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StateData: The National Report on Employment Services and Outcomes (2009)

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Originally published: 2/2010

Institute for Community Inclusion (UCEDD)
University of Massachusetts Boston

Winter 2010

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The StateData employment report is a product of Access to Integrated Employment, a project of the Institute for Community Inclusion at UMass Boston, supported in part by the Administration on Developmental Disabilities, U.S. Department of Health and Human Services under cooperative agreement #90DN0216. The opinions contained in this report are those of the grantee and do not necessarily reflect those of the funders.

Acknowledgements

The authors would like to express sincere thanks to our collaborators at the National Association of State Directors of Developmental Disabilities Services (NASDDDS), including Nancy Thaler, Chas Moseley, and Rie Kennedy-Lizotte. Additionally, the authors acknowledge the contributions of ICI’s entire StateData team, including Bill Kiernan, Suzzanne Freeze, Samita Bhattarai, Jaimie Timmons, and Monica Cox, as well as David Temelini, who assisted in the layout and production of this report. Lastly, Marcos Elugardo has provided significant database management and assistance and we thank him for these efforts.

Special thanks are directed toward the state administrators and key survey contacts in each state who consistently respond to ICI’s Intellectual and Developmental Disabilities (ID/DD) Agency National Survey of Day and Employment Outcomes. Their expertise, insights, and assistance have helped to make this report possible.

Table of Contents

Executive Summary

Introduction

Methodology

National Trends in Employment

Conclusion

Topical Chapter—
Data Systems and Decision-making: State ID/DD Agencies and their Employment Data

Allison Hall, Jean Winsor, and John Butterworth

References

List of Tables

List of Figures

Executive Summary

Policy shifts over the past 20 years have created an agenda for sustained commitment to integrated employment for individuals with disabilities. But despite these clear intentions, unemployment of individuals with disabilities continues to be a significant and pressing public policy concern. Recent analysis using the Current Population Survey (CPS) for September 2009 estimates that 28 percent of working-age adults with disabilities are employed, compared with 70 percent of people without disabilities, and CPS data published by the Bureau of Labor Statistics suggests that the number of workers with disabilities has dropped at three times the rate of workers without disabilities since October 2008. For people with intellectual and developmental disabilities (ID/DD) the disparity in labor market participation increases. In FY2003, only 26 percent of individuals with ID/DD supported by community rehabilitation providers (CRPs) worked in integrated jobs, including both individual jobs and group supported employment (Metzel, Boeltzig, Butterworth, Sulewski, & Gilmore, 2007). At the same time, participation in sheltered or facility-based employment and non-work services has grown steadily, suggesting that employment services continue to be viewed as an add-on service rather than a systemic change (Winsor & Butterworth, 2008; Mank, 2003).

States vary widely in their commitment to integrated employment. In recent years, we have worked with and documented individual state ID/DD agencies that have employment working groups, employment initiatives, and employment-first policies and agendas. The efforts of some of these states are being reflected in their employment outcomes data despite the fact that the federal government, through the Medicaid program, continues to spend four times more money on segregated adult day programs, including day habilitation and sheltered work ($488 million in 2002), than on supported employment ($108 million) (Rusch & Braddock, 2004). Nationally, an estimated 21.9 percent of individuals receiving day supports from state ID/DD agencies participated in integrated employment services during FY2008. This number has slowly declined following the peak of 25 percent of individuals in integrated employment in FY2001.

For the past 20 years, ICI’s Access to Integrated Employment, the national data collection project on day and employment outcomes funded by the Administration on Developmental Disabilities, has described the nature of day and employment services for individuals with ID/DD and contributed to a comprehensive understanding of the factors that influence employment outcomes at an individual, service provider, and state policy level. This report provides statistics over a 20-year period from several national data sets that address the status of employment and economic self-sufficiency for individuals with intellectual and developmental disabilities (ID/DD). The report contains three major sections:

Data from five sources is included: ICI’s ID/DD Agency National Survey of Day and Employment Programs for People with Developmental Disabilities from FY1988, 1990, 1993, 1996, 1999, 2001, 2004, 2007 and 2008, and datasets from the Social Security Administration (SSA), state Vocational Rehabilitation Programs, the U.S. Census Bureau (The American Community Survey), and the Bureau of Labor Statistics.

From varying perspectives, each dataset that is included in this report sheds light on the economic disparities that people with intellectual and developmental disabilities have experienced over the past decade and beyond. More individuals continue to be supported in facility-based employment, typically earning sub-minimum wage, than in integrated employment. In the Vocational Rehabilitation (VR) system, earnings of adults with disabilities are substantially lower compared to those in the general population. Overall, the findings suggest the need for a renewed and shared focus across several systems:

Multiple data sets offer varying perspectives on the employment situations of individuals with disabilities, and specifically intellectual and developmental disabilities. While the data do show progress in some systems (e.g., the gradual reduction in number of individuals working in sheltered employment and increased earnings for individuals who exit the VR system), there continues to be an urgent need for a re-investment of attention, priority, and resources dedicated toward expanding both economic and employment opportunities for individuals with intellectual and developmental disabilities.

Introduction

Enabling people with disabilities to enter the labor market is a priority concern for federal and state policy makers (Silverstein, Julnes, & Nolan, 2005). President George W. Bush’s New Freedom Initiative articulates a commitment to increase access and achieve better employment outcomes. Policy shifts over two decades have established an increasing emphasis on integrated employment, and the federal government has set the tone for broad-based systems change (Rogan, Novak, Mank, & Martin, 2002).

Even with this clear policy intent, there remains a significant gap in employment rates between people with and without disabilities. The September 2009 Current Population Survey (CPS) estimates that 28 percent of working-age adults with disabilities are employed, compared with 70 percent of people without disabilities. For people with intellectual and developmental disabilities (ID/DD), the disparity in employment participation widens further. In FY2003, only 26 percent of individuals supported by community rehabilitation providers (CRPs) worked in integrated jobs (Metzel, Boeltzig, Butterworth, Sulewski, & Gilmore, 2007), and data suggest that those who are employed work limited hours with low wages (Mank, 2003; Boeltzig, Gilmore, & Butterworth, 2006). At the same time, participation in sheltered employment and non-work services has grown steadily, suggesting that employment services continue to be viewed as an add-on service rather than a systemic change (Winsor & Butterworth, 2008; Mank, 2003).

Although nationwide resources and priorities have not realigned to expand employment, there is substantial evidence that individual states and CRPs are expanding community employment and focusing on outcomes. In FY2008, Connecticut, New Hampshire, New Mexico, Oklahoma, and Washington all reported that more than 40 percent of individuals receiving day and employment services were receiving integrated employment services. Analysis of the FY2004–2005 National Survey of Community Rehabilitation Providers showed that the majority (81 percent) of those entering some type of integrated employment worked in individual jobs. Of those people, most were paid above federal and state minimum wage levels from their employers and received paid time off (Boeltzig, Timmons, & Butterworth, 2009).

More recently, as an outgrowth of ICI’s Access to Integrated Employment project, state ID/DD agencies have come together as members of the State Employment Leadership Network, a membership roundtable co-managed with the National Association of State Directors of Developmental Disabilities Services dedicated to expanding employment for individuals with ID/DD. A growing number of advocates and states are adopting or using “employment first” as a guiding principle in policy and systems change. APSE (formerly the Association for Persons in Supported Employment) reported that 12 states are actively involved in “employment first” initiatives or considering the launch of local efforts focusing on employment first within their state (Niemac, Lavin, & Owens, 2009). The Alliance for Full Participation, a coalition of disability advocacy organizations, established employment as the priority for a 2011 national summit and has begun implementing outreach and planning for that event. The Office of Disability and Employment Policy (ODEP) recently brought together key leaders in the field to discuss these “employment first” policies in states where sheltered employment with sub-minimum wages and non-work day activities are no longer acceptable employment outcomes (Romano, 2009). The need to expand these activities was cited as a critical element in advancing the vision of people with disabilities as important contributors to renewed economic growth.

Policy and Practice Challenges

Despite advances in federal policy and the leadership of some high-performing states, widespread expansion of integrated employment has not occurred. Several factors present continuing challenges:

State and federal policy do not consistently prioritize employment. Despite spending millions of dollars on secondary education, adult community services, Social Security disability benefits, transportation, and comprehensive healthcare for Americans with disabilities, few of these resources actually encourage or reward integrated community based employment (Niemac, Lavin, & Owens, 2009). State systems continue to invest in sheltered employment and non-work services. While the number of individuals with ID/DD in integrated employment is growing, the number participating in sheltered employment and non-work services has grown even more rapidly over the past decade, and CRPs that have closed a facility-based program report that state agencies are rarely a catalyst for change (Butterworth, Fesko, & Ma, 2000). Expansion of community-based non-work services has competed with integrated employment, despite evidence that these services are poorly defined and do not consistently achieve their stated goals of community membership (Sulewski, Butterworth, & Gilmore, 2006).

Using data from the ICI’s ID/DD Agency National Survey of Day and Employment Programs for People with Developmental Disabilities, it was estimated that the total number of people served by state ID/DD agencies increased 91 percent (from 287,860 to 550,818) between 1988 and 2008. Over this same period of time, the number of people receiving integrated employment services increased 262 percent (from 33,382 to 120,691). Focusing on more recent data from 1999 to 2008, growth in integrated employment has not kept pace with the overall growth in the total number of individuals receiving services. Between 1999 and 2008, the estimated total number of individuals receiving services increased 20 percent while the number of individuals receiving integrated employment services only increased by 10 percent. Concurrently the percentage of individuals in integrated employment declined from 23.7 percent to 21.9 percent.

CRPs have not reallocated resources to community employment. In a national survey of CRPs that provide sub-minimum wage employment, 89 percent of respondents indicated that sheltered employment was a necessary service, 69 percent responded that individuals with intellectual/developmental disabilities were unable to earn minimum wage, and only 47 percent indicated that their organization had a formal plan to expand integrated employment (Wehman, Inge, Revell, Butterworth, & Gilmore, 2007).

