Data-driven Approaches to Evaluate the Impact of Technical Assistance

Abstract

Background

The Vocational Rehabilitation Technical Assistance Center for Quality Employment (VRTAC-QE) uses a data-driven approach to analyze the efficacy of its website (https://tacqe.com). The center also employs a management information system (MIS) with RSA-911 data to enable interagency data sharing through the Salesforce platform.

Objective

VRTAC-QE uses quantitative methods to identify the usage and efficacy of its website, and the MIS provides access to large data sets that can measure impact in vocational rehabilitation (VR). These quantitative measures are in line with the Government Performance and Results Act (GPRA).

Methods

Quantify website usage by tabulating user statistics, state rehabilitation service agencies (SVRA) participation, and employing longitudinal analysis to determine the efficacy of technical assistance (TA) among participating parties.

Results

Quantitative results show that the VRTAC-QE digital resources are utilized above target goals, and that participating SVRAs benefit from TA, as longitudinal data shows an increase in positive employment status at VR exit during the project period.

Conclusions

Data-driven approaches identify where VR efforts are successful, and the adoption of MIS architecture promotes wider access to large data sets among professionals, enhancing and standardizing data.

Keywords

vocational rehabilitation management information system technical assistance collaboration computer/internet applications evidence-based practice

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