11-2 - Family Member/Caregiver: Wellbeing by race/ethnicity and county, FY 2008-098
Each cell contains the mean accompanied by the n in parentheses.
Hispanic / Pacific American
County White Asian Black Other
Latino Islander Indian
.Alameda 3.85 (270) 4.05 (384) 3.97 (43) 3.93 (22) 4.00 (384) 3.98 (57) 4.00 (157)
.Butte 3.88 (587) 3.97 (175) 3.96 (15) 3.89 (6) 3.71 (58) 3.95 (105) 3.89 (92)
.Contra Costa 4.06 (110) 4.21 (137) 4.22 (25) 3.94 (7) 4.04 (144) 4.01 (24) 4.26 (54)
.Fresno 3.96 (231) 3.92 (404) 3.57 (13) 3.75 (9) 3.82 (130) 3.81 (38) 3.91 (169)
.Kern 3.79 (289) 3.94 (248) 3.77 (2) 4.09 (3) 3.68 (68) 3.56 (37) 3.92 (105)
.Los Angeles 3.88 (2,443) 4.01 (6,440) 3.93 (233) 3.84 (76) 3.81 (2,120) 3.85 (306) 4.01 (2,630)
.Marin 3.85 (43) 4.11 (29) 3.82 (4) 4.04 (3) 3.84 (8) 4.02 (14)
.Merced 3.66 (8) 3.95 (12) 4.64 (1) 3.68 (2) 3.73 (1) 3.87 (2) 4.73 (1)
.Monterey 4.02 (63) 4.17 (105) 3.67 (6) 3.88 (3) 3.74 (16) 4.21 (10) 4.21 (35)
.Orange 3.90 (758) 3.98 (1,077) 3.84 (78) 3.96 (31) 3.85 (90) 3.79 (81) 3.91 (383)
.Placer
.Riverside 3.90 (324) 3.98 (412) 4.34 (7) 3.95 (5) 3.87 (97) 3.89 (17) 3.98 (165)
.Sacramento 3.93 (1,775) 4.03 (1,095) 4.01 (138) 4.07 (67) 3.96 (1,067) 3.96 (272) 4.04 (512)
.San Bernardino 3.90 (591) 3.85 (656) 3.98 (18) 4.03 (7) 3.82 (276) 3.82 (65) 3.75 (338)
.San Diego 3.93 (1,829) 4.08 (2,858) 3.94 (127) 3.99 (75) 3.89 (663) 3.90 (200) 4.05 (1,104)
.San Francisco 4.01 (191) 4.16 (364) 4.02 (284) 3.91 (37) 3.96 (395) 4.03 (42) 4.09 (206)
.San Joaquin 3.73 (66) 3.68 (62) 3.36 (1) 3.97 (3) 3.62 (24) 3.58 (12) 3.79 (28)
.San Luis Obispo 3.90 (67) 4.03 (17) 3.93 (5) 4.09 (1) 3.88 (12) 4.12 (8) 3.62 (12)
.San Mateo 3.96 (107) 2.79 (161) 4.02 (8) 4.05 (20) 3.95 (39) 3.00 (1) 2.77 (154)
.Santa Barbara 3.80 (41) 4.00 (69) 3.82 (1) 3.26 (5) 4.00 (13) 4.08 (12)
.Santa Clara 3.95 (679) 4.06 (1,207) 4.02 (145) 3.89 (38) 4.04 (222) 4.00 (110) 4.04 (553)
.Santa Cruz 4.06 (119) 4.12 (148) 3.99 (6) 4.01 (7) 3.67 (13) 4.19 (11) 4.10 (53)
.Solano 4.01 (115) 4.15 (87) 3.99 (9) 3.77 (7) 3.89 (74) 4.05 (19) 4.14 (52)
.Sonoma 3.96 (110) 3.93 (55) 3.23 (4) 4.34 (3) 3.87 (9) 4.00 (17) 3.81 (19)
.Stanislaus 3.92 (706) 3.99 (543) 3.95 (17) 4.18 (19) 3.75 (77) 3.97 (55) 3.99 (281)
.Tulare 3.90 (150) 3.90 (150) 4.27 (2) 4.40 (3) 3.58 (9) 4.17 (17) 3.95 (51)
.Ventura 3.99 (222) 4.01 (326) 3.73 (5) 4.36 (5) 3.76 (30) 3.88 (28) 3.97 (102)
.Yolo 4.08 (26) 3.92 (19) 3.89 (4) 4.13 (4) 3.48 (10)
Small Counties 3.90 (1,124) 3.98 (547) 3.82 (13) 3.93 (21) 3.86 (100) 3.97 (184) 4.00 (233)
8 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
85
Table 11-3 - TAY: Wellbeing by race/ethnicity and county, FY 2008-099
Each cell contains the mean accompanied by the n in parentheses.
White Hispanic / Asian Pacific Black American Other
County Latino Islander Indian
.Alameda 3.91 (213) 4.00 (230) 3.77 (64) 3.85 (35) 3.97 (404) 3.84 (63) 3.90 (178)
.Butte 3.92 (282) 4.00 (67) 3.14 (6) 3.63 (7) 3.77 (31) 3.80 (57) 3.96 (63)
.Contra Costa 4.05 (122) 4.07 (127) 4.08 (20) 3.93 (12) 4.17 (172) 3.92 (38) 3.91 (73)
.Fresno 3.82 (102) 3.91 (269) 3.97 (32) 3.60 (4) 3.77 (66) 3.77 (32) 3.89 (153)
.Kern 3.90 (222) 3.90 (231) 3.61 (5) 3.94 (7) 3.63 (56) 3.88 (44) 3.88 (129)
.Los Angeles 3.92 (1,334) 3.95 (3,550) 3.81 (179) 3.88 (85) 3.86 (1,496) 3.93 (321) 3.94 (2,085)
.Marin 3.81 (140) 3.75 (72) 3.72 (17) 2.36 (2) 3.97 (32) 3.66 (19) 3.69 (51)
.Merced 3.75 (12) 3.89 (12) 3.14 (2) 2.60 (1) 4.33 (3) 3.67 (5)
.Monterey 3.94 (77) 3.86 (213) 4.14 (10) 4.18 (6) 3.89 (25) 4.00 (13) 3.97 (103)
.Orange 3.92 (440) 4.01 (638) 3.93 (59) 3.85 (33) 3.93 (60) 3.93 (65) 3.95 (323)
.Placer
.Riverside 3.96 (211) 3.98 (310) 3.85 (10) 3.96 (7) 3.85 (81) 4.04 (24) 4.00 (165)
.Sacramento 4.00 (974) 3.99 (579) 4.00 (106) 3.71 (48) 3.94 (642) 4.03 (252) 3.95 (395)
.San Bernardino 4.06 (476) 4.03 (474) 3.87 (18) 3.73 (9) 3.95 (201) 4.05 (97) 3.93 (265)
.San Diego 3.97 (1,041) 4.01 (1,608) 4.00 (119) 3.94 (76) 3.93 (482) 3.95 (236) 3.98 (775)
.San Francisco 3.91 (96) 4.04 (194) 3.86 (161) 4.06 (30) 4.04 (271) 3.76 (30) 4.07 (140)
.San Joaquin 3.82 (46) 3.78 (44) 4.09 (1) 3.30 (3) 4.11 (20) 3.85 (13) 3.87 (24)
.San Luis Obispo 3.99 (36) 4.51 (6) 4.67 (1) 3.44 (1) 3.52 (4) 3.58 (8) 4.17 (5)
.San Mateo 3.95 (104) 3.83 (183) 4.13 (14) 4.12 (44) 3.91 (47) 4.12 (3) 3.80 (174)
.Santa Barbara 4.00 (21) 3.76 (49) 4.27 (4) 4.50 (1) 4.03 (9) 3.63 (7) 3.69 (35)
.Santa Clara 3.94 (357) 3.99 (754) 3.84 (115) 4.00 (40) 4.05 (167) 4.07 (115) 3.98 (432)
.Santa Cruz 4.04 (92) 4.02 (127) 4.05 (5) 3.86 (4) 3.88 (17) 4.04 (23) 3.98 (83)
.Solano 3.89 (89) 3.95 (40) 3.92 (12) 4.37 (3) 3.95 (58) 3.75 (20) 3.92 (32)
.Sonoma 3.94 (117) 3.94 (49) 3.82 (11) 4.07 (3) 4.18 (13) 4.05 (24) 3.81 (44)
.Stanislaus 3.99 (268) 3.95 (253) 3.70 (11) 4.44 (8) 3.84 (37) 3.88 (39) 3.96 (181)
.Tulare 3.93 (63) 3.90 (82) 3.59 (4) 3.45 (3) 3.84 (11) 3.85 (13) 4.00 (38)
.Ventura 4.01 (220) 4.01 (236) 3.96 (7) 3.84 (14) 3.75 (40) 4.07 (31) 4.05 (132)
.Yolo 3.89 (22) 4.08 (15) 3.82 (2) 4.09 (4) 4.16 (4) 3.16 (4)
Small Counties 3.95 (642) 3.89 (391) 3.92 (22) 3.58 (8) 3.91 (1,129) 3.92 (173) 3.86 (238)
9 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
86
Table 11-4 - Adult: Perceptions of access to services by race/ethnicity and county, FY 2008-0910
Each cell contains the mean accompanied by the n in parentheses.