Best practices in job support and job development are not consistently implemented. Emerging practices such as job creation, customized employment, and facilitation of natural supports are rarely used in practice at the direct support level, reflecting a need to address direct-support professional training, qualifications, and job roles. For example, in the 2002-2003 ICI Survey of CRPs, only 35 out of more than 38,000 individuals with ID/DD were identified as supported in self-employment.

Individual employment outcomes have not progressed. Findings from ICI’s FY2004–2005 Individual Employment Outcomes Survey show that the majority of individuals with ID/DD work part-time and predominantly in the entry-level service industry, annual income remains low, and individuals have limited access to employee benefits such as health care (Boeltzig, Timmons, Gilmore, & Butterworth, 2007). A longitudinal comparison of the quality of supported employment outcomes shows similar results: despite slight improvements in some areas such as worksite integration, work rate, and work quality, individuals obtaining jobs in the late 1990s worked similar hours, earned similar wages, and held similar types of jobs compared to those obtaining jobs in the early 1990s (Mank, Cioffi, & Yovanoff, 2003). Additionally, Schur, Kruse, Blasi, and Blank (2009) found that employees with disabilities have less job security, experience higher levels of supervision, lower rates of participation in decision-making, and lower levels of company-sponsored formal training and informal training from coworkers.

Services and Supports Used by People with Intellectual and Developmental Disabilities

Employment supports are provided within a context of state and federal disability policy, workforce development policy, income maintenance and health care policy, and a wide array of work-related supports including transportation, housing, welfare, and childcare. Core supports are funded by state ID/DD and Vocational Rehabilitation (VR) agencies, and delivered by a network of over 12,000 CRPs. State trends and individual decisions about supports and employment are influenced by state funding for employment support, Medicaid and Social Security Administration policy, and CRP priorities and emphases.

State ID/DD agencies. State ID/DD agencies remain the primary source of long-term funding and service coordination for individuals with ID/DD, providing, funding, and monitoring a wide range of day and employment services. They support an estimated half a million adults in employment and day services nationally. The services they provide include employment supports, traditional facility-based options including sheltered workshops and non-work day habilitation programs, and community integration services. Given their essential role, examining state ID/DD policies and practices is vital for understanding the factors that influence employment outcomes.

State VR agencies. State VR agencies provide services to over one million people annually, with over 600,000 completing services and having their cases closed in each fiscal year. Approximately 12.5 percent, or 73,000, of those case closures can be identified as individuals with ID/DD (persons with a primary disability of mental retardation, cerebral palsy, epilepsy, or autism).

One-Stop career centers. One-stop career centers, established and supported under the Workforce Investment Act, provide a largely underutilized resource for individuals with ID/DD and other disabilities. In 2007, over 465,000 individuals with disabilities registered as job seekers for Wagner Peyser-funded one-stop services. Only 1,258 individuals with ID/DD who closed out of VR services in 2008 were referred from one-stop centers.

Medicaid. Medicaid is both a primary source for health care for individuals with ID/DD and the largest federal source of funding for day and employment services under the Home and Community Based Services waiver program. Despite expansion of Medicaid initiatives to support employment, including the Medicaid Infrastructure Grant program and expansion of state Medicaid buy-in programs, there is no preference for integrated employment in Medicaid funded services, and state Medicaid agencies have limited involvement in employment initiatives. In a study by Sulewski, Gilmore, and Foley (2006), state Medicaid agencies were asked about the provision of services to working people with disabilities and collaboration with disability- and employment-related agencies and services. Only one-third to one-half of respondents were involved in Workforce Investment Act implementation at the state level or were implementing a Medicaid buy-in option for working adults with disabilities. Collaboration with disability- or employment-focused agencies occurred at similarly moderate rates.

Social Security. SSA work incentives such as the Plan for Achieving Self Support (PASS) and Impairment-Related Work Expenses (IRWE) are designed to support employment by allowing individuals to exclude money, resources, and certain expenses from total earned income calculations. SSA also administers the Ticket to Work program, designed to provide beneficiaries with the ability to purchase Vocational Rehabilitation, employment, and other support services from any participating employment network or state VR agency of their choice. Despite SSA’s initiatives, work incentives and the Ticket to Work program remain largely under-utilized. In 2007, on average only 34 SSI recipients per state had PASS plans and 108 recipients per state had IRWEs in place. That same year, only 8 percent of individuals age 18 to 64 on SSI were identified as working (SSA, 2007).

Community Rehabilitation Providers (CRPs). CRPs and their staff are the primary source of day and employment supports for people with ID/DD. Based on the results of recent efforts to build a comprehensive list of CRPs, the ICI estimates that over 12,000 CRPs nationwide offer vocational services to individuals with disabilities. The majority (70 percent) of those served by CRPs are individuals with ID/DD (Metzel, Boeltzig, Butterworth, Sulewski, & Gilmore, 2007). Over two thirds of CRPs provide work and non-work services in both integrated and facility-based settings (Metzel, Boeltzig, Butterworth, Sulewski, & Gilmore, 2007). Findings indicate that 74 percent of individuals with ID/DD were supported in sheltered employment, day habilitation services, or non-work community integration supports, while only 26 percent were working in integrated employment. Furthermore, 8 percent of those in integrated employment were in group-supported employment models, including enclaves and mobile work crews. In a national survey of CRPs that provide sub-minimum wage employment, respondents reported that only 8.7 percent of staff work with individuals earning minimum wage or higher (Wehman, Inge, Revell, Butterworth, & Gilmore, 2007).

Factors that Influence Employment Outcomes

States vary widely in the extent to which they support integrated employment. Research suggests a range of factors that influence access to employment opportunities and areas of focus for state policy and strategy.

High performing state ID/DD agencies. ICI’s research on “high performing” state ID/DD agencies has identified policies and practices that support improved employment outcomes. ICI identifies high-performing states based on the percentage of those served by the state’s ID/DD agency that participate in integrated employment and the rate of growth in integrated employment. Strategies that characterize high-performing states include flexibility in funding and policies, communication of values through data, rewards and funding incentives, and innovation diffusion through relationships and training (Hall, Butterworth, Winsor, Gilmore, & Metzel, 2007). These strategies are most successful when they are embedded within the context of a solid values base, a network of dedicated stakeholders, and clarity about systemic goals.

Community-based non-work (CBNW). As an emerging service model, reported participation in CBNW has grown steadily over the past 15 years. Thirty-eight state ID/DD agencies that reported CBNW services indicated that that 36.2 percent of those served participated in FY2008. Results from a module in the 2001 survey of state ID/DD agencies indicated that CBNW (activities that do not involve paid employment and take place in the community) is loosely defined with respect to requirements, activities, populations served, and goals (Sulewski, Butterworth, & Gilmore, 2006). Although CBNW has the potential to enhance the lives of people with disabilities, these findings raise concerns, including how CBNW services can be provided without taking resources or focus away from expanding integrated employment (Sulewski, Butterworth, & Gilmore, 2006) and the extent to which CBNW services support true community inclusion. CRPs, for example, have indicated that they more often support group and disability-specific community-based non-work activities compared with other more individualized and integrated activities (Sullivan, Boeltzig, Metzel, Butterworth, & Gilmore, 2004), and it is unclear to what extent the growth in CBNW merely represents a redefinition of day habilitation and other non-work service models.

Collaboration with VR. While policy under the Medicaid Home and Community Based Waiver program requires that states refer individuals to VR for employment support prior to providing ID/DD agency supports under waiver funding, collaboration is impeded by a wide range of systemic barriers, including disagreement about target populations, differing commitment to the goal of employment, differences in language and culture, and differences in resource availability (Timmons, Cohen, & Fesko, 2004; Timmons, Fesko, & Cohen, 2004). Despite such barriers, collaborative initiatives between VR and ID/DD agencies are an important element in supporting stronger employment outcomes (Boeltzig, Timmons, & Marrone, 2008; Hall, Boeltzig, Hamner, Timmons, & Fesko, 2006).

CRPs and integrated employment. Considerable variation exists industry-wide in the quality of CRP service provision (Surdick, Pierson, Menz, Hagen-Foley, & Ussif, n.d.). Some providers have successfully shifted emphasis to integrated employment support, including closing one or more facility-based programs (Brooks-Lane, Hutcheson, & Revell, 2005; Butterworth, Fesko, & Ma, 2000). Butterworth, Gilmore, Timmons, Inge, and Revell (2007) found that smaller organizations (those serving one to 40 individuals) had significantly higher rates of participation in individual and integrated employment. In addition, organizations that served all or mostly individuals with ID/DD had significantly lower participation in individual employment and significantly higher participation in sub-minimum wage employment. The survey results also suggest that organizational priorities and goals are critical influences in outcomes and may play a more central role than commonly accepted factors such as fear of benefits loss, family concerns, or transportation availability.

CRPs and direct support personnel. Although researchers have investigated the competencies and training needs of direct support professionals (DSPs) in residential settings (Larson & Hewitt, 2005; Larson, Doljanac, Nord, Salmi, & Hewitt, 2007), very little has been done to examine the same issues regarding DSPs who assist job seekers with disabilities. DSPs in integrated employment face complex responsibilities, ranging from dealing with the dynamics of a business world driven by profit to addressing people with disabilities’ personal needs (Fesko & Temelini, 1997; Test, Flowers, & Hewitt, 2004; Wehman & Targett, 2001). Expanding knowledge about the roles and competencies of DSPs in employment is an area in need of further research.

Individual and family factors. Research has demonstrated that wages and hours worked increase dramatically as individuals move from facility-based to integrated employment and suggests that less tangible benefits include expanded social relationships, heightened self-determination, and more typical job acquisition and job roles (Cohen, 2005; Mank, 2003; Murphy, Rogan, Handley, Kincaid, & Royce-Davis, 2002). Despite these advantages, individuals continue to enter facility-based and non-work services at a higher rate than integrated employment. Researchers investigated what factors influence adults with ID/DD and their families to choose a facility-based setting over community-based employment (Migliore, Grossi, Mank, & Rogan, 2007; Migliore, Mank, Grossi, & Rogan, 2007), and found that the majority of respondents would at least consider community employment. Long-term placement, safety, and social environment emerged as the most important concerns when choosing an employment setting.

