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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Main Authors: Christopher B McLeod, Eline Reiff, Esther Maas, Ute Bültmann
Format: Article
Language:English
Published: Nordic Association of Occupational Safety and Health (NOROSH) 2018-03-01
Series:Scandinavian Journal of Work, Environment & Health
Subjects:
msd
rtw
Online Access: https://www.sjweh.fi/show_abstract.php?abstract_id=3701
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spelling 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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