OBJECTIVE: To determine which, if any, baseline social and disease characteristics can be used to identify persons with musculoskeletal disabilities accepted for state-federal vocational rehabilitation services who are most likely to return to work. METHODS: A database of case closures from the Alabama Vocational Rehabilitation Service was analyzed using segmentation modelling. This included all persons (n = 4093) with musculoskeletal disability who were accepted by the Alabama Vocational Rehabilitation Agency in 1987-91. Demographics, income, type of disability, severity of disability, medical insurance, similar benefits, benefit status, and referral source were independent variables. Outcome (dependent) variable was work status at end of agency services. RESULTS: Overall, 71% of persons with arthritis and musculoskeletal disorders who were accepted for vocational rehabilitation services in 1987-91 returned to work at the end of agency services. Segmentation modelling created a tree in which certain baseline characteristics formed subgroups with differing rates of successful rehabilitation. Social Security Disability Insurance (SSDI) status was the single best predictor of rehabilitation. Seventy-three percent of nonbeneficiaries were rehabilitated compared to 55% of beneficiaries (p < 0.00001). For non-SSDI beneficiaries, education level > or = grade 12 was associated with better rehabilitation outcome (p < 0.00001). SSDI beneficiaries with nonback disorders fared better than those with back disorders (p < 0.05). Disease severity, assessed by Federal Special Programs criteria, was not associated with rehabilitation outcome at any level of the tree. CONCLUSION: Simple baseline social and disease characteristics can be used to identify groups of persons accepted for vocational rehabilitation services with musculoskeletal disability with differing rates of vocational rehabilitation. Disability benefit status and education level are important predictors of return to work after agency services. These findings can lead to the development of strategies to improve the efficacy of vocational rehabilitation services.
OBJECTIVE: To determine which, if any, baseline social and disease characteristics can be used to identify persons with musculoskeletal disabilities accepted for state-federal vocational rehabilitation services who are most likely to return to work. METHODS: A database of case closures from the Alabama Vocational Rehabilitation Service was analyzed using segmentation modelling. This included all persons (n = 4093) with musculoskeletal disability who were accepted by the Alabama Vocational Rehabilitation Agency in 1987-91. Demographics, income, type of disability, severity of disability, medical insurance, similar benefits, benefit status, and referral source were independent variables. Outcome (dependent) variable was work status at end of agency services. RESULTS: Overall, 71% of persons with arthritis and musculoskeletal disorders who were accepted for vocational rehabilitation services in 1987-91 returned to work at the end of agency services. Segmentation modelling created a tree in which certain baseline characteristics formed subgroups with differing rates of successful rehabilitation. Social Security Disability Insurance (SSDI) status was the single best predictor of rehabilitation. Seventy-three percent of nonbeneficiaries were rehabilitated compared to 55% of beneficiaries (p < 0.00001). For non-SSDI beneficiaries, education level > or = grade 12 was associated with better rehabilitation outcome (p < 0.00001). SSDI beneficiaries with nonback disorders fared better than those with back disorders (p < 0.05). Disease severity, assessed by Federal Special Programs criteria, was not associated with rehabilitation outcome at any level of the tree. CONCLUSION: Simple baseline social and disease characteristics can be used to identify groups of persons accepted for vocational rehabilitation services with musculoskeletal disability with differing rates of vocational rehabilitation. Disability benefit status and education level are important predictors of return to work after agency services. These findings can lead to the development of strategies to improve the efficacy of vocational rehabilitation services.
Authors: Morten Støver; Kristine Pape; Roar Johnsen; Nils Fleten; Erik R Sund; Bjørgulf Claussen; Solveig Osborg Ose; Johan Håkon Bjørngaard Journal: BMC Health Serv Res Date: 2012-10-30 Impact factor: 2.655