Methodology

For the past 20 years, the Access to Integrated Employment project, funded by the Administration on Developmental Disabilities, has described the nature of day and employment services for individuals with intellectual and developmental disabilities, and contributed to a comprehensive understanding of the factors that influence employment outcomes at an individual, service provider, and state policy level. This report provides statistics over twenty years from several national data sets that address the status of employment and economic self-sufficiency for individuals with intellectual and developmental disabilities.

Readers should note the authors use abbreviations for both intellectual disability (ID) and intellectual and developmental disabilities (ID/DD) in this report. We do this because data sources used in this report allow us to look at these two distinct groups at different levels of specificity.
We provide a comprehensive overview that describes national trends in employment for people with ID/DD, and the Appendix provides individual state profiles with data from five sources: ICI’s ID/DD Agency National Survey of Day and Employment Programs for People with Developmental Disabilities from FY1999, 2001, 2004, 2007, and 2008, and datasets from the Social Security Administration, Vocational Rehabilitation, Bureau of Labor Statistics, and the American Community Survey. The Appendix provides a state by state analysis of trends across each data set.

The topical chapter included in this report is intended to shed light on employment data from a different perspective. Accompanying the national large-scale data sets that are presented in this book, we offer a qualitative, in-depth look into how employment data is collected and used throughout multiple levels within state ID/DD systems and recommend a call for national standards for data collection and reporting around employment outcomes.

Data Sources

Data source: ID/DD Agency National Survey of Day and Employment Programs for People with Developmental Disabilities

The National Survey of Day and Employment Programs for People with Developmental Disabilities is a longitudinal study commissioned by the Administration on Developmental Disabilities to analyze community-based day and employment service trends between FY1988 and FY2008 for individuals with intellectual and developmental disabilities and closely related conditions. Between 1988 and 2004 the survey was administered on a semi-annual basis, however beginning with 2007 information is collected on an annual basis. The most recent version of the survey is focused on state ID/DD agency data for fiscal year 2008.

The survey is designed to provide the following information:

The survey has been developed with input and field testing support from state ID/DD agency administrators. Core survey variables include the number served (total and by day and employment service categories), waiting lists, and expenditures by service and total funding by source. All questions focus on community-based day or employment services monitored by the state ID/DD agency, including services funded by another state agency (such as the Medicaid agency), even if the ID/DD agency does not provide or directly contract for the service. These items have not been changed since 1996, when the new category of community-based non-work service was added. Beginning in FY2001, states were offered the opportunity to complete the survey using a secure website. On the website, the states’ previous year’s response is listed for reference and updating if necessary.

The survey was most recently administered in May 2009 to ID/DD agencies in all 50 states and the District of Columbia. The agency director from each state and the staff members who responded to the previous survey were contacted when the survey was first implemented. The previous respondents are contacted to ensure consistency in the data reported. Initial contact was made by email and follow up was completed via email and telephone.

For the most recent survey, states were asked to complete the survey using data from FY2008. The survey home page provides general information and instructions for completing the survey. Additionally, instructions and guidance for responding to the survey questions are included within each question. The survey requests data on the total number of individuals served; however, if a state does not have the capacity to adjust for individuals who enter or exit the system during a fiscal year and can only provide the number served at the end of the fiscal year (or at some other specific point in time), there is a location on the survey to provide this information. Each step of the survey provides an opportunity for states to enter explanatory comments on their data. The final step of the survey offers states the opportunity to make suggestions for how the survey could be revised in the future. States are also asked to identify the information source used to provide service category data. There is a definition page that can be referred to from any page of the survey. A summary of the service category definitions can be found in Table 1. States could also amend their FY2007 data by clicking the “Edit 2007 Values” link at the bottom of the page. Lastly, after a state has finalized their response to the survey, ICI staff review the data and follow-up with states whose data shows an unexpected increase or decrease in the total number served, number served in a service category, or total funding.

Table 1: ID/DD Survey Service Definitions

Type of Setting/ Service: Work Nonwork
Community Integrated employment: Integrated employment services are provided in a community setting and involve paid employment of the participant. Specifically, integrated employment includes competitive employment, individual supported employment, group supported employment, and self-employment supports. Community-based nonwork: Community-based nonwork includes all services that are focused on supporting people with disabilities to access community activities in settings where most people do not have disabilities. It does not include paid employment.
Facility Facility-based work: Facility-based work includes all employment services which occur in a setting where the majority of employees have a disability. These activities occur in settings where continuous job-related supports and supervision are provided to all workers with disabilities. This service category is typically referred to as a Sheltered Workshop, Work Activity Center, or Extended Employment program. Facility-based nonwork: Facility-based nonwork includes all services that are located in a setting where the majority of participants have a disability and does not involve paid employment of the participant.

Estimation of number served. This report used regression analysis to estimate the total number of individuals served by state ID/DD agencies and the number of individuals served in integrated employment when these figures were not reported by states. However, estimations were only accepted when valid data were available at the two margins of the data series, and one of the following three guidelines were met: at least five out of ten data points were available; at least four out of ten data points were available but two pairs of valid data points were symmetrically distributed around the middle of the time series; or at least three valid data points were available and the third valid data point was the median point in the data series. Eleven states did not meet these criteria; therefore, an additional data point for the year 2006 was included from the literature (Braddock, Hemp, & Rizzolo, 2008), which allowed for an estimation to be computed. After visual analysis of the trend lines, all estimates were accepted. Estimates were computed using SPSS v17.

Data Source: Rehabilitation Services Administration 911(RSA-911) database

The RSA-911 is a public access database that captures individual characteristics, services provided, and employment outcomes at the point of closure from Vocational Rehabilitation services. Records are at the individual level, covering over 600,000 case closures per year.

Table 2: RSA Service Definitions

Term Explanation
Closure Data in the RSA-911 are collected at the time of closure (conclusion) of VR services. The VR closure categories used in this report include Closure with an Employment Outcome after receiving services (formerly Status 26) and Closure without an Employment Outcome after receiving services (formerly Status 28).
Successful rehabilitation Closure with an Employment Outcome including integrated employment (including supported employment), self-employment, state agency-managed business enterprise, homemaker, and unpaid family worker.
Rehabilitation rate The percentage of individuals receiving services who achieve a successful rehabilitation. Calculated as:
closures with an employment outcome / closures with an employment outcome + closures without an employment outcome after receiving services.
Supported employment services Supported employment may be funded from Title VI-b funds, funds dedicated to supported employment under the Rehabilitation Act, or from general rehabilitation funds.


Data Source: American Community Survey

The American Community Survey (ACS) is a national survey designed by the U.S. Census Bureau to better understand changing communities. The ACS collects information from all 50 states and D.C. on topics such as disability, age, race, income, commute time to work, home value, veteran status, and other demographic and personal data.
(source: www.census.gov).

Table 3: ACS Service Definitions

Term Explanation
Employment rate The percent of working-age (16-64 years old) individuals who have a job.
Disability categories The ACS classifies individuals as having a disability based on

presence of a long lasting condition in two categories:

Blindness, deafness, or a severe vision or hearing impairment (sensory disability).

Substantial limitation in the ability to perform basic physical activities, such as walking, climbing stairs, reaching, lifting, or carrying (physical disability).

Or because of a physical, mental, or emotional condition lasting six months or more that causes the person to have difficulty doing any of the following activities:

Difficulty learning, remembering, or concentrating (mental disability).

Difficulty dressing, bathing, or getting around inside the home (self-care disability).

Difficulty going outside the home alone to shop or visit a doctor’s office (go-outside-the-home disability).

Difficulty working at a job or business (employment disability).



Data Source: Social Security Administration (SSA)

These data are abstracted from the annual SSA report, “SSI Disabled Recipients Who Work.” The SSA reports work incentive participation and the number of individuals on SSI who are working.

Table 4: Work Incentive Program Definitions

Program Definition
Plan for Achieving Self Support (PASS) Allows a person with a disability or a person who is blind to set aside income or resources to support achieving a specific work goal. Money set aside under a PASS plan is excluded both as current income and from the SSI resource limits.
Impairment-Related Work Expense (IRWE) Allows people to exclude the cost of certain impairment-related services or items needed to earn income when determining the beneficiary’s current earned income for SSI eligibility and benefits.
Section 1619(a) Allows people with disabilities to continue receiving SSI income even if their earned income is at Substantial Gainful Activity (SGA) levels, i.e. the amount that would normally make them ineligible for SSI.
Section 1619(b) Allows individuals to continue receiving Medicaid benefits if their earnings disqualify them from eligibility for SSI cash payments but are not enough to afford medical insurance.

Data Source: State Demographics

State demographics are from multiple data sources. State population is taken from the Census web site. Unemployment data is taken from the Bureau of Labor Statistics web site, and earnings data is taken from the Bureau of Economic Analysis’s website.

National Trends in Employment

ID/DD Agency National Survey of Day and Employment Programs for People with Developmental Disabilities

The data reported here are the core elements of the Institute for Community Inclusion’s ID/DD Agency National Survey of Day and Employment Programs for People with Developmental Disabilities. These data focus on participation in integrated employment, community-based non-work, and facility-based services. Data are solicited from the 50 states and the District of Columbia. The number of reporting states varied from 37 to 45 over the time studied, with data projection used to estimate national totals for service participation. For some states, data reported by service setting represent duplicated counts because individuals were served in multiple settings. For these states, the percentage served across settings may add to more than 100 percent. In addition, other services, including services for individuals who are elderly, are not reported.

Major findings include the following:

Figure 1. Trend line for estimated total number of persons served by state ID/DD agencies and estimated number served in integrated employment

Figure 1. Trend line for estimated total number of persons served by state ID/DD agencies and estimated number served in integrated employment

* Represents a year when the ID/DD Agency National Survey of Day and Employment Programs for
People with Developmental Disabilities was administered

In Fiscal Year (FY) 2008, an estimated 550,818 individuals received day or employment supports from state intellectual disability/developmental disability (ID/DD) program agencies. This number grew from 458,646 in FY1999. The estimated number of individuals supported in integrated employment services increased from 108,804 in FY1999 to 120,691 in FY2008. State investment in supports continues to emphasize facility-based and non-work services rather than integrated employment services.