White Hispanic / Asian Pacific Black American Other
County Latino Islander Indian
.Alameda 3.90 (697) 4.08 (309) 3.93 (237) 3.96 (59) 3.92 (610) 4.03 (110) 4.08 (228)
.Butte 3.85 (375) 3.80 (57) 3.89 (16) 4.11 (5) 3.85 (14) 3.65 (43) 3.81 (35)
.Contra Costa 3.92 (266) 4.05 (139) 4.02 (48) 3.97 (12) 3.83 (147) 3.93 (40) 3.97 (68)
.Fresno 3.66 (179) 3.90 (193) 3.58 (30) 3.22 (6) 3.67 (56) 3.70 (24) 3.79 (127)
.Kern 3.80 (632) 3.91 (355) 3.58 (13) 3.72 (13) 3.57 (77) 3.80 (73) 3.87 (201)
.Los Angeles 3.83 (3,460) 3.94 (3,763) 3.78 (747) 3.84 (162) 3.84 (2,738) 3.70 (633) 3.92 (2,123)
.Marin 3.97 (436) 3.76 (49) 4.00 (19) 4.02 (11) 4.12 (34) 3.81 (45) 4.00 (55)
.Merced 3.81 (151) 3.77 (129) 3.69 (20) 4.29 (8) 4.02 (41) 3.32 (38) 3.67 (72)
.Monterey 3.93 (240) 3.97 (201) 4.24 (22) 3.96 (6) 3.80 (46) 3.88 (39) 3.87 (115)
.Orange 3.90 (879) 4.03 (445) 3.89 (206) 3.94 (22) 4.00 (77) 3.96 (61) 4.02 (264)
.Placer 3.80 (167) 4.03 (24) 3.76 (3) 4.12 (3) 4.42 (4) 4.26 (17) 3.67 (15)
.Riverside 3.86 (758) 3.97 (432) 4.15 (26) 4.29 (19) 3.83 (162) 3.91 (61) 3.92 (253)
.Sacramento 3.73 (1,301) 3.78 (391) 3.81 (217) 3.86 (49) 3.86 (538) 3.86 (194) 3.77 (286)
.San Bernardino 3.76 (972) 3.85 (580) 3.92 (32) 3.66 (16) 3.84 (248) 3.79 (116) 3.83 (281)
.San Diego 3.86 (1,646) 4.06 (900) 3.98 (178) 3.99 (55) 3.81 (364) 3.95 (149) 3.99 (535)
.San Francisco 3.85 (856) 4.03 (696) 4.00 (771) 3.86 (1,108) 3.93 (683) 3.95 (154) 3.97 (504)
.San Joaquin 3.76 (279) 3.91 (129) 3.77 (39) 4.29 (13) 3.84 (58) 3.73 (61) 3.74 (79)
.San Luis Obispo 3.96 (310) 3.89 (48) 3.84 (8) 3.14 (2) 3.91 (15) 3.84 (32) 3.82 (35)
.San Mateo 3.97 (371) 4.09 (156) 3.89 (26) 4.03 (52) 3.83 (56) 3.56 (10) 4.11 (125)
.Santa Barbara 3.92 (84) 4.08 (58) 3.84 (4) 3.54 (1) 3.78 (7) 3.89 (8) 4.20 (32)
.Santa Clara 3.92 (1,217) 4.01 (647) 3.95 (282) 4.15 (54) 4.00 (218) 3.91 (155) 3.99 (380)
.Santa Cruz 3.91 (267) 3.90 (86) 3.78 (13) 4.07 (4) 4.11 (12) 3.76 (28) 3.80 (58)
.Solano 3.96 (103) 3.89 (42) 4.27 (20) 3.71 (7) 4.02 (60) 4.21 (23) 3.97 (23)
.Sonoma 3.97 (350) 4.19 (64) 3.42 (10) 4.30 (6) 3.97 (18) 4.00 (27) 3.71 (42)
.Stanislaus 3.88 (428) 3.92 (150) 4.08 (26) 4.21 (12) 3.67 (34) 3.80 (50) 3.85 (87)
.Tulare 3.61 (328) 3.73 (214) 3.78 (17) 3.58 (3) 3.45 (28) 3.47 (37) 3.74 (111)
.Ventura 3.84 (515) 3.96 (208) 3.73 (13) 4.13 (13) 4.01 (28) 3.84 (37) 3.96 (130)
.Yolo 3.78 (106) 4.10 (40) 3.90 (10) 3.36 (1) 3.93 (16) 4.20 (14) 4.10 (29)
Small Counties 3.80 (2,648) 3.89 (857) 3.93 (85) 4.13 (35) 3.79 (220) 3.82 (366) 3.83 (485)
10 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
87
Table 11-5 - Older Adult: Wellbeing by race/ethnicity and county, FY 2008-0911
Each cell contains the mean accompanied by the n in parentheses.
