Kessler Foundation scientists awarded subcontract to study ways to improve disability statistics

Drs. Botticello and O'Neill to study ways to improve disability statistics toward the goal of more effective programs for people with disabilities

Kessler Foundation scientists John O'Neill, PhD, CRC and Amanda Botticello, PhD, MPH, were awarded a subcontract on the University of New Hampshire's (UNH) Rehabilitation Research and Training Center grant on Disability Statistics and Demographics (StatsRRTC). The five-year grant is funded by the National Institute on Disability and Rehabilitation Research (NIDRR) under cooperative agreement H133B130015. Economist Andrew Houtenville, PhD, of UNH's Institute on Disability, is project director of the StatsRRTC grant, which totals $4.3 million. The Kessler subcontract is valued at $398,115. Dr. O'Neill is director of Disability & Employment Research; Dr. Botticello is a research scientist in Outcomes & Assessment Research at Kessler Foundation.

According to Dr. O'Neill, the goal of the StatsRRTC is to bridge the divide between the producers and end users of disability statistics, supporting better data collection, more accurate information, better decision-making, more effective programs, and better lives for people with disabilities. Drs. O'Neill and Botticello will collaborate on three Stats RRTC research projects. These projects, which are summarized below, will address highly relevant and current policy issues, increasing the likelihood that the data will be used by policymakers to make informed, evidence-based decisions about programs and policies that impact people with disabilities. Researchers will focus on the disparities in various outcomes between people with and without disabilities and trends for program participation.

Comprehensive Taxonomy of Employment Supports and Services

Past research indicates that problems in question wording as well as the content and context of data collection have created measurement error that has obscured the relationship between vocational rehabilitation (VR) services and employment outcomes. This research will address these shortcomings by developing new streamlined approaches to collecting information on VR employment services so that employment services and outcomes can be more rigorously tracked. A Comprehensive Taxonomy for Employment Supports and Services (CoTESS) will inform the administrative measurement of VR services.

VR Services and Employment

Social Security Administration (SSA) caseloads nearly tripled in size since 1980, from 2.9 million to 8.2 million in 2010. Consequently, there is great interest in understanding more about these government programs, and to find ways to improve the independence and economic self-sufficiency of people with disabilities. Although there is a positive relationship between VR service use and employment, a key question is the extent to which VR agencies promote employment outcomes, particularly earnings. This research project will estimate the relationship of VR on employment and earnings for SSA beneficiaries. SSA administrative data will be matched to Rehabilitation Services Administration records identifying SSA beneficiaries who apply for VR services.

The Disability Belt

Geographic disparities exist both within and across people with and without disabilities, particularly in the "disability belt" of Appalachia and the lower Mississippi Valley. Although existing studies offer a broad overview of disability prevalence and benefit receipt, they provide very limited information on trends over time and on factors that contribute to those trends. This study will extend this work by taking advantage of both advances in spatial statistics and improvements to disability data to investigate disparities in the geographic concentration of people with disabilities, SSDI beneficiaries, and SSI recipients. County-level information from national and state surveys and national administrative data sets will be used along with spatial statistical analyses to compare the geographic variation in disability prevalence across disability types, and empirically define the boundaries of the disability belt. Findings will provide program planners at the state and local level with information to accurately target resources and services.