Table 5. Participation in day and employment services in FY2008

State Total Served Integrated Employment (%)v Community- based Nonwork (%) Combined Facility-based Settings (%)
AK 1,544 23.5 0 77
AL 5,274 4.5 0 95
AR 1,397 5 0 95
AZ 7,689 20.5 0 80
CA 69,944 15 69 16
CO 5,623 27 56 65
CT 8,801 55 44 7
DC 1,490 9.5 16 69
DE 1,931 21 0 76
FL * * * *
GA 10,957 17 56.5 26
HI 2,643 8.5 91.5† -
IA * * * *
ID 6,502 5 79.5 57
IL 28,559 11 0 89
IN 92,18 32 22 45
KS 5,955 19 55 81
KY 5,301 22.5 43.5 70
LA 3,891 33.5 1 39
MA 15,012 25.5 11.5 63
MD 10,085 39 - -
ME * * * *
MI * * * *
MN 12,561 16.5 0 85
MO 4,862 7.5 4 88
MS 5,910 6.5 70.5 40
MT * * * *
NC 14,150 20 51 45
ND * * * *
NE 3,712 33 0 77
NH 2,275 46 50.5 3
NJ * * * *
NM 3,108 43.5 28.5 69
NV 1,998 20.5 1 78
NY 56,536 15 68.5 30
OH 31,485 22 4.5 66
OK 4,704 55 27.5 49
OR 3,892 25 0 71
PA * * * *
RI * * * *
SC 8,753 26 0 74
SD 2,089 26 27 111
TN 7,917‡ 20 - -
TX 34,713 8§ 26.5 47
UT 2,823 38 69 0
VA 11,268 22.5 2.5 75
VT 2,336 38.5 61.5 0
WA 8,273 87.5** 4 10
WI * * * *
WV * * * *
WY 1,274 19.5 16 64

Figure 2 shows the trends in estimated percentage of people served in integrated employment and facility-based and non-work settings between FY1999 and FY2008. In FY2008, an estimated 21.9 percent of individuals receiving day supports from state ID/DD agencies received integrated employment services, while an estimated 84 percent of individuals were supported in facility-based and non-work services. The data demonstrate a decline in the estimated percentage of people served in integrated employment services (from 23.7 percent in 1999 to 21.9 percent in 2008), suggesting that the growth seen in supported employment between the mid-1980s and mid-1990s has not continued. The data also demonstrate an increase in the estimated percentage of people served in facility-based and non-work settings (from 78 percent in 1999 to 84 percent in 2008). While variability in the number of states who are able to report data for the individual service categories for facility-based work, facility based non-work, and community-based non-work limits the conclusions that can be drawn regarding the specific setting in which growth is occurring, analysis using data from states who reported data for each of these categories shows that the percentage of individuals served in facility-based work and facility-based non-work settings is decreasing, while the percentage served in community-based non-work services appears to be expanding.

Figure 2: Estimated ID/DD Agency Service Distribution by Service Category by Year*

Figure 2: Estimated ID/DD Agency Service Distribution by Service Category by Year*

*(Data for RI could not be included in the estimates for these years)

Presently, states vary in their ability to report on funding for day and employment services by service setting. The number of states reporting funding by setting has increased since these data points were first added to the national survey for FY1996. Figure 3 shows trends in funding allocation by service setting for states that reported these monetary figures. Facility-based and non-work settings continue to make up the largest percentage of expenditures for day and employment services. Collectively, states that reported funding for all facility-based work and non-work services (n=16) allocated 90.3 percent of the funding for day and employment to services in these settings in FY2008. Alternatively, states that reported funding for integrated employment (n=29) allocated 11.6 percent of the funding for day and employment to services to integrated employment in FY2008. While there has been a net decrease in the percentage of reported funds allocated toward facility-based work and non-work services since 1999, there has been little fluctuation over time in the percentage of funding allocated toward integrated employment which peaked in 2001 at 16.6 percent but otherwise ranged between 9.6 and 12.7 percent in all other years since 1999.

Figure 3: Percentage of Total Funding Allocation by Year (Number of States Reporting in Parenthesis)

Figure 3: Percentage of Total Funding Allocation by Year

Growth in community-based non-work.

Nationally, the reported participation in community-based non-work services has grown steadily for states that report it as a service, from 18.7 percent in FY1999 to 36.2 percent in FY2008. First added to the survey as a service option in FY1996 in response to state feedback, the number of states reporting individuals in community-based non-work has grown from 18 in FY1996 to 38 in FY2008 (see Table 5). Community-based non-work services accounted for over 50 percent of state ID/DD agency expenditures for FY2008, for states that reported expenditures for this service (n=23). The rapid growth in community-based non-work services may reflect a growing emphasis on community presence, although the contribution of this service to community participation remains unclear. There is currently limited data on the structure, activities, and outcomes of this service, and states have not established clear service expectations or quality assurance strategies (Sullivan, Boeltzig, Metzel, Butterworth, & Gilmore, 2004). While some states report service requirements about how much time CBNW participants spend in the community, it is possible that in some cases states have reclassified services from facility-based to community-based as the emphasis on community participation grows even though substantial time is still spent in facility-based settings.

Funding from State, County, and Local Sources.

State, County, and Local ID/DD dollars are one of the largest sources of funds for day and employment services; additionally, as a funding source that is directly controlled within each state, it is one of the most flexible sources of dollars for day and employment services. Similar to funding by service category, states vary in their ability to report state, county, and local spending on ID/DD services. As the number of states able to report these figures increases, it will be interesting to examine both the cross-sectional and trend data for this type of funding. For states that have been able to report these figures, the allocation of these funds varied based upon year and service category: integrated employment, community based non-work, facility-based work, and facility-based non-work.

Total reported state, county, and local ID/DD dollars have decreased slightly from $1,480,531,831 (n=25) to $1,401,106,179 (n=26) between 1999 and 2008. The percentage of funds allocated to all facility-based services declined from 65 percent in 1999 to 31.5 percent in 2008 but did not result in a substantial increase in funds being allocated toward integrated employment; instead dollars have shifted toward community based non-work services. Reported dollars for community-based non-work increased from $279,490,187 (n=13) to $422,014,459 (n=14) between 1999 and 2008. This change coincided with a decrease in the funds allocated toward facility-based non-work services from $470,893,634 (n=16) to $40,652,812 (n=13). One potential explanation for the significant redistribution of funds toward community based non-work services is that traditional facility-based non-work services are being rebranded as community based non-work services.

Since 2004 there has been an increase in the percentage of state, county, and local ID/DD funds allocated toward all community based services. While this is hopeful and could be an indication that states are placing a greater emphasis on community inclusion, ultimately state, county, and local ID/DD dollars are increasingly being spent on community-based non-work services and not integrated employment. The trend toward community-based non-work services raises concerns about the clarity of the service system’s goals for community employment. It is highly likely due to the lack of specificity of the goals of community-based non-work services (Sulewski, Butterworth & Gilmore, 2006) that as funds transition to the community, non-work services are seen as an alternative rather than a complement to integrated employment services. Sulewski, Butterworth, and Gilmore (2008) recommend that states use community-based non-work services as a supplement to integrated employment services and not as a substitute for employment. States need to clarify the intent and goals of community-based non-work services and their relationship to integrated employment.

Trends in Rehabilitation Services Administration outcomes for individuals with ID/DD (1995–2008)

This section describes trends in outcomes of the VR program for adults with intellectual and developmental disabilities (ID/DD) during the period of fiscal years 1995 to 2008.

In summary:

Most VR closures with ID/DD have an intellectual disability.

In 2008, 83 percent of the VR closures for people with ID/DD were of people with intellectual disabilities; 6 percent of closures were for people with epilepsy; 7 percent for people with cerebral palsy, and 4 percent for people with autism. The percentage of closures for people with epilepsy declined from 10 percent in 1995 to 6 percent in 2008, and the percent of closures for people with autism increased from 1 percent in 1995 to 4 percent in 2008.

The majority of VR closures with ID/DD are individuals who were transition age during their time in VR.

The majority of VR customers with ID/DD were male (58 percent), and the average age at application was 27. Of all the closures in 2008, 59 percent were between 16 and 26 years old at the point when they closed out of VR services. This figure increased over the years from 37,713 (53 percent) in 1995 to 42,736 (41 percent) in 2008. Most closures with ID/DD in 2008 involved people of white ethnicity (69 percent).

Whereas the overall number of closures with ID/DD remained relatively constant, the number of closures in employment declined.

In 2008, VR closed 72,541 cases for people with ID/DD, of which 27,153 were closures in employment, a figure 15 percent smaller than in 1995. The decline occurred mostly between 2001 (N = 33,485) and 2002 (N = 29,992), when VR discontinued counting extended employment (sheltered workshop) as an employment outcome.

VR outcomes vary substantially across states.