White Hispanic / Asian Pacific Black American Other
County Latino Islander Indian
.Alameda 3.98 (85) 4.29 (18) 3.60 (11) 3.23 (10 3.94 (54) 4.14 (10) 4.02 (13)
.Butte 3.84 (24) 4.07 (1) 4.14 (5) 4.11 (2)
.Contra Costa 4.06 (20) 2.79 (1) 3.94 (6) 3.75 (4) 4.33 (2)
.Fresno 3.97 (40) 3.70 (11) 4.19 (3) 3.34 (6) 3.96 (2) 3.95 (3)
.Kern 3.83 (56) 3.84 (29) 3.57 (1) 3.83 (7) 3.95 (6) 3.83 (14)
.Los Angeles 3.83 (297) 4.11 (241) 4.01 (61) 2.52 (6) 4.10 (122) 3.56 (20) 4.12 (120)
.Marin 3.87 (56) 4.35 (8) 3.63 (4) 3.25 (1) 3.78 (4)
.Merced 3.87 (7) 4.54 (4) 2.67 (2) 4.14 (1) 4.29 (2)
.Monterey 4.05 (30) 4.16 (8) 4.14 (2) 3.99 (4) 4.55 (3)
.Orange 3.96 (89) 4.09 (42) 3.98 (21) 5.00 (1) 3.65 (12) 4.30 (4) 4.02 (29)
.Placer 4.54 (2)
.Riverside 3.86 (199) 3.91 (80) 4.12 (3) 3.97 (30) 3.55 (13) 3.87 (44)
.Sacramento 3.91 (149) 3.92 (17) 3.83 (23) 3.00 (1) 3.98 (39) 3.92 (15) 3.58 (18)
.San Bernardino 3.86 (70) 4.15 (25) 3.55 (4) 4.13 (11) 3.77 (14) 4.34 (10)
.San Diego 3.79 (209) 4.14 (143) 4.10 (17) 4.82 (2) 3.92 (34) 3.97 (11) 4.20 (62)
.San Francisco 3.87 (358) 4.08 (88) 4.06 (117) 3.81 (9) 3.91 (93) 3.78 (30) 4.05 (64)
.San Joaquin 4.05 (25) 3.85 (7) 3.42 (2) 3.21 (2) 4.41 (3) 4.49 (5)
.San Luis Obispo 4.02 (10) 4.00 (1) 4.38 (1)
.San Mateo 4.26 (59) 4.48 (16) 3.50 (2) 4.18 (11) 4.50 (3) 3.73 (2) 4.30 (6)
.Santa Barbara 4.14 (1) 5.00 (1) 5.00 (1)
.Santa Clara 3.95 (167) 4.13 (48) 4.02 (34) 3.88 (2) 4.02 (14) 3.18 (7) 4.23 (23)
.Santa Cruz 3.85 (7) 4.00 (1) 3.79 (2) 3.25 (2)
.Solano 3.97 (8) 3.50 (2) 4.00 (1) 3.32 (4) 4.83 (1) 3.75 (1)
.Sonoma 4.13 (26) 5.00 (1)
.Stanislaus 4.35 (15) 3.54 (1) 5.00 (1) 3.64 (1)
.Tulare 3.74 (17) 3.80 (16) 3.75 (1) 4.14 (2) 3.38 (5) 3.67 (7)
.Ventura 4.00 (51) 4.36 (24) 4.33 (3) 4.28 (3) 4.43 (4) 4.58 (4) 3.87 (7)
.Yolo 4.56 (4) 3.93 (1) 3.38 (1)
Small Counties 3.96 (249) 4.19 (49) 3.72 (4) 3.41 (4) 3.62 (13) 3.85 (18) 3.90 (17)
11 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
88
Table 11-6 - Race/Ethnicity – Unknown/Missing Table
Family Member/
TAY Adults Older Adults
County Caregiver
.Alameda 13.0% (171) 21.0% (249) 16.6% (374) 18.9% (38)
.Butte 10.4% (108) 20.5% (105) 17.2% (94) 28.1% (9)
.Contra Costa 9.2% (46) 14.5% (82) 17.9% (129) 39.4% (13)
.Fresno 15.1% (150) 17.8% (117) 14.8% (91) 13.8% (9)
.Kern 14.8% (111) 18.3% (127) 11.0% (150) 15.0% (17)
.Los Angeles 11.0% (1,572) 14.8% (1,337) 24.9% (3,396) 28.3% (245)
.Marin 13.9% (14) 13.5% (45) 14.5% (94) 19.2% (14)
.Merced 15% (4) 29% (10) 20% (94) 31% (5)
.Monterey 8.0% (19) 13.0% (58) 11.1% (74) 14.9% (7)
.Orange 9.5% (238) 11.0% (178) 16.0% (312) 14.1% (28)
.Placer 19.3% (45) 50.0% (1)
.Riverside 9.5% (98) 16.3% (132) 14.0% (239) 11.4% (42)
.Sacramento 11.8% (580) 18.4% (552) 21.1% (628) 24.4% (64)
.San Bernardino 13.5% (263) 15.4% (237) 18.3% (410) 20.9% (28)
.San Diego 6.6% (450) 11.7% (508) 12.9% (492) 17.8% (85)
.San Francisco 13.6% (206) 15.9% (147) 26.4% (1,262) 27.1% (206)
.San Joaquin 13.8% (27) 18.5% (28) 26.9% (177) 29.5% (13)
.San Luis Obispo 16.4% (20) 32.8% (20) 16.7% (75) 16.7% (2)
.San Mateo 5.9% (29 10.2% (58 21.7% (173 33.3% (33
.Santa Barbara 9.9% (14) 32.5% (41) 19.6% (38) 0.0% (0)
.Santa Clara 9.9% (291) 10.8% (214) 19.6% (579) 20.0% (59)
.Santa Cruz 7.6% (27) 8.8% (31) 10.9% (51) 16.7% (2)
.Solano 6.6% (24) 17.3% (44) 16.5% (46) 17.6% (3)
.Sonoma 4.1% (9) 6.5% (17) 13.7% (71) 3.7% (1)
.Stanislaus 4.1% (70) 9.2% (73) 13.3% (105) 16.7% (3)
.Tulare 14.7% (56) 19.2% (41) 29.1% (215) 10.4% (5)
.Ventura 9.5% (68) 15.6% (106) 14.7% (139) 14.6% (14)
.Yolo 7.9% (5) 9.8% (5) 14.4% (31)
Small Counties 12.9% (287) 10.4% (270) 20.1% (944) 20.3% (72)
Black shading indicates where data was unavailable to calculate an indicator.
89
Table 11-7 - Perceptions of access to services by gender and county, FY 2008-0912
Each cell contains the mean accompanied by the n in parentheses.
