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PubMed · 15586965

Imagining the future.

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Yuval Levin. 2004. Imagining the future.. https://pubmed.ncbi.nlm.nih.gov/15586965/

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Assistive technology outcomes in work settings.

Successfully documenting the outcomes of assistive technology (AT) interventions in the workplace benefits people with disabilities, service providers and agencies. However, no work related system currently exists that comprehensively collects the data needed to analyze such outcomes. Part of the reason for this absence of an outcome system is that, while the concept is simple, the process is complex and depends on the acquisition of data that represent many outcomes related variables. This article describes the exploratory work of the NIDRR (National Institute on Disability and Rehabilitation Research) funded ATOMS Project (Assistive Technology Outcomes Measurement System) and its efforts to identify existing data that might be used as the basis for an outcomes measurement system. Sample records from four assistive technology service programs were acquired and evaluated for the data they housed. This study discovered that AT service programs fail to collect consistent or sufficient data for outcomes analysis. However, discussions with AT programs that provided services to State vocational rehabilitation agencies revealed an interesting potential. Assistive technology service data in combination with data collected by State vocational rehabilitation departments might coalesce the needed data. The Federal Rehabilitation Services Administration (RSA) 911 Report aggregates many variables of outcomes related information including employment status and the success of the vocational rehabilitation investment. This combined database could answer a range of assistive technology outcomes related questions of interest to service providers, people with disabilities, and vocational rehabilitation State agencies. This paper describes the data needed in an outcomes system, reviews the data that appear to be available today related to AT outcomes, and projects how data from two diverse programs might be used together to create a significant outcomes database.

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