Table 6: VR Outcomes for Individuals with ID/DD across States and DC in FY2008

State Total closures Rehabilitation rate (%)* Weekly earnings (in dollars) Weekly
hours
Minimum 77 34 151 18
Maximum 7,239 85 313 32
Mean 1.422 57 216 26
Median 947 62 220 26
AK 176 66 272 25
AL 1,856 68 218 30
AR 741 34 313 31
AZ 773 52 282 28
CA 7,239 49 225 28
CO 1,107 64 196 22
CT 454 47 286 26
DC 77 70 286 31
DE 252 74 241 28
FL 2,411 44 191 24
GA 2,848 57 253 32
HI 163 54 233 26
IA 1,158 64 275 29
ID 575 67 158 21
IL 3,194 61 220 24
IN 2,474 53 178 23
KS 998 60 192 25
KY 1,482 67 222 25
LA 1,185 40 198 26
MA 947 64 227 22
MD 770 82 256 26
ME 530 61 201 21
MI 2,302 51 192 23
MN 1,313 67 239 26
MO 3,038 72 211 27
MS 823 50 235 30
MT 332 60 151 19
NC 3,757 62 192 25
ND 203 71 215 27
NE 339 65 238 29
NH 239 77 178 20
NJ 1,177 59 249 25
NM 406 64 195 22
NV 228 64 233 27
NY 3,938 57 204 23
OH 3,307 53 224 27
OK 569 53 251 29
OR 1,164 61 228 24
PA 2,601 58 243 27
RI 291 62 185 21
SC 895 47 259 32
SD 469 74 194 26
TN 3,092 35 164 22
TX 3,732 56 238 27
UT 494 71 217 24
VA 2,020 62 214 27
VT 384 85 160 18
WA 1,750 68 189 20
WI 1,563 52 192 22
WV 540 63 235 26
WY 165 78 167 20

Table 6 shows that the VR outcomes varied substantially across the 50 states and the District of Columbia (FY2008). The rehabilitation rate, for instance, ranged between 34 percent in Arkansas and 85 percent in Vermont (mean = 57 percent). The rehabilitation rate is calculated as closures with an employment outcome / closures with an employment outcome + closures without an employment outcome after receiving services. Weekly earnings at closure ranged from $151 in Montana to $313 in the Arkansas (mean = $216). Finally, the weekly work hours varied from 18 in Vermont to 32 in Georgia and South Carolina (mean = 26). The fact that Vermont had the highest rehabilitation rate while at the same time having the lowest hours per week worked and third lowest earnings per week ($160) underscores that importance of looking at multiple employment outcomes and data elements to get a full understanding of what is happening in a particular area. Though a greater percentage of consumers in Vermont are getting jobs, these jobs appear to offer fewer hours and lower earnings potential than ones in other states.

VR engagement varies substantially across states.

According to Hayward and Schmidt-Davis (2003), only about a third of people with disabilities who potentially could benefit from the Vocational Rehabilitation (VR) program receive its services. Here we describe engagement of the VR program at the state level in FY2007. Data for 2007 is used because data for 2008 was unavailable at the point when this research was conducted. Our goal is to increase understanding about whether people with ID/DD have similar chances of receiving employment services through the VR program across the nation.

We define engagement of the VR program as the number of closures––with or without employment––per 100,000 people in the state general population. Moreover, we define above average engagement as engagement falling one standard deviation above the mean and below average engagement as engagement falling one standard deviation below the mean.

Table 7 shows that, in 2007, seven state VR agencies (14 percent) reported above-average engagement ranging from 41 to 63 (*). At the other end of the spectrum, eight state VR agencies (16 percent) reported below-average engagement ranging from 9 to 15 (**). The highest level of engagement—63 in Vermont—was seven times greater than the lowest figure of 9 in Nevada (M=28, SD=12).

The variation of VR engagement raises the question about the extent to which lower levels of VR engagement in some states are offset by other federal, state, or local agencies’ services. Addressing this question would be important in order to make sure that people with disabilities have adequate opportunities to achieve economic self-sufficiency through employment.

Table 7. Engagement of people with ID/DD with state VR programs in FY2007

Closures per
100,000
population		 Closures per
100,000
population
Alabama* 50 Montana 34
Alaska 27 Nebraska 24
Arizona** 12 Nevada** 9
Arkansas 22 New Hampshire 23
California 16 New Jersey** 12
Colorado 17 New Mexico 23
Connecticut** 12 New York 21
Delaware 29 North Carolina* 55
District of Columbia** 12 North Dakota 31
Florida** 13 Ohio 28
Georgia 30 Oklahoma 34
Hawaii 20 Oregon 36
Idaho 38 Pennsylvania 26
Illinois 25 Rhode Island 30
Indiana 40 South Carolina 16
Iowa* 47 South Dakota* 59
Kansas 29 Tennessee 34
Kentucky 34 Texas** 13
Louisiana 20 Utah 21
Maine 32 Vermont* 63
Maryland 17 Virginia 26
Massachusetts** 15 Washington 24
Michigan 23 West Virginia* 41
Minnesota 27 Wisconsin 31
Mississippi 33 Wyoming 25
Missouri* 49 United States 28

Weekly earnings in integrated employment at closure increased slightly, even after adjusting for inflation and in spite of a decline in the weekly work hours. However, earnings are still substantially lower than in the general population.

In 2008, weekly earnings in integrated employment for closures of people with ID/DD averaged $216; on average, weekly hours worked was 26. The highest average number of work hours per week was 28.5 in 1995 (M = 27.2; SD = 0.8).

It is noteworthy that, as Figure 4 shows, the gap between earnings of adults with ID/DD at closure and personal income in the general population is very large and widening slightly over time.

Figure 4: Inflation-adjusted weekly earnings at closure and per capita income

Figure 4: Inflation-adjusted weekly earnings at closure and per capita income

The time from application to closure in integrated employment increased.

VR typically closes cases when applicants have been employed for at least 90 days. In 2008, each closure in integrated employment required 718 days on average from the time of application. This figure was the greatest over the period studied, whereas the smallest figure was 673 days in 2003 (M = 698; SD = 14). The average number of days from application to closure was substantially smaller if applicants who received postsecondary services or who already had a job at the time of application are excluded (559 days in 2008).

Trends in American Community Survey (ACS) Data (2000–2007)

Data show that people with disabilities are consistently less likely to be working than their non-disabled counterparts. This data set allows us to compare employment participation and outcomes for civilian working-age people with and without disabilities, and provides a population estimate that includes people who do not receive formal supports from a human service agency. We define “working-age” as civilian non-institutionalized people ages 16-64. The employment rate is calculated by dividing the number of people who are employed by the total civilian working-age population in the state. The data presented below will emphasize the ACS disability category of mental disability as the closest proxy for individuals with intellectual and developmental disabilities.

Five major trends emerged in the data set:

Among working-age Americans, people with any disability and people with a mental disability are more likely to live in a household that is below the poverty line than people without a disability.

In 2007, only 5.3 percent of people without a disability lived in a household that was below the poverty line. The percentage of people living in a household below the poverty line increased to 10.6 percent for people with any disability and 14.1 percent for people with a mental disability.

Employment declined for individuals with any disability, and for individuals reporting a mental disability.

In 2000, 48.3 percent of those reporting any disability were employed. By 2007, only 36.2 percent of individuals with any disability were working, with the biggest decrease occurring between 2002 and 2003 (from 44.2 percent to 37.3 percent). The percent of those with a mental disability that were employed decreased steadily from 33 percent in 2000 to 27.5 percent in 2007. In contrast, the percentage of all people employed who reported that they do not have a disability decreased only slightly, from 75.4 percent to 75.1 percent between 2000 and 2007.

While earnings increased overall, wages for individuals with any disability and individuals reporting a mental disability increased at a much lower rate than for individuals without a reported disability. Mean weekly hours worked declined slightly for people with any disability and those with a mental disability.

Weekly earnings from employment increased from $735 in 2000 to $908 in 2007 for all working-age people with no disabilities. Weekly earnings for people with any disability increased from $626 in 2000 to $710 in 2007. Earnings for people with a mental disability increased only slightly from $530 in 2000 to $561 in 2007. Mean weekly hours worked remained consistent, at 40 hours in 2000 and 2007 for all working-age residents without a reported disability. For people reporting any disability, the number declined from 38 to 37 during the same time period, while those with a mental disability reported a decline from 35 to 34 hours. In addition to having lower average earnings and working fewer hours per week on average, people with any disability and with a mental disability worked fewer weeks out of the year, on average, than people without a disability. Thus, in addition to having lower average weekly earnings, they also have disproportionately low annual earnings from employment because of working less frequently.

Indicators of labor market success

In assessing employment outcomes, it is important to review multiple indicators to get a full understanding of the employment experiences of people with disabilities. Indicators commonly used in labor market and population studies include:

Employed: People with jobs.

Unemployed: People who do not have jobs and have actively looked for work in the past four weeks.

Not in the Labor Force: People who do not have jobs and have not actively look for work in the past four weeks.

Employment Rate: Number of people employed / Labor Force

Unemployment Rate: Number unemployed / (number employed + number unemployed)

Reporting meaningful indicators of labor market success for individuals with disabilities, particularly ID/DD, is challenging for a number of reasons. Measures that allow people to indicate specific disabilities like ID are uncommon in large national data sets. Additionally, the use of the “traditional” unemployment rate reported by the Department of Labor as an indicator of labor market success for people with disabilities leaves people who are not in the labor force, a significant group when it comes to subpopulations of people with disabilities, out of the calculation.

While the ACS does not collect information on people with ID/DD specifically, it does allow people to self-report on six disability questions. Any individual who answers yes to one or more of these six items is categorized as having any disability. Someone with a mental disability is anyone who indicates that, because of a physical, mental, or emotional condition lasting six months or more, they have difficulty learning, remembering, and concentrating. The table below displays indicators of labor market success for four groups of civilian, non-institutionalized, working-age individuals: People who do not have a disability, people who indicated they have at least one disability (Any Disability), people with a mental disability, and people with a mental disability who received Supplemental Security Income (SSI) in 2007. This last group is likely to include people who have the most significant mental disabilities. The table also displays the unemployment rate as traditionally calculated for these same groups.

Table 8. Labor Market Success Indicators by Disability Status: 2007

No Disability (%) Any Disability (%) Mental Disability (%) Mental Disability with SSI Income (%)
A. Percentage Employed 75 36 28 9
B. Percentage Unemployed 5 6 6 3
C. Percentage Not in the Labor Force 20 58 66 88
Total (A+B+C) 100 100 100 100
Unemployment Rate (number unemployed / number employed + number unemployed) 6 14 19 23

The table confirms the low levels of participation in employment for individuals with disabilities. People with disabilities are employed at much lower rates than those without disabilities, and across disability categories all are much less likely to be in the labor force than people without disabilities. Individuals with disabilities also fare poorly using the calculation of unemployment rate. People with mental disabilities who receive SSI have the lowest employment rate (percentage employed) with only 9 percent of individuals in this group being employed. While the most striking differences are in overall employment participation, unemployment rates for people with disabilities who are in the labor force are two to three times the unemployment rate for people without disabilities. These figures may reflect a longer job search and the difficulty individuals with disabilities face in reentering the workforce after a job loss.