County Children TAY Adult Older Adult
Female Male Female Male Female Male Female Male
.Alameda 3.98 (304) 4.00 (691) 3.94 (320) 3.93 (488) 3.96 (774) 3.94 (1,048) 3.93 (17) 3.93 (83)
.Butte 3.88 (311) 3.93 (447) 3.92 (185) 3.93 (192) 3.76 (235) 3.95 (203) 3.86 (13) 3.89 (15)
.Contra Costa 4.16 (127) 4.09 (238) 4.06 (181) 4.15 (22) 3.92 (305) 3.91 (263) 4.06 (17) 3.95 (9)
.Fresno 3.90 (281) 3.92 (427) 3.89 (216) 3.84 (222) 3.65 (252) 3.85 (214) 3.94 (44) 3.93 (13)
.Kern 3.80 (211) 3.83 (344) 3.85 (238) 3.93 (264) 3.77 (622) 3.88 (415) 3.87 (74) 3.75 (23)
.Los Angeles 3.96 (4,056) 3.94 (6,235) 3.91 (2,971) 3.93 (3,187) 3.85 (6,205) 3.90 (4,200) 3.93 (471) 4.01 (260)
.Marin 3.73 (30) 3.89 (52) 3.82 (68) 3.83 (156) 3.96 (278) 4.01 (258) 3.94 (38) 3.95 (36)
.Merced 3.86 (7) 3.94 (13) 3.97 (12) 3.68 (12) 3.72 (176) 3.76 (171) 3.98 (8) 3.80 (6)
.Monterey 4.10 (64) 4.06 (90) 3.98 (95) 3.81 (204) 3.99 (266) 3.92 (233) 4.16 922) 4.01 (17)
.Orange 3.96 (710) 3.90 (1,066) 3.94 (522) 3.98 (575) 3.95 (861) 3.91 (690) 4.02 (93) 3.91 (76)
.Placer 3.87 (107) 3.84 (91) 4.54 (2)
.Riverside 3.88 (228) 3.97 (516) 3.87 (210) 4.01 (349) 3.87 (740) 3.89 (586) 3.90 (213) 3.87 (100)
.Sacramento 3.95 (1,424) 3.98 (1,974) 3.93 (964) 4.04 (1,015) 3.74 (1,448) 3.78 (1,003) 3.89 (148) 3.92 (91)
.San Bernardino 3.85 (475) 3.86 (875) 3.99 (432) 4.00 (631) 3.76 (1,105) 3.86 (648) 3.87 985) 3.97 (25)
.San Diego 3.98 (1,863) 4.02 (3,204) 3.95 (1,412) 3.99 (1,764) 3.91 (1,612) 3.92 (1,377) 4.01 (242) 3.86 (146)
.San Francisco 4.05 (416) 4.02 (703) 4.00 (324) 4.00 (349) 3.91 (1,679) 3.92 (2,165) 3.91 (333) 3.96 (329)
.San Joaquin 3.63 (62) 3.72 (77) 3.73 (60) 3.88 (42) 3.80 (265) 3.81 (229) 4.04 (29) 3.91 (11)
.San Luis Obispo 3.92 (33) 3.80 (51) 3.92 (21) 3.96 (24) 3.86 (207) 4.03 (161) 3.85 (4) 4.14 (0)
.San Mateo 3.21 (125) 3.52 (215) 3.82 (166) 3.92 (253) 4.02 (382) 3.95 (279) 4.25 (60) 4.26 (29)
.Santa Barbara 3.77 (49) 3.99 (52) 3.84 (24) 3.83 (54) 3.79 (82) 4.09 (70) 4.14 (1) 5.00 (1)
.Santa Clara 4.02 (732) 4.04 (1,213) 3.96 (522) 3.99 (715) 3.94 (1,239) 3.96 (1,152) 3.91 (159) 4.08 (93)
.Santa Cruz 4.10 (104) 4.01 (146) 4.05 (104) 4.01 (118) 4.03 (184) 3.81 (183) 3.84 (9) 4.00 (1)
.Solano 4.07 (88) 4.03 (141) 3.85 (67) 3.95 (100) 3.91 (94) 4.01 (109) 3.91 (6) 3.61 (8_
.Sonoma 4.25 (48) 3.82 (102) 3.99 (98) 3.86 (75) 3.96 (200) 3.97 (233) 4.19 (14) 4.13 (13)
.Stanislaus 3.92 (396) 3.95 (773) 3.91 (212) 4.00 (309) 3.78 (367) 3.95 (273) 4.36 (15) 3.50 (1)
.Tulare 3.95 (90) 3.88 (173) 3.86 (76) 3.94 (73) 3.64 (331) 3.68 (244) 3.76 (26) 3.88 (8)
.Ventura 4.01 (207) 4.01 (306) 3.94 (206) 4.00 (271) 3.81 (359) 3.96 (369) 4.13 (50) 4.16 (26)
.Yolo 4.14 (8) 3.92 (34) 3.89 (12) 4.02 (25) 3.87 (65) 3.89 (110) 4.31 (5) 4.00 (1)
Small Counties 3.92 (618) 3.93 (1,013) 3.90 (530) 3.94 (551) 3.80 (2,346) 3.82 (1,449) 4.01 (216) 3.91 (102)
12 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
90
Table 11-8 - Gender – Unknown/Missing Tables
Family Member/ TAY Adults Older Adults
County Caregiver
.Alameda 7.8% (78) 14.6% (118) 6.9% (126) 18.0% (18)
.Butte 5.4% (41) 8.8% (33) 11.4% (50) 7.1% (2)
.Contra Costa 4.4% (16) 8.4% (17) 14.4% (82) 30.8% (8)
.Fresno 12.6% (89) 18.0% (79) 11.8% (55) 5.3% (3)
.Kern 6.5% (36) 9.8% (49) 5.7% (59) 5.2% (5)
.Los Angeles 8.3% (853) 10.9% (670) 21.0% (2,189) 24.8% (181)
.Marin 4.9% (4) 16.1% (36) 7.1% (38) 4.1% (3)
.Merced 15.0% (3) 37.5% (9) 16.7% (58) 14.3% (2)
.Monterey 6.5% (10) 12.0% (36) 7.0% (35) 17.9% (7)
.Orange 7.4% (132) 9.1% (100) 10.2% (158) 5.3% (9)
.Placer 11.1% (22) 0.0% (0)
.Riverside 7.0% (52) 13.2% (74) 8.7% (115) 4.2% (13)
.Sacramento 6.4% (216) 10.5% (207) 10.8% (264) 13.0% (31)
.San Bernardino 7.9% (107) 9.5% (101) 13.4% (235) 7.3% (8)
.San Diego 0.4% (18) 0.2% (5) 6.8% (204) 9.3% (36)
.San Francisco 9.2% (103) 11.0% (74) 19.3% (740) 14.5% (96)
.San Joaquin 8.6% (12) 10.8% (11) 24.3% (120) 0.0% (0)
.San Luis Obispo 21.4% (18) 31.1% (14) 8.4% (31) 0.0% (0)
.San Mateo 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
.Santa Barbara 6.9% (7) 30.8% (24) 15.8% (24) 0.0% (0)
.Santa Clara 6.6% (129) 9.8% (121) 11.2% (268) 11.5% (29)
.Santa Cruz 8.4% (21) 7.2% (16) 7.1% (26) 0.0% (0)
.Solano 3.9% (9) 9.0% (15) 7.4% (15) 14.3% (2)
.Sonoma 0.7% (1) 1.2% (2) 5.3% (23) 3.7% (1)
.Stanislaus 2.7% (32) 6.3% (33) 4.7% (30) 12.5% (2)
.Tulare 14.8% (39) 16.8% (25) 26.1% (150) 8.8% (3)
.Ventura 9.0% (46) 10.3% (49) 11.8% (86) 7.9% (6)
.Yolo 4.8% (2) 10.8% (4) 8.0% (14) 0.0% (0)
Small Counties 7.1% (115) 10.3% (111) 14.0% (533) 13.5% (43)
Black shading indicates where data was unavailable to calculate an indicator.
91
Priority Indicator 12: Satisfaction with Services
Table 12-1 - Satisfaction services by age group and county, FY 2008-0913
Each cell contains the mean accompanied by the n in parentheses.
