Patterns and Predictors of Failed and Sustained Return-to-Work in Transport Injury Insurance Claimants
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Purpose To determine the incidence of employed people who try and fail to return-to-work (RTW) following a transport crash. To identify predictors of RTW failure. Methods: A historical cohort study was conducted in the state of Victoria, Australia. People insured through the state-based compulsory third party transport accident compensation scheme were included. Inclusion criteria included date of crash between 2003 and 2012 (inclusive), age 15–70 years at the time of crash, sustained a non-catastrophic injury and received at least 1 day of income replacement. A matrix was created from an administrative payments dataset that mapped their RTW pattern for each day up to 3 years’ post-crash. A gap of 7 days of no payment followed by resumption of a payment was considered a RTW failure and was flagged. These event flags were then entered into a regression analysis to determine the odds of having a failed RTW attempt. Results: 17% of individuals had a RTW fail, with males having 20% lower odds of experiencing RTW failure. Those who were younger, had minor injuries (sprains, strains, contusions, abrasions, non-limb fractures), or were from more advantaged socio-economic group, were less likely to experience a RTW failure. Most likely to experience a RTW failure were individuals with whiplash, dislocations or particularly those admitted to hospital. Conclusions: Understanding the causes and predictors of failed RTW can help insurers, employers and health systems identify at-risk individuals. This can enable earlier and more targeted support and more effective employment outcomes.
KeywordsInjuries Return to work Rehabilitation
This project was funded by the Transport Accident Commission through the Institute for Safety, Compensation and Recovery Research (ISCRR). IC’s salary is supported by an Australian National Health and Medical Research Council Practitioner Fellowship.
Compliance with Ethical Standards
Conflict of interest
Shannon E. Gray, Behrooz Hassani-Mahmooei, Ian D. Cameron, Elizabeth Kendall, Justin Kenardy and Alex Collie declare that they have no conflict of interest.
This article does not contain any studies with human participants performed by any of the authors.
Statement not required. This study was performed using a de-identified administrative dataset, with ethics approval granted by Monash University Human Research Ethics Committee (CF09/3150—2009001727).
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