Assessing Vocational Rehabilitation Agency Capacity to Engage in Evidence-Based Decision Making.
Background: The Evidence-based Policy-Making Act of 2018 requires that Federal agencies use their data to develop statistical evidence to support policy and programmatic decisions. Objective: This study assessed Vocational Rehabilitation agency capacity to effectively use their data to inform eviden...
| Published in: | Journal of Vocational Rehabilitation Vol. 63; no. 3; pp. 271 - 282 |
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| Main Authors: | , , , , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Sage Publications Inc.
Nov2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188669759&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188669759 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10522263 3O2 jtl: Journal of Vocational Rehabilitation issn: 10522263 maglogo: N pubinfo: dt: Nov2025 vid: 63 iid: 3 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 188669759 188162117 188669759 188669759 10.1177/10522263251376322 188669759 ppf: 271 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Assessing Vocational Rehabilitation Agency Capacity to Engage in Evidence-Based Decision Making. aug: au: Clapp, Christopher M Ipsen, Catherine Garry, Crystal S Ashley, Joe M Pepper, John Schmidt, Robert Stern, Steven McGuire-Kuletz, Maureen affil: Harris School of Public Policy, The University of Chicago, Chicago, IL, USA sug: subj: Rehabilitation, Vocational Organizations Medical Practice, Evidence-Based Decision Making, Clinical Organizational Efficiency Human Descriptive Statistics Data Analysis Software Professional Competence Software Investments Policy Making Accountability Data Management Multimethod Studies Chi Square Test T-Tests Coding Funding Source Interinstitutional Relations ab: Background: The Evidence-based Policy-Making Act of 2018 requires that Federal agencies use their data to develop statistical evidence to support policy and programmatic decisions. Objective: This study assessed Vocational Rehabilitation agency capacity to effectively use their data to inform evidence-based decision-making. Methods: The Capacity Survey assessed agency capacity in data management, data visualization and statistical analysis. The survey asked for details about (1) the availability of relevant software programs (e.g., SPSS for statistical analysis), and (2) staff expertise to use that software. Results: Results pointed to capacity gaps that would significantly hinder most agencies' application of even a simplified return on investment model. When examining statistical capacity, 60% of agencies responded "not applicable – staff do not have competence in the listed software packages (including SPSS, SAS, R, Python, Stata, and other)" and 71% of respondents said they lacked internal statistical capacity to analyze data using any of the listed programs. Conclusions: Results suggested that many state VR agencies lack internal capacity to meet requirements outlined in the Evidence-Based Policy-Making Act of 2018 or regulations related to reporting and performance accountability requirements. Potential solutions to overcome capacity deficits include expanding internal capacity, expanding agency/consultant partnerships, and building cross-agency collaborations. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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