County Children TAY Adults Older Adults
.Alameda 4.33 (1,066) 3.94 (925) 4.28 (1,971) 4.30 (189)
.Butte 4.30 (805) 4.12 (413) 4.34 (503) 4.28 (31)
.Contra Costa 4.36 (382) 4.16 (420) 4.23 (659) 4.40 (35)
.Fresno 4.18 (797) 3.92 (528) 4.33 (537) 4.55 (61)
.Kern 4.25 (594) 4.05 (552) 4.40 (1,109) 4.51 (105)
.Los Angeles 4.30 (11,171) 4.00 (6,860) 4.32 (12,748) 4.33 (972)
.Marin 4.23 (87) 3.88 (259) 4.33 (591) 4.28 (79)
.Merced 4.18 (23) 3.99 (35) 4.22 (412) 4.55 (16)
.Monterey 4.38 (161) 3.71 (337) 4.20 (545) 4.22 (50)
.Orange 4.28 (1,924) 4.08 (643) 4.39 (1,757) 4.42 (186)
.Placer 4.34 (230) 5.00 (2)
.Riverside 4.34 (805) 4.08 (643) 4.37 (1,464) 4.48 (342)
.Sacramento 4.33 (3,644) 4.12 (2,221) 4.28 (2,823) 4.38 (288)
.San Bernardino 4.20 (1,460) 4.14 (1,172) 4.38 (2,054) 4.59 (121)
.San Diego 4.36 (5,085) 4.05 (3,199) 4.46 (3,231) 4.52 (419)
.San Francisco 4.37 (1,193) 4.18 (739) 4.44 (4,587) 4.49 (832)
.San Joaquin 4.06 (157) 4.09 (116) 4.17 (659) 4.31 (45)
.San Luis Obispo 4.27 (101) 4.07 (60) 4.39 (400) 4.64 (12)
.San Mateo 3.59 (339) 4.00 (420) 4.44 (675) 4.65 (92)
.Santa Barbara 4.34 (105) 3.79 (107) 4.36 (182) 4.67 (2)
.Santa Clara 4.39 (2,093) 4.10 (1,367) 4.32 (2,691) 4.40 (291)
.Santa Cruz 4.43 (274) 4.19 (240) 4.30 (401) 4.27 (10)
.Solano 4.36 (241) 4.04 (183) 4.16 (223) 3.98 (16)
.Sonoma 4.34 (151) 4.04 (176) 4.20 (461) 4.59 (28)
.Stanislaus 4.38 (1,207) 4.12 (559) 4.39 (693) 4.70 (19)
.Tulare 4.17 (313) 4.12 (176) 4.09 (788) 4.33 (44)
.Ventura 4.39 (570) 4.15 (533) 4.29 (835) 4.47 (82)
.Yolo 4.40 (44) 4.07 (41) 3.99 (189) 4.50 (6)
Small Counties 4.26 (1,748) 4.09 (1,198) 4.28 (4,482) 4.45 (385)
Total 4.31 (36,540) 4.05 (24,694) 4.33 (47,900) 4.43 (4,770)
13 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
92
Table 12-2 - Family Member/Caregiver: Satisfaction services by race/ethnicity and county, FY 2008-
0914
Each cell contains the mean accompanied by the n in parentheses.
White Hispanic / Asian Pacific Black American Other
County Latino Islander Indian
.Alameda 4.26 (271) 4.37 (385) 4.39 (42) 4.19 (22) 4.33 (383) 4.40 (57) 4.34 (157)
.Butte 4.27 (588) 4.44 (177) 4.50 (15) 4.70 (5) 4.19 (59) 4.37 (106) 4.32 (92)
.Contra Costa 4.36 (110) 4.50 (137) 4.31 (25) 4.14 (7) 4.31 (144) 4.17 (24) 4.57 (54)
.Fresno 4.26 (232) 4.19 (405) 3.87 (13) 4.37 (9) 4.10 (131) 4.13 (38) 4.27 (168)
.Kern 4.20 (288) 4.31 (249) 4.08 (2) 4.17 (3) 4.25 (68) 3.97 (37) 4.33 (106)
.Los Angeles 4.32 (2,440) 4.36 (6,439) 4.28 (235) 4.34 (73) 4.26 (2,118) 4.22 (309) 4.36 (2,625)
.Marin 4.12 (44) 4.50 (30) 4.06 (4) 4.33 (3) 4.44 (8) 4.39 (14)
.Merced 4.11 (8) 4.09 (12) 4.67 (1) 4.00 (2) 4.00 (1) 4.17 (2) 4.67 (1)
.Monterey 4.30 (62) 4.43 (102) 4.53 (6) 3.94 (3) 4.39 (16) 4.52 (9) 4.47 (33)
.Orange 4.28 (759) 4.31 (1,080) 4.05 (78) 4.36 (32) 4.35 (90) 4.14 (80) 4.34 (384)
.Placer
.Riverside 4.29 (326) 4.37 (414) 4.67 (7) 4.63 (5) 4.28 (97) 4.22 (18) 4.37 (167)
.Sacramento 4.34 (1,777) 4.37 (1,101) 4.36 (18) 4.24 (67) 4.33 (2,571) 4.35 (273) 4.37 (515)
.San Bernardino 4.22 (590) 4.18 (655) 4.60 (18) 4.24 (7) 4.22 (275) 4.12 (65) 4.14 (334)
.San Diego 4.33 (1,841) 4.41 (2,878) 4.32 (130) 4.43 (75) 4.30 (660) 4.20 (203) 4.39 (1,113)
.San Francisco 4.42 (192) 4.45 (355) 4.37 (283) 4.31 (37) 4.32 (380) 4.38 (42) 4.45 (200)
.San Joaquin 4.09 (66) 4.11 (63) 3.33 (1) 4.28 (3) 4.04 (24) 3.77 (12) 4.33 (28)
.San Luis Obispo 4.25 (67) 4.53 (17) 4.63 (5) 4.50 (1) 3.99 (12) 4.35 (8) 3.97 (12)
.San Mateo 4.33 (107) 2.83 (160) 4.46 (8) 4.25 (20) 4.37 (39) 2.17 (1) 2.83 (152)
.Santa Barbara 4.39 (41) 4.41 (25) 4.33 (1) 3.77 (5) 4.27 (13) 4.03 (12)
.Santa Clara 4.36 (684) 4.41 (1,213) 4.28 (145) 4.20 (39) 4.40 (222) 4.31 (111) 4.41 (555)
.Santa Cruz 4.48 (119) 4.45 (150) 4.28 (6) 4.74 (7) 4.34 (14) 4.70 (11) 4.43 (53)
.Solano 4.38 (115) 4.47 (88) 4.10 (9) 4.43 (7) 4.24 (75) 4.49 (20) 4.47 (52)
.Sonoma 4.35 (110) 4.34 (55) 3.33 (4) 4.72 (3) 4.45 (9) 4.57 (17) 4.11 (19)
.Stanislaus 4.39 (708) 4.38 (545) 4.27 (18) 4.35 (19) 4.27 (79) 4.38 (55) 4.40 (282)
.Tulare 4.30 (154) 4.13 (151) 4.42 (2) 4.36 (3) 4.08 (9) 4.43 (17) 4.14 (51)
.Ventura 4.41 (222) 4.41 (326) 3.97 (5) 4.63 (5) 4.29 (30) 4.39 (542) 4.37 (101)
.Yolo 4.55 (26) 4.39 (19) 4.13 (4) 4.58 (4) 4.20 (10)
Small Counties 4.27 (1,122) 4.29 (548) 4.08 (13) 4.41 (21) 4.24 (99) 4.30 (186) 4.24 (236)
14 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
93
Table 12-3 - TAY: Satisfaction services by race/ethnicity and county, FY 2008-0915
Each cell contains the mean accompanied by the n in parentheses.
