Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders
OBJECTIVES: This study aimed to identify return-to-work (RTW) trajectories among workers with work-related musculoskeletal disorders (MSD) and examine the associations between different MSD and these RTW trajectories. METHODS: We used administrative workers’ compensation data to identify accepted MS...
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Nordic Association of Occupational Safety and Health (NOROSH)
2018-03-01
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doaj-2f973314751e407c8e89bf9a1161e8ee2021-04-21T06:57:26ZengNordic Association of Occupational Safety and Health (NOROSH)Scandinavian Journal of Work, Environment & Health0355-31401795-990X2018-03-0144214715510.5271/sjweh.37013701Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disordersChristopher B McLeod0Eline ReiffEsther MaasUte BültmannSchool of Population and Public Health, University of British Columbia, 2206 East Mall, Vancouver, BC Canada, V6T 1Z3.OBJECTIVES: This study aimed to identify return-to-work (RTW) trajectories among workers with work-related musculoskeletal disorders (MSD) and examine the associations between different MSD and these RTW trajectories. METHODS: We used administrative workers’ compensation data to identify accepted MSD lost-time claims with an injury date between 2010–2012 in British Columbia, Canada. Cox regression analyses were used to investigate differences in time to RTW between MSD. Validated day-to-day calendar measures of four RTW states (sickness absence, modified RTW, RTW, and non-RTW) were grouped into RTW trajectories spanning a one-year period using sequence analysis. RTW trajectories were clustered using decision rules that identified a shared trajectory structure. Poisson regression with robust standard errors was used to estimate relative risk ratios (RR) with 95% confidence intervals (CI) between MSD and RTW trajectory clusters. RESULTS: In a cohort of 81 062 claims, 2132 unique RTW trajectories were identified and clustered into nine RTW trajectory clusters. Half of the workers sustainably returned to work within one month. Workers with back strains were most likely to have trajectories characterized by early sustained RTW, while workers with fractures or dislocations were more likely to have prolonged sickness absence trajectories (RR 4.9–9.9) or non-RTW trajectories (RR 1.4–7.6). CONCLUSION: This is the first study that has characterized different types of RTW trajectories of workers with MSD using sequence analysis. The application of sequence analysis and the identification of RTW trajectories yielded a number of key insights not found using conventional cox regression analysis. https://www.sjweh.fi/show_abstract.php?abstract_id=3701 musculoskeletal disordersick leavecohort studysickness absencemusculoskeletal diseasemsdsickness absencereturn-to-workrtwreturn-to-work trajectorysequence analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Christopher B McLeod Eline Reiff Esther Maas Ute Bültmann |
spellingShingle |
Christopher B McLeod Eline Reiff Esther Maas Ute Bültmann Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders Scandinavian Journal of Work, Environment & Health musculoskeletal disorder sick leave cohort study sickness absence musculoskeletal disease msd sickness absence return-to-work rtw return-to-work trajectory sequence analysis |
author_facet |
Christopher B McLeod Eline Reiff Esther Maas Ute Bültmann |
author_sort |
Christopher B McLeod |
title |
Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders |
title_short |
Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders |
title_full |
Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders |
title_fullStr |
Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders |
title_full_unstemmed |
Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders |
title_sort |
identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders |
publisher |
Nordic Association of Occupational Safety and Health (NOROSH) |
series |
Scandinavian Journal of Work, Environment & Health |
issn |
0355-3140 1795-990X |
publishDate |
2018-03-01 |
description |
OBJECTIVES: This study aimed to identify return-to-work (RTW) trajectories among workers with work-related musculoskeletal disorders (MSD) and examine the associations between different MSD and these RTW trajectories. METHODS: We used administrative workers’ compensation data to identify accepted MSD lost-time claims with an injury date between 2010–2012 in British Columbia, Canada. Cox regression analyses were used to investigate differences in time to RTW between MSD. Validated day-to-day calendar measures of four RTW states (sickness absence, modified RTW, RTW, and non-RTW) were grouped into RTW trajectories spanning a one-year period using sequence analysis. RTW trajectories were clustered using decision rules that identified a shared trajectory structure. Poisson regression with robust standard errors was used to estimate relative risk ratios (RR) with 95% confidence intervals (CI) between MSD and RTW trajectory clusters. RESULTS: In a cohort of 81 062 claims, 2132 unique RTW trajectories were identified and clustered into nine RTW trajectory clusters. Half of the workers sustainably returned to work within one month. Workers with back strains were most likely to have trajectories characterized by early sustained RTW, while workers with fractures or dislocations were more likely to have prolonged sickness absence trajectories (RR 4.9–9.9) or non-RTW trajectories (RR 1.4–7.6). CONCLUSION: This is the first study that has characterized different types of RTW trajectories of workers with MSD using sequence analysis. The application of sequence analysis and the identification of RTW trajectories yielded a number of key insights not found using conventional cox regression analysis. |
topic |
musculoskeletal disorder sick leave cohort study sickness absence musculoskeletal disease msd sickness absence return-to-work rtw return-to-work trajectory sequence analysis |
url |
https://www.sjweh.fi/show_abstract.php?abstract_id=3701
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work_keys_str_mv |
AT christopherbmcleod identifyingreturntoworktrajectoriesusingsequenceanalysisinacohortofworkerswithworkrelatedmusculoskeletaldisorders AT elinereiff identifyingreturntoworktrajectoriesusingsequenceanalysisinacohortofworkerswithworkrelatedmusculoskeletaldisorders AT esthermaas identifyingreturntoworktrajectoriesusingsequenceanalysisinacohortofworkerswithworkrelatedmusculoskeletaldisorders AT utebultmann identifyingreturntoworktrajectoriesusingsequenceanalysisinacohortofworkerswithworkrelatedmusculoskeletaldisorders |
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1721516762627833856 |