Impacting Entry into Evidence-Based Supported Employment: A Population-Based Empirical Analysis of a Statewide Public Mental Health Program in Maryland

  • David Salkever
  • Michael Abrams
  • Kevin Baier
  • Brent Gibbons
Original Article


We use discrete-time survival regression to study two empirical issues relating to take-up of individual placement and support (IPS) supported employment (SE) services for persons with serious mental illness: (1) the influence of client characteristics on take-up probability, and (2) the possible impacts of a major recent initiative in one state (Maryland) to overcome barriers to IPS-SE expansion. Our longitudinal analysis of population-based Medicaid cohorts, during 2002–2010, provides tentative evidence of positive state initiative impacts on SE take-up rates, and evidence of effects on take-up for clients’ diagnoses, prior work-history, health and demographic characteristics, and geographic accessibility to SE providers.


Supported employment State mental health Medicaid 



Support for this research was provided by Grant R01MH093374 from the National Institute of Mental Health. The research project underlying this work was in large part the result of key efforts by our late friend and colleague, Judy Shinogle. She was the Principal Investigator when the project began, shortly before her death, and her knowledge, insights and vision are reflected in all aspects of the project. We are also grateful to a number of other people who provided valuable insights, data, suggestions, and other assistance on this work. They include: Agnes Rupp, Ph.D., NIMH Program Officer, colleague and supplier of valuable perspectives, suggestions, and (occasionally) criticisms; Chrstine Yee UMBC, for her careful review of earlier versions of this work; Judith Leiman and Steven Reeder, Ph.D. of the Maryland Behavioral Health Administration, who gave us access to information and documents relevant to the study and helped us better understand Maryland’s supported-employment initiative; and Tim Santoni and the staff of the Systems Evaluation Center, Mental Health Systems Improvement Collaborative, Division of Services Research, Department of Psychiatry, University of Maryland School of Medicine. We further acknowledge many useful suggestions from the editor and reviewers on an earlier version of this work. We reluctantly acknowledge our own responsibility for remaining errors, and shortcomings.

Compliance with Ethical Standards

Conflict of interest

The authors have no conflict to report.

Informed Consent

All analyses used only de-identified, routinely collected administrative data and were therefore deemed by the University and State of Maryland IRB’s to be exempt from informed consent requirements.

Research Involving Human Participants and/or Animals

The research involved no participation of human or animal subjects.

Supplementary material

10488_2017_827_MOESM1_ESM.docx (221 kb)
Supplementary material 1 (DOCX 220 KB)


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.School of Public Policy and Maryland Institute for Policy Analysis and ResearchUniversity of Maryland – Baltimore County (UMBC)BaltimoreUSA
  2. 2.Hilltop InstituteUniversity of Maryland Baltimore CountyBaltimore CountyUSA
  3. 3.Westat Inc.RockvilleUSA
  4. 4.IBM Watson HealthBethesdaUSA

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