These data suggest the importance of examining both the percentage employed, percentage unemployed, and percentage not in the labor force (indicators A, B, and C in Table 8), and the unemployment rate in order to gain a full understanding of the employment experiences of individuals with disabilities. It is important to note these figures are from a period that was before the recent economic downturn. The recent availability of similar data from the Bureau of Labor Statistics using data from the Current Population Survey provides an opportunity to examine national trends in these figures on a monthly basis. The sample for the Current Population Survey, however, is too small to allow for employment estimates at the state level. The larger sample size of the ACS allows analysis at the state level.

Trends in Social Security Administration Data (1991–2007)

The Supplemental Security Income program (SSI) administered by the Social Security Administration provides cash assistance to low-income individuals who are seniors, blind, or have a disability. Analysis of this dataset revealed two key findings:

Work incentives remain largely underutilized.

Congress has enacted a number of work incentive programs for Supplemental Security Income (SSI) recipients with disabilities after concluding additional incentives were necessary to help individuals become self-supporting. Moreover, Congress has noted that individuals who could work outside of sheltered workshops might have been discouraged from doing so by the fear of losing their benefits before they had established for themselves the capability for continued self-support.

To encourage employment for individuals with disabilities, the Social Security Administration (SSA) offers special provisions that limit the impact of earnings from work on eligibility for Social Security Disability Insurance (SSDI) or Supplemental Security Income (SSI) benefits. These work incentives include the Plan to Achieve Self-Support (PASS), Impairment-related Work Expenses (IRWE), Blind Work Expenses (BWE), and section 1619(a) and 1619(b) benefits.

PASS, IRWE, and BWE allow individuals to set aside money, resources, and expenses to be excluded from total earned income calculations. PASS allows people to set aside money and resources to be used for attaining a work goal such as going back to school, finding a better job, or starting a business. IRWE allows people to exclude current expenses from income that are necessary for work, such as wheelchairs, transportation, or specialized equipment. BWE allows the exclusion of expenses such as service animals, income taxes, and visual/sensory aids. Section 1619(a) allows people with disabilities to continue receiving SSI income even if their earned income is at Substantial Gainful Activity (SGA) levels, i.e., the amount that would normally make them ineligible for SSI. Section 1619(b) allows individuals to continue receiving Medicaid benefits if their earnings disqualify them from eligibility for SSI cash payments but are not enough to afford medical insurance.

A notable trend is the sharp drop in the number of people enrolled in the PASS program between 1995 and 1997. This decline followed a publication of the General Accounting Office that criticized SSA for being too lenient in accepting applicants into a program they deemed to be ineffective for achieving the goal of self-support. The procedures for acceptance were then reevaluated by SSA and amended, resulting in fewer approvals in subsequent years. Recent data have also shown a decrease in the average number of IRWE and BWE enrollees per state.

Table 9. National Mean Number of People Enrolled per State in Work Incentive Programs from 1991 to 2007

1991 1993 1995 1997 1999 2001 2003 2005 2007
PASS 70 159 202 39 20 31 35 33 34
IRWE 128 169 195 189 187 173 157 129 108
BWE 85 86 87 81 78 71 61 53 45

SSI recipients with ID work more but participate in work incentive programs less frequently than their counterparts with other types of disabilities.

Over one-fifth of all SSI recipients with disabilities ages 18–64 in 2007 (21 percent) were individuals with an intellectual disability. Next to individuals classified as having other mental disorders, this is the largest disability subgroup among SSI recipients. SSI recipients with ID have had relative success with employment outcomes compared to recipients who do not have ID. In 2007 the rate at which SSI recipients with ID worked was more than double that of SSI recipients without ID (15.1 versus 6.2).

As Table 10 shows, SSI recipients with ID participate in the 1619(a) and 1619(b) work incentive programs at lower rates than SSI recipients with other disabilities. SSI recipients with ID participate in the IRWE program at slightly higher rates than recipients with other disabilities. The observation that SSI recipients with ID have better employment outcomes than their counterparts with other disabilities while at the same time participating in certain work incentive programs at much lower rates is an interesting one. It is likely there are a number of factors that explain this. Analysis of other data sources, e.g., the Rehabilitation Services Administration 911, has shown that people with ID often work fewer hours and earn less than individuals from other disability subgroups. If this is the case for SSI recipients with ID, the lower participation in 1619(a) and (b) work incentives could be due to the fact that the individuals do not have earnings close to SGA and are not likely to lose benefits because of earnings.

The low rates of participation should not overshadow the overall impact of the program. For instance, in 2007 section 1619(b) benefits allowed more than 27,000 individuals with ID to continue working and receiving Medicaid benefits. Better explanations of incentives and more encouragement to participate in incentive programs by employment and disability services professionals could lead to better employment for individuals receiving SSI.

Table 10. Employment Outcomes and Participation in Work Incentives for SSI Recipients with Disabilities

Intellectual disability

(%)

 All other disabilities

(%)

Percentage of all SSI recipients with disabilities who work 15.1 6.2
Percentage of all working SSI recipients who work and participate in 1619(a) 3.8 5.6
Percentage of all working SSI recipients who work and participate in 1619(b) 19.8 32.8
Percentage of all working SSI recipients work and participate in IRWE 1.9 1.3


Conclusion

From varying perspectives, each dataset that is included in this report sheds light on the economic disparities that people with intellectual and developmental disabilities have experienced over the past decade and beyond. Many more individuals continue to be supported in facility-based employment, earning sub-minimum wage, than in integrated employment earning a living wage. In the Vocational Rehabilitation (VR) system, earnings of adults with disabilities are substantially lower compared to those in the general population. Moreover, data continues to show that work incentives meant to encourage workforce engagement remain largely underutilized, especially for people with intellectual disabilities.

Overall the findings suggest the need for a renewed and shared focus across several systems:

Multiple data sets offer varying perspectives on the employment situations of individuals with disabilities and specifically intellectual and developmental disabilities. While the data do show some progress within particular systems over time (e.g., the gradual reduction in the number of individuals working in sheltered employment and increased earnings of individuals who are exiting the VR system), there continues to be an urgent need for a re-investment of attention, priority, and resources dedicated toward expanding both economic and employment opportunities for individuals with intellectual and developmental disabilities.

Data Systems and Decision-making:
State ID/DD Agencies and their Employment Data

Allison Hall, Jean Winsor, and John Butterworth

Introduction

The growing emphasis on government accountability at the state and federal levels has increased interest in the collection and use of outcome data. Moreover, research has found that high performing states in integrated employment generally have a clear and visible data collection system that includes individual outcome data (Hall, Butterworth, Winsor, Gilmore, & Metzel, 2007). But what are the most important elements in designing and using a system? Stakeholders have raised questions regarding how to develop and implement an effective data collection system, which variables provide the most utility for influencing policy, and how to use data as a strategic planning tool.

This topical chapter offers a qualitative, in-depth look into how employment data is collected and used throughout multiple levels within state ID/DD systems. This chapter details findings from state-level case studies conducted in four states: Florida, Massachusetts, New Hampshire, and Washington. Case study research focused specifically on the development and use of employment data collection systems and their relationship to priorities, decision-making, and policy development.

Understanding ID/DD data systems

To put this chapter in context, it is useful to understand the national scope of ID/DD data systems as they relate to employment. As a part of the FY2007 National Survey of Day and Employment Programs, data were requested from state intellectual disability and developmental disability (ID/DD) agencies regarding the sources of information used to report the total number of individuals served in the following services categories: integrated employment, facility-based work, community-based non-work, and facility-based non-work. Data on the source of information is an important factor to note when comparing each state’s service outcomes over time (Bhattarai & Winsor 2008). Information on the source of the data can help to explain unexpected trends in state service distribution when the state has not implemented changes in policy or practice. Ensuring that the source of the data used by each state is consistent over time can improve the reliability of longitudinal data. States were given the six choices listed in the table below and asked to identify whether they used each source to complete the service category data and which choice was the primary source of their data. Thirty-seven states responded to the first question. Sixteen of those states used more than one source. However when asked which source was the primary source of data, the majority of states reported that service funding records were their primary source.

Table 11. Sources of data used for reporting outcomes

Data Source Number of states who reported that they used this source (n=37) Number of states who reported using this as their primary source (n=37)
Service funding records (e.g. number receiving funding by service) 26 19
Data collected at the provider level on services provided 17 12
Other sources 8 3
Data collected at the individual level on employment outcomes 7 3
Case management records 6 0
The number of individuals designated for service in provider contracts 4 0

In a secondary question states were asked if they collect data at the individual level on employment outcomes; twenty states reported they collect data at the individual level on employment outcomes. Those states were asked a series of follow-up questions related to data collection on individual integrated employment placements that can be used to assess the quality of the employment outcomes. Of these 20 states, 18 reported the type of data they collect. The most commonly collected data elements were type of job, wages earned, and hours worked (See Table 12).

While there was no correlation between the percentage of individuals a state supported in integrated employment and the specific type of outcome data they collect, 75 percent of states who supported a high percentage (more than 40 percent) of individuals in integrated employment in FY2007 reported collecting information on at least three of the data types. Only 33 percent of states that supported a moderate percentage (between 20 percent and 40 percent) of individuals in integrated employment reported collecting this same number of data types; and for states supporting a low percentage (less than 20 percent) of individuals in integrated employment only 28.5 percent of states collected data on at least three of the data types. This finding is consistent with that of Hall, Butterworth, Winsor, Gilmore, and Metzel (2007), which concluded that ID/DD agencies that consistently produce high rates of integrated employment have implemented statewide outcome data systems to assess the quality of their employment outcomes.

Table 12. Employment outcomes data elements collected at the individual level

Data type Number of states collecting this data (n=18)
Type of jobs (e.g., individual, group supported employment) 16
Wages 16
Hours worked 16
Job tenure/longevity 10
Occupation or industry a person is employed in 10
Source of wages (e.g., employer or provider) 9
Benefits received from employer 8

Methodology

We interviewed stakeholders in 2008 from four states to discuss the strategies, successes and challenges within their employment data collection systems and reviewed state documents related to their data collection systems.