White Hispanic / Asian Pacific Black American Other
County Latino Islander Indian
.Alameda 4.00 (214) 4.10 (229) 3.90 (63) 3.92 (36) 3.97 (407) 3.89 (63) 3.94 (177)
.Butte 4.09 (284) 4.22 (67) 3.75 (6) 4.02 (7) 3.88 (32) 4.09 (57) 4.09 (63)
.Contra Costa 4.18 (298) 4.13 (126) 4.28 (20) 4.09 (12) 4.23 (172) 3.90 (38) 3.98 (73)
.Fresno 3.89 (102) 3.97 (270) 4.17 (32) 3.83 (4) 3.82 (65) 3.88 (33) 3.94 (154)
.Kern 4.13 (222) 4.09 (231) 4.43 (5) 4.40 (7) 3.89 (56) 3.98 (44) 4.01 (129)
.Los Angeles 4.06 (1,343) 4.07 (3,553) 3.91 (177) 3.77 (88) 3.96 (1,500) 3.99 (319) 4.06 (2,088)
.Marin 3.84 (141) 3.94 (71) 3.92 (17) 2.25 (2) 3.98 (32) 3.67 (19) 3.72 (49)
.Merced 4.00 (12) 3.90 (12) 3.92 (2) N/A 4.00 (2) 4.44 (3) 3.73 (5)
.Monterey 4.02 (77) 3.64 (211) 3.93 (10) 3.92 (6) 3.63 (25) 4.01 (13) 3.71 (103)
.Orange 4.08 (446) 4.13 (642) 4.01 (59) 4.06 (31) 4.03 (60) 4.15 (67) 4.07 (323)
.Placer
.Riverside 4.13 (211) 4.16 (309) 4.05 (10) 4.08 (7) 3.86 (82) 4.23 (24) 4.19 (165)
.Sacramento 4.17 (985) 4.15 (584) 4.07 (106) 3.90 (48) 4.05 (645) 4.16 (253) 4.07 (396)
.San Bernardino 4.21 (478) 4.17 (475) 3.95 (18) 4.00 (9) 4.11 (201) 4.09 (97) 4.09 (266)
.San Diego 4.07 (1,040) 4.12 (1,607) 4.05 (118) 4.19 (76) 3.96 (479) 4.02 (237) 4.10 (776)
.San Francisco 4.21 (95) 4.22 (194) 4.13 (161) 4.42 (30) 4.23 (273) 4.16 (31) 4.14 (141)
.San Joaquin 4.16 (46) 4.09 (43) 4.17 (1) 3.78 (3) 4.23 (20) 3.90 (13) 4.15 (23)
.San Luis Obispo 4.20 (36) 4.67 (6) 5.00 (1) 4.00 (1) 3.81 (4) 3.84 (8) 4.58 (5)
.San Mateo 3.98 (105) 3.97 (183) 4.33 (14) 4.32 (44) 4.05 (47) 3.61 (3) 3.93 (174)
.Santa Barbara 4.15 (21) 3.89 (48) 4.61 (3) 5.00 (1) 4.24 (8) 3.21 (6) 3.85 (35)
.Santa Clara 4.08 (358) 4.14 (755) 3.96 (118) 3.95 (40) 4.20 (167) 4.19 (115) 4.12 (434)
.Santa Cruz 4.21 (92) 4.16 (129) 4.43 (5) 4.54 (4) 4.17 (17) 4.18 (23) 4.21 (83)
.Solano 4.02 (89) 3.96 (40) 3.42 (12) 3.57 (3) 3.96 (58) 3.96 (20) 4.07 (32)
.Sonoma 4.07 (118) 4.12 (49) 3.83 (11) 4.00 (3) 4.13 (13) 4.08 (24) 3.96 (44)
.Stanislaus 4.18 (271) 4.09 (255) 3.88 (11) 4.46 (8) 4.05 (37) 4.06 (40) 4.13 (182)
.Tulare 4.17 (64) 4.16 (80) 4.00 (4) 4.00 (3) 4.09 (11) 4.11 (14) 4.18 (39)
.Ventura 4.20 (221) 4.18 (236) 4.48 (7) 4.24 (14) 3.97 (40) 4.16 (31) 4.13 (132)
.Yolo 4.08 (22) 3.95 (15) 3.33 (2) 4.33 (4) 4.17 (4) 3.58 (4)
Small Counties 4.12 (643) 4.07 (392) 4.17 (22) 3.94 (8) 4.09 (1,198) 4.18 (173) 4.00 (239)
15 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
94
Table 12-4 - Adult: Perceptions of access to services by race/ethnicity and county, FY
2008-0916
Each cell contains the mean accompanied by the n in parentheses.
Hispanic / Pacific American
White Asian Black Other
County Latino Islander Indian
.Alameda 4.28 (699) 4.38 (308) 4.26 (237) 4.07 (59) 4.28 (613) 4.30 (109) 4.32 (229)
.Butte 4.32 (376) 4.31 (58) 4.28 (16) 4.27 (5) 4.39 (14) 4.34 (43) 4.44 (35)
.Contra Costa 4.24 (267) 4.35 (139) 4.33 (48) 4.36 (12) 4.19 (146) 4.21 (39) 4.27 (67)
.Fresno 4.31 (183) 4.37 (195) 4.19 (30) 3.50 (6) 4.36 (57) 4.33 (24) 4.47 (127)
.Kern 4.41 (635) 4.45 (359) 4.29 (13) 4.44 (13) 4.26 (77) 4.44 (74) 4.41 (203)
.Los Angeles 4.39 (3,479) 4.45 (3,769) 4.18 (737) 4.34 (163) 4.36 (2,738) 4.18 (607) 4.43 (2,129)
.Marin 4.33 (440) 4.23 (49) 4.04 (19) 4.18 (11) 4.32 (34) 4.41 (45) 4.15 (54)
.Merced 4.32 (152) 4.16 (128) 4.55 (20) 4.67 (8) 4.33 (41) 4.07 (38) 4.16 (72)
.Monterey 4.26 (242) 4.21 (201) 4.29 (22) 3.89 (6) 3.97 (46) 3.96 (39) 4.15 (116)
.Orange 4.39 (886) 4.48 (442) 4.31 (209) 4.48 (22) 4.43 (79) 4.43 (61) 4.48 (265)
.Placer 4.31 (168) 4.43 (24) 5.00 (3) 4.78 (3) 4.67 (5) 4.39 (17) 4.16 (15)
.Riverside 4.38 (764) 4.45 (431) 4.36 (25) 4.52 (18) 4.31 (162) 4.36 (60) 4.34 (251)
.Sacramento 4.27 (1,320) 4.36 (400) 4.29 (218) 4.25 (49) 4.38 (546) 4.36 (196) 4.36 (290)
.San Bernardino 4.42 (971) 4.42 (580) 4.49 (32) 4.19 (16) 4.44 (247) 4.39 (116) 4.38 (280)
.San Diego 4.43 (1,657) 4.56 (899) 4.49 (178) 4.49 (56) 4.44 (365) 4.48 (150) 4.51 (533)
.San Francisco 4.48 (847) 4.52 (694) 4.44 (757) 4.42 (1,099) 4.41 (676) 4.47 (156) 4.52 (500)
.San Joaquin 4.19 (279) 4.15 (130) 4.13 (39) 4.77 (13) 4.19 (59) 4.12 (61) 3.99 (81)
.San Luis Obispo 4.40 (310) 4.24 (48) 4.67 (8) 5.00 (2) 4.56 (15) 4.31 (32) 4.19 (35)
.San Mateo 4.41 (378) 4.54 (158) 4.36 (29) 4.33 (54) 4.46 (55) 4.10 (10) 4.58 (128)
.Santa Barbara 4.35 (84) 4.44 (57) 4.50 (4) 4.00 (1) 4.24 (7) 4.33 (7) 4.60 (34)
.Santa Clara 4.35 (1,222) 4.37 (651) 4.31 (291) 4.23 (54) 4.33 (219) 4.34 (156) 4.35 (378)
.Santa Cruz 4.33 (267) 4.31 (86) 4.13 (13) 4.17 (4) 4.11 (12) 4.27 (28) 4.29 (58)
.Solano 4.17 (104) 4.17 (41) 4.42 (21) 4.14 (7) 4.20 (61) 4.48 (22) 4.28 (23)
.Sonoma 4.22 (352) 4.48 (64) 3.57 (10) 4.56 (6) 4.24 (18) 4.21 (27) 3.98 (41)
.Stanislaus 4.41 (432) 4.41 (151) 4.40 (26) 4.49 (13) 4.45 (34) 4.32 (51) 4.41 (87)
.Tulare 4.14 (335) 4.28 (217) 4.17 (17) 4.42 (4) 4.17 (27) 4.21 (38) 4.37 (117)
.Ventura 4.28 (515) 4.28 (208) 4.56 (13) 4.21 (13) 4.21 (29) 4.26 (37) 4.29 (130)
.Yolo 3.90 (105) 4.10 (39) 4.30 (10) 4.67 (1) 3.80 (16) 4.12 (14) 4.14 (28)
Small Counties 4.33 (2,686) 4.39 (862) 4.44 (86) 4.40 (35) 4.35 (220) 4.35 (369) 4.33 (490)
16 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
95
Table 12-5 - Older Adult: Perceptions of access to services by race/ethnicity and county, FY
2008-0917
Each cell contains the mean accompanied by the n in parentheses.
