2015European Journal of Public HealthRequires access

New Methods for Work Disability Assessment – Computer-Adaptive Tests (CATs)

Alan M. Jette, Elizabeth Marfeo, Christine M. McDonough, Pengsheng Ni, Kara Bogusz, D. Brandt, Leighton Chan, Mark Meterko, Elizabeth K. Rasch

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Abstract

The Disability Insurance program of the US Social Security Act, provides earnings replacement insurance for over 20 million workers, covering earnings loss in the event of a work disability. As the number of work disability claims continues to rise, efforts to improve the efficiency and accuracy of the Social Security Administration (SSA)’s Work Disability decision process are increasingly important. In its 2007 report entitled, “Improving the Social Security Disability Decision Process”, the Institute of Medicine committee recommended the development of new approaches to work disability determination, including the creation of standardized functional assessment approaches. Item-response theory (IRT) and computer adaptive test (CAT) assessment of function may be a promising means to provide the SSA with feasible functional assessment tools that can inform the evaluation of a claimant’s ability to engage in substantial gainful employment activity. CAT methodology uses a computer interface that is tailored to the unique ability level of each person to be assessed, allowing for fewer items to be administered, while providing assessment precision, breadth and efficiency. This presentation will provide an introduction to IRT/CAT measurement techniques and describe the multidimensional work disability functional assessment instruments developed for the US SSA Work Disability Insurance Program. I will present data on a recently completed calibration study with 3000 claimants to the US SSA’s Disability Insurance Programs (Disability Insurance and Supplemental Security Income programs) and a normative sample of 2000 adults living across the US. Key messages Indicate how Computer Adaptive Tests could potentially improve SSA’s disability determination processes Indicate the importance and relevance of this work for national social security programs and national policy-making

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The Disability Insurance program of the US Social Security Act, provides earnings replacement insurance for over 20 million workers, covering earnings loss in the event of a work disability. As the number of work disability claims continues to rise, efforts to improve the efficiency and accuracy of the Social Security Administration (SSA)’s Work Disability decision process are increasingly important. In its 2007 report entitled, “Improving the Social Security Disability Decision Process”, the Institute of Medicine committee recommended the development of new approaches to work disability determination, including the creation of standardized functional assessment approaches. Item-response theory (IRT) and computer adaptive test (CAT) assessment of function may be a promising means to provide the SSA with feasible functional assessment tools that can inform the evaluation of a claimant’s ability to engage in substantial gainful employment activity. CAT methodology uses a computer interface that is tailored to the unique ability level of each person to be assessed, allowing for fewer items to be administered, while providing assessment precision, breadth and efficiency. This presentation will provide an introduction to IRT/CAT measurement techniques and describe the multidimensional work disability functional assessment instruments developed for the US SSA Work Disability Insurance Program. I will present data on a recently completed calibration study with 3000 claimants to the US SSA’s Disability Insurance Programs (Disability Insurance and Supplemental Security Income programs) and a normative sample of 2000 adults living across the US. Key messages Indicate how Computer Adaptive Tests could potentially improve SSA’s disability determination processes Indicate the importance and relevance of this work for national social security programs and national policy-making

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Available abstract

The Disability Insurance program of the US Social Security Act, provides earnings replacement insurance for over 20 million workers, covering earnings loss in the event of a work disability. As the number of work disability claims continues to rise, efforts to improve the efficiency and accuracy of the Social Security Administration (SSA)’s Work Disability decision process are increasingly important. In its 2007 report entitled, “Improving the Social Security Disability Decision Process”, the Institute of Medicine committee recommended the development of new approaches to work disability determination, including the creation of standardized functional assessment approaches. Item-response theory (IRT) and computer adaptive test (CAT) assessment of function may be a promising means to provide the SSA with feasible functional assessment tools that can inform the evaluation of a claimant’s ability to engage in substantial gainful employment activity. CAT methodology uses a computer interface that is tailored to the unique ability level of each person to be assessed, allowing for fewer items to be administered, while providing assessment precision, breadth and efficiency. This presentation will provide an introduction to IRT/CAT measurement techniques and describe the multidimensional work disability functional assessment instruments developed for the US SSA Work Disability Insurance Program. I will present data on a recently completed calibration study with 3000 claimants to the US SSA’s Disability Insurance Programs (Disability Insurance and Supplemental Security Income programs) and a normative sample of 2000 adults living across the US. Key messages Indicate how Computer Adaptive Tests could potentially improve SSA’s disability determination processes Indicate the importance and relevance of this work for national social security programs and national policy-making

Key concepts: Disability insurance, Social security, Earnings, Disability benefits, Work (physics), Social insurance, Actuarial science, Social work

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