Sample selection. States were selected using a purposeful two-phase sampling strategy that ensured representation across key elements, placing particular emphasis on the design, use, and integration of the state ID/DD agencies’ employment data collection system. In the first phase, a comprehensive document review process was undertaken and included several states which were known to have some type of employment data collection system in place. This knowledge came from past ICI case study research, involvement of some of the states in the State Employment Leadership Network, and ongoing involvement with ICI’s National Survey on Day and Employment Services. These ongoing activities offered enough evidence to be able to list and sort states according to important data-related variables. These states included CT, DE, FL, MA, NH, WV, WI, CO, CA, LA, WA, OR, AZ, NM, TX, and SC. Data from these states were organized into a matrix which sorted data by the following categories: frequency of data collection; population targets for data collection; data elements collected; who is providing the data; how and to what other systems the data is tied; and how data is used and shared across the state. This matrix helped to compare the states across similar variables and allowed the researchers to engage in the second phase of sampling, which involved choosing four of these states that represented a range of data systems and models for use of the data.

Data collection. Researchers used document review and semi-structured interviews to better understand states’ employment data collection systems. First, research staff conducted a review of literature and existing documentation related to data collection systems and strategies. The information obtained was organized within the matrix that provided a platform from which to choose the case study states.

Four states were chosen to participate in more in-depth follow-up interviews. These states were MA, FL, WA, and NH. These states were chosen because they had engaged in strategic efforts to create well-developed data systems to capture integrated employment outcomes, because they offered different approaches to data collection, management and use and because of the lessons they could provide to other states in earlier stages of data system development. In each state, ID/DD central office and regional staff participated in hour-long tape recorded telephone conversations about their data systems. Researchers also interviewed staff from community rehabilitation providers (CRPs) in each state to ensure diverse opinions and perspectives were represented. Interviews with CRP staff focused on their experiences in providing data to their state’s ID/DD agency, and their perceptions on how the data is used. In total, 17 individuals participated in interviews.

Data analysis. Thematic analysis techniques were used to review and analyze the literature, documentation, and data collected, resulting in the development of a matrix on state data collection policies and methodologies. Interview data was analyzed using a qualitative data analysis approach. Individual descriptive case studies of each state’s funding system can be found elsewhere (e.g. Hall, Winsor, Butterworth, 2009, Winsor, Butterworth, Hall, 2009).

Findings

The findings section discusses both concrete strategies that states used in developing their systems, as well as thematic elements that were present across states. The section concludes with a review of the challenges and lessons learned from states as they moved forward in the evolution of their data systems.

Data systems: A reflection of new and ongoing priorities

The core reason these states have implemented and supported data collection systems is to emphasize priorities. States are paying attention to outcome data because they understand that knowing how many people are working is the key to moving an employment agenda forward. Being able to track how many people are both currently working and entering community employment helps states to develop and then understand their progress toward goals. The continued collection of employment data helps to keep the spotlight on employment in a sea of other priorities with which a state ID/DD agency must contend.

Some of the states studied have understood the link between data and priorities for several years, while other systems have only recently begun to emphasize the data collection process. Florida, for instance, developed its data collection system to track the outcomes of its 5 Year Employment Initiative, begun in 2004. Florida’s SETS (Supported Employment Tracking System) was developed to provide a comprehensive and accurate picture of the state’s progress in reaching its goals around employment. Prior to 2004, the state had a data collection system in place but it was less automated and standardized. The new database that is now in place reflects a more defined commitment to accuracy and buy-in from all those involved with employment services.

In 2002, the Massachusetts ID/DD developed a contractual requirement that employment services provider performance be tracked through outcome measures. A new Request for Responses (RFR) for Employment Support Services emphasized robust reporting requirements, and consequently the ID/DD agency shaped its employment data collection system to focus on what it viewed as key outcomes for measuring success around employment. Overall its intrinsic commitment to greater community employment supported the development of an employment data system that focused on individual outcomes.

States like New Hampshire and Washington have been comprehensively collecting employment data for a much longer time. New Hampshire began collecting data in 1994 and has built on lessons learned to make its current system standardized and efficient. The state started with a simple question, “How many people are working?” and evolved the data collection effort to meet the changing needs of its system. The data collection system has continued to allow New Hampshire to keep employment at the forefront of its service delivery goals. Washington’s system is linked to its billing system, emphasizing the state’s long-standing focus on employment outcomes as a systemic priority. The collection of billing and reporting data on individual outcomes is an additional method to ensure that providers are fulfilling their obligation to support individuals in community employment or in services that support the individual’s employment plan.

Data collection strategies

Each state has a structure in place that attempts to standardize how data is collected. However, in some states the details of actually obtaining the data varies by regional office, which was noted by respondents to sometimes have either positive or negative implications.

Florida. In each of Florida’s 14 regions, there is a supported employment (SE) liaison that is responsible for collecting employment data. On a monthly basis, each SE liaison documents the outcomes of individuals within his or her region. This is done through outreach to supported employment service providers and Support Coordinators in the region who are supporting individuals who are employed and receiving services from the state ID/DD agency. The way in which the data is reported at this level varies. Depending on the region and the provider, some providers mail their data, while others use email. In one region, each provider develops their own form based on the data that the SE liaison requests. Providers submit the data to the liaison, and he enters it into a hardcopy book and then into the electronic SETS data systems. In another region, the SE liaison works with her IT staff to get a point-in-time picture of the data at the end of each month, and she works with providers, coordinators, and families to get an accurate update of this data each month. Once she gets the data, she enters it into the SETS database. Additionally, each individual file maintains a completed census form which includes demographic data that does not change month to month.

Massachusetts. In Massachusetts, data are collected once per year during a four-week period in April. Providers receive a spreadsheet preloaded with names, ID numbers and contract numbers for the individuals they support. For each individual, the provider enters cumulative information for the four-week period. Historically, this information was then loaded onto a CD and sent to the ID/DD agency. For the FY2009 data collection, a web system was developed to allow providers to report data directly to the ICI through a secure web interface. Providers are required to submit this annual data as part of their provider contracts. Initially the ID/DD agency was collecting data twice per year, but then subsequently moved to an annual collection to reduce the burden on providers and the Department.

The ID/DD agency passes the data on to staff at the Institute for Community Inclusion, their local University Center of Excellence in Developmental Disabilities, UCEDD, who manage and clean the data and flag issues for follow-up. Follow up and clarification of the data with providers is done by ID/DD agency staff.

New Hampshire. In New Hampshire, employment providers must submit the data to their Area Agency (10 throughout the state), who enter the data into the statewide employment database, and export the data to the state ID/DD agency. For individuals who direct their own services employment data is completed by case managers who manage their service funds. Data is collected on all jobs in New Hampshire, including those in sheltered workshops.

The first time employment data is collected on an individual both the demographic and employment sections of the survey must be completed. For subsequent collection periods Area Agencies print out the last employment survey for each individual and ask provider staff to update the data. The data reported on hours worked and wages earned is reported as an average for the six month period. After all necessary changes have been made, the employment surveys are returned to the Area Agency. When employment vendors supply data that looks inaccurate or incomplete, Area Agency staff contact the providers for clarification prior to exporting the data to the ID/DD agency. Area Agencies have 40 days after the end of the data reporting period to export their data. To ensure that the exported data remains confidential, the ID/DD agency assigns each individual a code number. Once the exported data is received, the system is automatically linked to the coded individual database at the ID/DD agency’s central office.

Washington. In Washington, state counties are responsible for contracting with vendors to provide day and employment services. The data collection system is an integral part of the billing reporting process that vendors, counties, and the ID/DD agency engage in to fund services. Vendors provide outcome data on the activities for each individual for the billing month. The vendor or a county ID/DD agency staff member enters the data into an excel spreadsheet, which is then uploaded to the state ID/DD office. This data is used by the state ID/DD agency to reimburse counties for the services that they have paid vendors to provide.

Data shapes relationships with providers

The data collection process helps providers and the state ID/DD agency to connect in many ways around the goals of employment. The actual implementation of the data collection process establishes a regular and consistent dialogue between providers and the ID/DD agency, and supports providers to understand and work toward the shared goal of increased employment.

Frequency and consistency of data collection helps to cement relationships. Frequent data collection in Florida was seen as a tool to foster relationships with providers and keep them familiar with the data collection process. Having one point person, a Supported Employment liaison, consistently collect data on a monthly basis from providers lets them know that it is a top priority for the Florida’s ID/DD agency, so that providers and the ID/DD agency can have a shared understanding about the importance of data in achieving the system’s goals. In addition, regular interaction with providers helps to give the SE liaison a month-to-month compass point on the progress providers are making toward their goals.

Outcome data helps providers to become more in tune with their role in increasing employment outcomes. Having conversations with providers about the data is key in helping them to establish a more proactive role in a state’s employment agenda. These conversations were taking place during the data collection period, such as was the case in Florida, but more likely they were occurring after the data had been analyzed and was being presented back to providers.

In one local area in Florida, a Supported Employment liaison felt the monthly data collection contact she has with providers is a direct entrée to talk about questions or concerns regarding progress toward employment goals. She uses the consistent check-ins as built-in opportunities for training and technical assistance in specific areas. These conversations can equip providers with the tools they need to increase their employment outcomes.

In Washington, several counties have used their systems’ data to identify weaknesses within their contracted provider agencies and develop plans to correct the problems; and as a way to supply feedback to providers about the amount and types of employment outcomes they have provided. A county noted that they have used the data to have conversations with providers about the relationship between services and outcomes. One respondent felt that providers appreciated that the data was being shared with them, reinforcing the sense of ownership providers feel about the types of outcomes they produce. Washington is the only state where, in some counties, they share provider-level data among providers, creating a sense of awareness and competition among providers. Other states do it at a regional or county level.

