Who will have Sustainable Employment After a Back Injury? The Development of a Clinical Prediction Model in a Cohort of Injured Workers.
Purpose Our objective was to develop a clinical prediction model to identify workers with sustainable employment following an episode of work-related low back pain (LBP). Methods We used data from a cohort study of injured workers with incident LBP claims in the USA to predict employment patterns 1 and 6 months following a workers' compensation claim. We developed three sequential models to determine the contribution of three domains of variables: (1) basic demographic/clinical variables; (2) health-related variables; and (3) work-related factors. Multivariable logistic regression was used to develop the predictive models. We constructed receiver operator curves and used the c-index to measure predictive accuracy. Results Seventy-nine percent and 77 % of workers had sustainable employment at 1 and 6 months, respectively. Sustainable employment at 1 month was predicted by initial back pain intensity, mental health-related quality of life, claim litigation and employer type (c-index = 0.77). At 6 months, sustainable employment was predicted by physical and mental health-related quality of life, claim litigation and employer type (c-index = 0.77). Adding health-related and work-related variables to models improved predictive accuracy by 8.5 and 10 % at 1 and 6 months respectively. Conclusion We developed clinically-relevant models to predict sustainable employment in injured workers who made a workers' compensation claim for LBP. Inquiring about back pain intensity, physical and mental health-related quality of life, claim litigation and employer type may be beneficial in developing programs of care. Our models need to be validated in other populations.
UOIT-CMCC Center for the Study of Disability Prevention and Rehabilitation, University of Ontario Institute of Technology, 2000 Simcoe St. North, Oshawa, ON, L1H 7K4, Canada. heather.shearer@uoit.ca.|Graduate Education and Research Programs, Canadian Memorial Chiropractic College, 6100 Leslie St., Toronto, ON, M2H 3J1, Canada. heather.shearer@uoit.ca.
Heather M
HM
Shearer
UOIT-CMCC Center for the Study of Disability Prevention and Rehabilitation, University of Ontario Institute of Technology, 2000 Simcoe St. North, Oshawa, ON, L1H 7K4, Canada.|Canada Research Chair in Disability Prevention and Rehabilitation, University of Ontario Institute of Technology, 2000 Simcoe St. North, Oshawa, ON, L1H 7K4, Canada.|Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Pierre
P
Côté
Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark.
Eleanor
E
Boyle
Department of Community Health and Epidemiology, Dalhousie University, 5790 University Avenue, Room 403, Halifax, NS, B3H 1V7, Canada.
Jill A
JA
Hayden
Chair, Public Health Research and Policy, Usher Institute of Population Health Sciences, University of Edinburgh, Scottish Collaboration for Public Health Research and Policy, First Floor, 20 West Richmond St., Edinburgh, EH4 6AQ, UK.
John
J
Frank
Department of Biomedical Informatics, Arizona State University, Samuel C. Johnson Research Bldg., 13212 Shea Blvd., Scottsdale, AZ, 85259, USA.
William G
WG
Johnson
D000328:Adult; D016009:Chi-Square Distribution; D004185:Disability Evaluation; D005260:Female; D006801:Humans; D007588:Job Satisfaction; D017116:Low Back Pain / Q000534:rehabilitation*; D008297:Male; D060051:Occupational Injuries / Q000534:rehabilitation*; D017063:Outcome Assessment, Health Care; D016016:Proportional Hazards Models; D011446:Prospective Studies; D062707:Return to Work / Q000706:statistics & numerical data*; D013997:Time Factors; D014942:Workers' Compensation
Back injuries; Employment; Return to work