White Hispanic / Asian Pacific Black American Other
County Latino Islander Indian
.Alameda 4.40 (86) 4.50 (18) 3.94 (11) 4.00 (1) 4.22 (54) 4.35 (10) 4.33 (13)
.Butte 4.15 (25) 5.00 (1) 4.33 (5) 5.00 (2)
.Contra Costa 4.42 (20) 3.67 (1) 4.39 (6) 4.42 (4) 4.17 (2)
.Fresno 4.66 (40) 4.39 (11) 5.00 (3) 4.83 (2) 5.00 (3)
.Kern 4.44 (56) 4.47 (30) 3.67 (1) 4.48 (7) 4.42 (6) 4.38 (14)
.Los Angeles 4.47 (304) 4.57 (245) 4.47 (62) 3.06 (6) 4.42 (124) 4.28 (20) 4.59 (121)
.Marin 4.21 (56) 4.71 (7) 4.50 (4) 4.00 (1) 4.53 (5)
.Merced 4.19 (7) 5.00 (4) 5.00 (2) 5.00 (1) 5.00 (2)
.Monterey 4.20 (31) 4.33 (9) 5.00 (1) 4.58 (4) 4.08 (4)
.Orange 4.53 (90) 4.41 (43) 4.38 (22) 5.00 (1) 4.19 (12) 4.50 (4) 4.45 (30)
.Placer 5.00 (2)
.Riverside 4.47 (206) 4.56 (81) 4.67 (3) N/A 4.34 (29) 4.33 (13) 4.50 (43)
.Sacramento 4.43 (154) 4.55 (19) 4.48 (23) 4.67 (1) 4.33 (39) 4.31 (15) 4.46 (20)
.San Bernardino 4.61 (68) 4.66 (25) 3.92 (4) 4.70 (11) 4.69 (14) 4.57 (10)
.San Diego 4.45 (209) 4.61 (143) 4.61 (18) 5.00 (2) 4.52 (34) 4.52 (11) 4.58 (62)
.San Francisco 4.51 (369) 4.61 (95) 4.41 (125) 4.19 (9) 4.41 (101) 4.41 (31) 4.54 (69)
.San Joaquin 4.16 (25) 4.48 (7) 5.00 (2) 3.50 (2) 4.67 (3) 4.53 (5)
.San Luis Obispo 4.60 (10) 4.67 (1) 5.00 (1)
.San Mateo 4.68 (61) 4.63 (17) 4.50 (2) 4.36 (11) 4.89 (3) 4.33 (2) 4.50 (6)
.Santa Barbara 4.33 (1) 5.00 (1) 5.00 (1)
.Santa Clara 4.42 (170) 4.56 (48) 4.35 (34) 5.00 (2) 4.18 (14) 4.05 (7) 4.55 (23)
.Santa Cruz 4.38 (7) 4.00 (1) 4.00 (2) 4.50 (2)
.Solano 4.04 (8) 3.50 (2) 4.00 (1) 3.50 (4) 5.00 (1) 3.33 (1)
.Sonoma 4.60 (26) 5.00 (1)
.Stanislaus 4.78 (15) 4.00 (1) 5.00 (1) 4.67 (1)
.Tulare 4.28 (18) 4.56 (16) 5.00 (1) 3.89 (3) 4.20 (5) 4.24 (7)
.Ventura 4.43 (50) 4.63 (25) 4.67 (3) 4.44 (3) 4.79 (4) 5.00 (4) 4.14 (7)
.Yolo 4.50 (4) 4.00 (1) 5.00 (1)
Small Counties 4.49 (257) 4.58 (51) 4.17 (4) 3.50 (4) 4.26 (13) 4.65 (20) 4.61 (18)
17 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
96
Table 12-6 - Race/Ethnicity: Unknown Table
County Children TAY Adults Older Adults
.Alameda 51.7% (681) 20.9% (249) 17.3% (391) 21.2% (41)
.Butte 60.3% (628) 20.5% (106) 19.6% (107) 27.3% (9)
.Contra Costa 48.9% (245) 11.4% (84) 18.9% (136) 42.4% (14)
.Fresno 39.4% (392) 19.2% (127) 16.2% (101) 16.9% (10)
.Kern 45.8% (345) 18.4% (128) 11.4% (157) 16.7% (19)
.Los Angeles 11.8% (1,678 15.5% (1,402 21.0% (2,855 33.8% (298
.Marin 13.6% (14) 13.3% (44) 15.0% (98) 21.9% (16)
.Merced 14.8% (4) 30.6% (11) 22.0% (101) 31.3% (5)
.Monterey 8.2% (19) 13.9% (62) 12.2% (82) 20.4% (10)
.Orange 10.0% (251) 11.7% (190) 17.8% (349) 16.3% (33)
.Placer 23.0% (54 50.0% (1
.Riverside 10.0% (103) 17.6% (142) 14.9% (255) 13.6% (51)
.Sacramento 9.5% (603) 19.0% (574) 23.5% (710) 28.8% (78)
.San Bernardino 13.8% (269) 15.8% (244) 21.2% (476) 24.2% (32)
.San Diego 6.1% (418) 12.2% (530) 13.5% (519) 18.2% (87)
.San Francisco 13.4% (199) 14.9% (138) 27.6% (1,306) 32.0% (256)
.San Joaquin 16.2% (32) 21.5% (32) 33.2% (220) 34.1% (15)
.San Luis Obispo 15.6% (19) 34.4% (21) 16.7% (75) 16.7% (2)
.San Mateo 6.0% (29) 10.2% (58) 21.4% (174) 33.3% (34)
.Santa Barbara 13.4% (13) 38.5% (47) 21.6% (42) 0.0% (0)
.Santa Clara 10.2% (304) 11.1% (221) 20.3% (603) 22.5% (67)
.Santa Cruz 7.8% (28) 8.8% (31) 12.6% (59) 16.7% (2)
.Solano 7.1% (26) 17.7% (45) 17.6% (49) 17.6% (3)
.Sonoma 4.1% (9) 6.5% (17) 14.3% (74) 3.7% (1)
.Stanislaus 4.2% (71) 9.3% (75) 15.4% (122) 22.2% (4)
.Tulare 16.3% (63) 20.5% (44) 35.1% (265) 20.0% (10)
.Ventura 6.5% (80) 16.6% (113) 16.8% (159) 13.5% (13)
.Yolo 7.9% (5) 9.8% (5) 15.5% (33) 0.0% (0)
Small Counties 24.6% (548) 10.2% (272) 21.5% (1,022) 24.3% (89)
Black shading indicates where data was unavailable to calculate an indicator.
97
Table 12-7 - Perceptions of access to services by gender and county, FY 2008-0918
Each cell contains the mean accompanied by the n in parentheses.