Going a step further, other states are using the data for more direct accountability from providers. In Massachusetts, when the ID/DD agency engages in contract renewal with providers, the expectation is that they use the data to assess outcomes and progress toward identified goals and to set goals for the upcoming contract year. A provider noted his agency makes good use of the data during contract negotiations and goal setting. While use of data for goal setting seems to be a priority in some areas, there is variance among the local area agencies across the state. Another provider noted that they did not currently have targets in their contracts but that they were moving in that direction for the future.

Designing a system that conveys the goal

While the four states examined for this study developed data collection systems to meet their states’ unique needs, they each underwent similar processes in the development of the basic components of their systems. The first steps each state took were to identify the frequency of their data collection, the population to collect data on, employment variables, responsibility for collection of data, and responsibility for analysis of the data (please see Table 13). Most important to consider about each of these components is how they help the state further their goals around employment. Each of the elements influences how effective the system is in gathering the data sought and conveying the message of the importance of employment.

Frequency of data collection. As noted, one of the defining elements of Florida’s system is its monthly data collection. Respondents spoke of this frequency for the most part as a boon for several reasons, from relationship-development with providers, to ease of reporting because of the frequency of engagement. Washington’s data collection system is tied to its service billing system and therefore coincides with the monthly billing cycle. While the frequency of the data collection was seen as an indicator of its significance (said one Supported Employment liaison in Florida, “If it wasn’t important, why would I chase them down all month and not let go until I get what I need?”), other states such as Massachusetts and New Hampshire collect data far less frequently (once per year and twice per year, respectively) and feel this is sufficient to assess their state’s progress over time.

Targets for data collection. With the exception of Florida, the three other states collect information on all individuals who are working either in the community or in facility-based services (sheltered workshops). Florida only collects information on individuals in community jobs. The types of work activities that are “counted” can be seen as important because it is another element that reflects states’ priorities. Other states, such as New Hampshire and Washington, however, keep track of the number of individuals in sheltered workshops so they can ensure that this number is declining or at least showing little to no growth.

Employment variables. All four states collect information on the type of job (group supported employment, individual employment, etc.), or the amount of time spent in each service category or activity, and wages and hours worked. Some states, like Florida and New Hampshire, collect information on other variables such as receipt of Vocational Rehabilitation services, use of assistive technology, or career advancement opportunities. While data such as these are valuable in assessing the quality of the overall work situation, they are often difficult to obtain. Massachusetts takes a straightforward approach and only collects information they see as most relevant to understanding who is employed and who is not, and who has entered into a new job during the data collection period. This variable has been added recently and speaks directly to their focus on outcomes.

Responsibility for data collection and analysis. In all cases, employment data is gathered locally at the provider level and submitted to the state ID/DD agency, either at the state level or to a regional office level within the state. With the exception of Massachusetts, all analysis is conducted within the state agency. Massachusetts has contracted with the ICI to conduct the analysis and provide the information back to the state for its use with its regional offices, and providers.

Table 13. Basic elements of state data collection system

State Frequency of data collection Targeted
population		 Employment
variables 		Responsibility for data collection Responsibility for data analysis
FL Monthly All individuals receiving services from the ID/DD agency who are working in the community, and individuals who are eligible to receive services (on the waiting list) who are working Employer, job title, wages, average hours worked per week, date of last raise, career advancement opportunities, employer-based benefits, integrated work setting, funding source, VR referral information Employment data is gathered locally. Supported Employment liaisons in each region are responsible for data collection. Analysis is done within the Employment Unit of the state ID/DD agency
MA Once annually during a four-week period All individuals supported by the ID/DD agency employment contracts. Does not include day habilitation (funded through Medicaid state plan) or Community Based Day Services Hours spent in each activity: individual and group SE, facility-based employment, volunteer work, other non-paid day services, and “in transition;” total gross wages; whether the individual was employed for 10 of last 12 months in individual or group SE; whether the individual entered a new individual job during previous 12 months Providers are required to submit their data to the ID/DD agency. ID/DD agency contracts with the Institute for Community Inclusion to produce employment reports
NH Twice annually All individuals receiving services who have had paid employment in the community or a sheltered workshop during the last six months and on each job an individual obtained or maintained during that period of time Individual demographics, area agency, provider, employer, job tenure, hours worked, wages, work environment, employment benefits, employer incentives, assistive technology, transportation, vocational rehabilitation services Providers submit data to the Area Agency in their region. The Area Agency enters the data into the statewide employment database, and exports the data to the state. State ID/DD agency
WA Monthly All individuals receiving day and employment services Data is directly linked to the billing system. Within each service category (individual, group, and prevocational employment; person-to-person; and community access services), data is collected on individual demographics, provider, funding sources, service start date, client hours (paid, volunteer, or other), gross wages, provider service units delivered and cost of service The vendor or a county ID/DD staff member enters outcome data into an Excel spreadsheet which is then uploaded by the county to the state ID/DD office. The state ID/DD agency produces standardized reporting measures. The analysis is reported by region, county and provider.

States’ use of the data

The four state data collection systems studied used the data they collected at both the state and local levels. While state level data helped states to understand progress toward employment goals, local level data provided information that allowed the ID/DD agency and providers to develop objectives for technical assistance and also has created a sense of awareness among providers with respect to how other providers are doing. Local level administrators (e.g., counties and area agencies) are using the data to have conversations with providers about the relationship between services and outcomes. It should be noted, though, that there are differences between and within states as to how the collected data is used.

State level use of data. States are using this level of data to understand trends at the most macro-level for their agency. State level reports have allowed New Hampshire to see that, while over time more people are getting jobs, the rate of job attainment has not kept pace with growth in the number of people served due to the movement of individuals off the agency’s waiting list and transitioning from school to adult life. The reports challenged New Hampshire to do a better job of expanding opportunities for integrated employment. The reports showed that only about 700 businesses in the state employed people supported by the Bureau, despite the fact that New Hampshire has approximately 30,000 businesses.

In Massachusetts, statewide and regional summaries of employment trends are produced. DDS shares these reports, including a three-year historical analysis of employment outcomes in Massachusetts from 2004–2006, with stakeholders. In addition to printed copies of the reports, the summary data are available to DDS staff on demand from a web-based data system developed at ICI. The web-based system allows users to produce graphs or summary reports for each of the variables at the state, regional, or provider levels. Data access is currently restricted to state staff using a password. Custom presentations have also been developed for review by the regional quality improvement teams.

Florida also uses the internet to highlight data. Line graphs documenting the state’s progress in meeting its employment goals are posted on its public website. On its intranet, area offices have access to a table that provides employment data for each area. Additionally, in Florida reports are produced on a monthly basis and are shared with each region and staff within ID/DD central office.

In Washington, data are used to complete standard reports including cost/benefit ratios (ratio of service cost to income earned) broken down by region, county, and provider. Data reports have a focus on total number of individuals receiving services, total and average wages, total and average hours worked, total and average state ID/DD agency funding share, and total and average service hours or units.

Local level use of data. Several states reported using data at the local level to motivate providers. Staff at one area agency in New Hampshire noted they use the data to see if their region is producing better employment outcomes than other areas in the state. In Massachusetts, individual provider reports are shared with providers and contain comparisons to regional and statewide averages for placement rates. Florida’s data is analyzed by region, and each region can view its own report and generate state-wide reports. While regional office staff have provider-level data, available data reports do not compare one provider to another across the region or across the state. At the county level in Washington, reports have been used to encourage providers to focus on employment and to increase understanding about trends in employment outcomes. Counties can access the data system and retrieve data. Some counties also have customized software that gave them more flexibility to work with the data, while others maintain their own data systems to retain outcomes information from the billing data and use this data as part of the evaluation of providers’ services.

Data are also used to facilitate technical assistance to providers at multiple stages. In Massachusetts, the state ID/DD Agency uses its individual-level provider reports to facilitate conversations with providers about their performance and areas where providers would benefit from support. The conversations often result in the provision of technical assistance to address issues related to employment outcomes. As noted earlier, this is in contrast to Florida, where at times the provision of technical assistance happens at an earlier stage, when supported employment liaisons are collecting the data from providers.

Local level data is not only being used to measure performance, but to set performance expectations. For FY2009, each Massachusetts ID/DD agency area office is using local data to establish a goal for improving employment outcomes and was required to identify and implement at least one strategy to support change. Strategies were varied and included focusing on transition-age young adults, engaging families and residential staff, collaborating with other agencies and resources, building local capacity through training and technical assistance, engaging in strategic planning, and working with employers.

Challenges in developing and implementing a data system

States described challenges that were encountered when they were beginning to implement their systems and ongoing implementation problems with collecting, maintaining, and using the data.

Implications

Data is important from both a strategic and program planning perspective, and these states are at various stages in using data to drive policy and practice-level decision-making. Respondents reflected that the data collection process as well as the data it produces has been critical in informing and promoting conversation about employment. In some of these states, data has not only been used at local office levels to establish priorities and goals but can also support decision making at the provider level as they receive current data about performance in relationship to local areas and their state. Notwithstanding the challenges noted above, states described several recommendations that can be used by other states as they move toward more comprehensive data collection systems that help to promote their goals.

Goal setting

Establishing a clear message about data collection

Communicating across the system

Strategies for implementation

Conclusion

With a growing emphasis on accountability, states are beginning to use their data collection systems as part of an overall plan to communicate about and facilitate their states’ progress toward greater integrated employment. Through investigation of the important elements in designing and using a data collection system, the variables that provide the most utility for influencing policy, and how data has been used as a strategic planning tool, this chapter provides a framework, although not a blueprint, for how states can use data to effectively communicate their priorities. While most states are at various stages in the process of refining their systems, it is clear that the use of data is one of the most important tools state ID/DD agencies can use to develop, implement, and evaluate their goals.

Based on case study data and recommendations from stakeholders about the most important elements in designing such systems, we suggest some federal guidance for states as they work to develop effective strategies. Guidelines could be based on best practices identified through careful study of successful systems, such as those presented in this chapter and through further research, and help states to work toward establishing national standards for data collection and reporting of employment outcomes. This would be beneficial not only from a state perspective as they create and refine their systems, but would also help to standardize national data comparisons, such as those available through ICI’s National Survey of Day and Employment Programs.

References

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