VR-ROI Project: Estimating Return on Investment in State Vocational Rehabilitation Programs

VR-ROI Project: Estimating Return on Investment in State Vocational Rehabilitation Programs

The VR-ROI Project: Estimating Return on Investment in State Vocational Rehabilitation Programs - is a five-year examination of the return on investment in eight state vocational rehabilitation programs, by a collaborative team led by the University of Richmond (UR) and involving George Washington University (GWU) and the University of Arkansas CURRENTS. Return on investment (ROI) information for the state-federal vocational rehabilitation (VR) program has increasingly been seen as a way to demonstrate the effectiveness of VR. Recent years have seen substantial growth in the numbers of ROI studies of state vocational rehabilitation (VR) programs. However, the analytic methods, time periods covered and data used in existing VR ROI studies have varied widely. Most recent analyses have serious shortcomings that limit the credibility and utility of their results. Also, with one exception, the recent work of the late David Dean and his colleagues (2014), the existing studies provide a single ROI estimate based on an entire cohort of VR participants and total service expenditures. A single ROI estimate, when credible, can be very useful to VR administrators in demonstrating the impact and value of the program. However, a single ROI estimate does not provide information to help administrators and policymakers determine which types of services are most effective for which types of participants.

The current work, now led by Robert Schmidt of UR, has developed an individual-level framework which cracks the “black box” of VR services to allow for estimates of the long-term impacts of a specific mix of VR services on the employment probability and subsequent earnings for VR applicants with specific impairments. The objective of the proposed new research is to further refine and test the existing ROI models using a more heterogeneous set of state agencies and a more recent cohort of applicants for VR services. This project also proposes to test a “turnkey” approach to ROI analysis that can generate rigorous and credible estimates for any size agency, for individuals with virtually any type of disability, and for different types of VR services. A user-friendly Web-based “ROI Estimator” will be developed to allow state agencies to simulate the impact of different VR services on the employment outcomes of VR clients and to develop ROI estimates for the entire state program.

This project will build upon the results of a 3-year NIDRR-funded Field Initiated Project carried out by the Bureau of Disability Economics Research at UR together with the University of Virginia (UVA) and state VR agencies in Virginia, Maryland and Oklahoma. These states will partner with UR, GWU, CURRENTS, and consultants from UVA on the proposed new project. VR agencies in Delaware, Kentucky and Texas will be added to help provide the heterogeneity necessary to test the Estimator. The project will make use of readily available administrative data from both state and federal sources, including VR client and services data, employment data from state Unemployment Insurance programs and the Federal Employment Data Exchange System, and disability benefits data from the Social Security Administration.

The proposed project will develop VR ROI estimates for specific populations, including youth in transition, individuals with several low-incidence disabilities and individuals with disabilities from minority backgrounds. The project will also develop and disseminate training materials for state VR agencies interested in conducting ROI analyses, and will provide training in effective use of both the project’s methodological framework and the agency-specific results produced by the ROI Estimator. Project information will also be disseminated widely to a broad range of stakeholders.

More About the VR-ROI Project

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.