Abstract
Purpose
To identify predictors of return to work, duration of time off work, and claim closure for first responders experiencing injuries or illnesses, and summarize the claim data.
Methods
First responder claims collected between January 2012 and July 2017 were obtained from a disability management company. Known predictors of return to work were extracted from the data including age, sex, diagnosis, years of service, claim lag, medical report lag, and the return-to-work duties. Survival analyses were performed to identify predictors of return to work and claim closure using the Cox proportional regression analysis. Log-rank tests were performed to identify predictors that affected the rate of return to work and claim closure. Summary statistics were performed for the injury and return-to-work data.
Results
60 of the 67 (89.6%) identified first responders returned to work within the data collection period. Musculoskeletal injuries predicted an increased likelihood of returning to work (hazard ratio = 2.0, 95%CI = 1.14–3.60) and a shorter duration of time off work (37 days on average) compared to mental health issues. Everyday of claim lag and medical report lag predicted a 2% decrease in likelihood of return to work. Returning to work was the only predictor of claim closure. 45 (67.2%) first responders returned to their pre-absence duties. 22 (32.8%) mental health claims and 45 (67.2%) injury claims were identified.
Conclusions
89.6% of first responders returned to work, although only 67.2% returned to their pre-absence duties. Predictors of return to work included injury type, as first responders with musculoskeletal injuries returned to work sooner, and claim and medical lag delayed the return to work.
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Availability of data and materials
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. The data are not publicly available because the data belongs to an organization (Organizational Solutions Incorporated) and contains injury claim detail of their clients.
Code availability
Codes used for the data analysis in STATAIC 14 are available from the corresponding author upon request.
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Acknowledgements
The dataset was provided by Dr. Liz Scott and Organizational Solutions Incorporated. Joy MacDermid was supported by a Canadian Institutes of Health Research Chair in Gender, Work and Health and the Dr James Roth Chair in Musculoskeletal Measurement and Knowledge Translation. This work was supported by from the Ontario Ministry of Labour (FRN: 13-R-027), Canadian Institutes of Health Research (FRN: HPW-146016), and Social Sciences and Humanities Research Council (FRN: 890-2016-3013).
Funding
This work was supported by from the Ontario Ministry of Labour (FRN: 13-R-027), Canadian Institutes of Health Research (FRN: HPW-146016), and Social Sciences and Humanities Research Council (FRN: 890-2016-3013).
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All authors contributed to the study conception and design. Material preparation and analysis were performed by Shannon Killip. The first draft of the manuscript was written by Shannon Killip and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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The authors Shannon Killip, Joy MacDermid, Kathryn Sinden, Rebecca Gewurtz and Liz Scott declare that they have no conflicts of interest. The authors have no relevant financial or non-financial interests to disclose.
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Not applicable. As a secondary analysis of disability management data which did not include any personal identifying information, ethics approval was not required. We consulted with the Hamilton Integrated Research Ethics Board (HiREB) who determined that our study did not need ethical approval.
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Not applicable. As a secondary analysis of disability management data, consent and contract forms explaining that the data collected would be used in an aggregate manner for research had been signed at the time of the data collection by the clients and the disability managers.
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Not applicable. As a secondary analysis of disability management data, consent and contract forms explaining that the data collected would be used in an aggregate manner for research had been signed at the time of the data collection by the clients and the disability managers. All personal identifiers were removed from the data.
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Killip, S.C., MacDermid, J.C., Sinden, K.E. et al. Identifying predictors of return to work and the duration of time off work in first responders affected with musculoskeletal injuries or mental health issues. Int Arch Occup Environ Health 95, 723–735 (2022). https://doi.org/10.1007/s00420-021-01800-0
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DOI: https://doi.org/10.1007/s00420-021-01800-0