County Children TAY Adult Older Adult
Female Male Female Male Female Male Female Male
.Alameda 4.29 (304) 4.35 (691) 4.06 (321) 3.96 (490) 4.32 (775) 4.27 (1,054) 4.25 (83) 4.35 (85)
.Butte 4.28 (312) 4.30 (450) 4.17 (185) 4.08 (194) 4.34 (237) 4.34 (203) 4.55 (14) 3.93 (15)
.Contra Costa 4.45 (127) 4.33 (238) 4.21 (180) 4.16 (222) 4.24 (306) 4.23 (263) 4.39 (17) 4.30 (9)
.Fresno 4.14 (282) 4.23 (427) 3.99 (217) 3.91 (221) 4.34 (255) 4.36 (218) 4.60 (44) 4.69 (13)
.Kern 4.28 (212) 4.22 (343) 4.17 (238) 4.02 (264) 4.48 (626) 4.30 (417) 4.53 (75) 4.32 (23)
.Los Angeles 4.32 (4,062) 4.32 (6,230) 4.09 (2,980) 3.97 (3,189) 4.42 (6,210) 4.35 (4,211) 4.48 (479) 4.47 (265)
.Marin 4.08 (31) 4.31 (53) 3.93 (68) 3.88 (156) 4.40 (279) 4.27 (258) 4.29 (37) 4.28 (37)
.Merced 4.23 (7) 4.04 (13) 4.04 (12) 4.09 (13) 4.29 (176) 4.13 (171) 4.50 (8) 4.72 (6)
.Monterey 4.35 (63) 4.43 (88) 4.10 (95) 3.50 (202) 4.35 (267) 4.08 (235) 4.41 (23) 4.08 (18)
.Orange 4.32 (714) 4.27 (1,068) 4.13 (521) 4.06 (582) 4.45 (871) 4.35 (690) 4.45 (96) 4.44 (77)
.Placer 4.44 (107) 4.28 (93) N/A 5.00 (2)
.Riverside 4.28 (231) 4.36 (518) 4.05 (210) 4.13 (349) 4.44 (746) 4.31 (586) 4.50 (218) 4.43 (103)
.Sacramento 4.31 (1,433) 4.36 (1,977) 4.15 (971) 4.11 (1,024) 4.33 (1,469) 4.27 (1,014) 4.43 (153) 4.38 (93)
.San Bernardino 4.17 (475) 4.21 (871) 4.22 (433) 4.12 (632) 4.45 (1,105) 4.36 (646) 4.60 (84) 4.62 (24)
.San Diego 4.36 (1,860) 4.37 (3,206) 4.11 (1,418) 4.01 (1,775) 4.50 (1,622) 4.43 (1,378) 4.59 (243) 4.38 (147)
.San Francisco 4.38 (406) 4.37 (692) 4.25 (324) 4.14 (350) 4.51 (1,661) 4.41 (2,123) 4.48 (350) 4.48 (344)
.San Joaquin 3.98 (62) 4.17 (78) 4.09 (59) 4.09 (42) 4.24 (266) 4.15 (232) 4.31 (29) 4.12 (11)
.San Luis Obispo 4.38 (33) 4.12 (51) 4.06 (22) 4.13 (24) 4.47 (207) 4.32 (161) 4.60 (5) 4.67 (7)
.San Mateo 3.44 (125) 3.69 (214) 4.04 (167) 3.97 (253) 4.52 (389) 4.32 (286) 4.74 (61) 4.48 (31)
.Santa Barbara 4.37 (47) 4.28 (52) 3.67 (23) 4.02 (54) 4.29 (82) 4.38 (71) 4.33 (1) 5.00 (1)
.Santa Clara 4.38 (734) 4.39 (1,219) 4.20 (526) 4.07 (716) 4.40 (1,247) 4.29 (1,156) 4.41 (161) 4.41 (93)
.Santa Cruz 4.50 (105) 4.35 (147) 4.26 (104) 4.10 (120) 4.46 (184) 4.17 (183) 4.30 (9) 4.00 (1)
.Solano 4.35 (89) 4.38 (141) 4.13 (67) 3.93 (100) 4.29 (95) 4.11 (110) 4.06 (6) 3.88 (8)
.Sonoma 4.49 (48) 4.27 (102) 4.18 (98) 3.91 (76) 4.37 (201) 4.07 (233) 4.76 (14) 4.45 (13)
.Stanislaus 4.43 (398) 4.36 (775) 4.18 (214) 4.10 (311) 4.48 (370) 4.31 (276) 4.71 (15) 5.00 (1)
.Tulare 4.20 (91) 4.21 (176) 4.21 (76) 4.08 (73) 4.22 (338) 4.19 (250) 4.46 (26) 4.23 (10)
.Ventura 4.32 (207) 4.45 (306) 4.22 (206) 4.12 (272) 4.30 (360) 4.26 (371) 4.52 (50) 4.48 (26)
.Yolo 4.65 (8) 4.37 (34) 4.44 (12) 3.91 (25) 4.10 (65) 3.90 (108) 4.60 (5) 4.00 (1)
Small Counties 4.27 (616) 4.27 (1,016) 4.17 (532) 4.05 (552) 4.39 (2,375) 4.26 (1,460) 4.53 (221) 4.37 (107)
18 Consumer perception data for FY 2009-10 cannot be disaggregated by county.
Black shading indicates where data was unavailable to calculate an indicator.
98
Table 12-8 - Gender: Unknown/Missing Tables
County Children TAY Adults Older Adults
.Alameda 7.1% (7) 14.1% (114) 7.8% (142) 12.5% (21)
.Butte 5.6% (43) 9.0% (34) 14.3% (63) 6.9% (2)
.Contra Costa 4.7% (17) 4.5% (18) 15.8% (90) 34.6% (9)
.Fresno 12.4% (88) 20.5% (90) 13.5% (64) 7.0% (4)
.Kern 0.2% (1) 10.0% (50) 6.3% (66) 7.1% (7)
.Los Angeles 7.8% (802) 1.2% (76) 7.1% (736) 30.6% (228)
.Marin 3.6% (3) 15.6% (35) 10.1% (54) 6.8% (5)
.Merced 15.0% (3) 18.0% (45) 18.7% (65) 14.3% (2)
.Monterey 6.6% (10) 13.5% (40) 8.6% (43) 22.0% (9)
.Orange 8.0% (142) 10.2% (112) 12.6% (196) 7.5% (13)
.Placer 15.0% (30) 0.0% (0)
.Riverside 7.5% (56) 15.0% (84) 9.9% (132) 6.5% (21)
.Sacramento 6.9% (234) 11.3% (226) 13.7% (340) 17.1% (42)
.San Bernardino 8.5% (114) 10.0% (107) 17.3% (303) 12.0% (13)
.San Diego 0.4% (19) 0.2% (6) 7.7% (231) 10.0% (39)
.San Francisco 8.7% (95) 9.6% (65) 21.2% (803) 19.9% (138)
.San Joaquin 12.1% (17) 14.9% (15) 32.3% (161) 12.5% (5)
.San Luis Obispo 20.2% (17) 30.4% (14) 8.7% (32) 0.0% (0)
.San Mateo 0.0% (0) 0.0% (0) 0.0% (0) 0.0% (0)
.Santa Barbara 6.1% (6) 39.0% (30) 19.0% (29) 0.0% (0)
.Santa Clara 7.2% (140) 10.1% (125) 0.5% (13) 14.6% (37)
.Santa Cruz 8.7% (22) 7.1% (16) 9.3% (34) 10.0% (1)
.Solano 4.8% (11) 9.6% (16) 8.8% (18) 14.3% (2)
.Sonoma 0.7% (1) 1.1% (2) 6.2% (27) 3.7% (1)
.Stanislaus 2.9% (34) 6.5% (34) 7.3% (47) 18.8% (3)
.Tulare 17.2% (46) 18.1% (27) 34.0% (200) 22.2% (8)
.Ventura 11.1% (57) 11.5% (55) 14.2% (104) 7.9% (6)
.Yolo 4.8% (2) 10.8% (4) 9.2% (16) 0.0% (0)
Small Counties 7.1% (116) 10.5% (114) 16.9% (647) 17.4% (57)
Black shading indicates where data was unavailable to calculate an indicator.