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Do Work-Related Lost-Time Injuries Sustained Early in Employment Predict Multiple Lost-Time Injuries Throughout Employment? 2019

Xuguang Grant Tao, and Nimisha Kalia, and Robert A Lavin, and Sebastian A Minor, and Larry Yuspeh, and Nina Leung, and Nicholas F Tsourmas, and Edward J Bernacki
Division of Occupational and Environmental Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (Dr Tao and Dr Kalia); Department of Neurology, University of Maryland School of Medicine, Baltimore, Maryland (Dr Lavin); Insurance and Information Technology, School of Medicine, Johns Hopkins University, Baltimore, Maryland (Minor); AVP of Strategic Risk and Strategy Management, Louisiana Workers' Compensation Corporation, Instructor in Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (Yuspeh); Dell Medical School, The University of Texas at Austin, Austin, Texas; Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland (Dr Leung and Dr Bernacki); Department of Population Health, Dell Medical School, The University of Texas at Austin, Austin, Texas (Dr Tsourmas).

The aim of this study was to identify a simple surrogate to predict the future risk of multiple lost-time injuries. Employees of an academic medical center who sustained 5,906 injuries were followed from 1994 to 2017 or 1,046,218 person years. The odds ratio of having three or more lost-time injuries during their entire duration of employment was 2.12 (95% confidence interval: 1.60 to 2.79) for employees having their first lost-time injury within the first 6 months of employment versus those injured after that, controlling for demographics and employment duration. For each increasing year before the first lost-time injury, the probability of having three or more lost-time injuries decreased by 13%. Employment duration before the first lost-time injury may be used to predict future lost-time injuries without detailed information of underlying risk factors.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D012008 Recurrence The return of a sign, symptom, or disease after a remission. Recrudescence,Relapse,Recrudescences,Recurrences,Relapses
D004651 Employment The state of being engaged in an activity or service for wages or salary. Employment Termination,Employment Status,Labor Force,Occupational Status,Status, Occupational,Underemployment,Labor Forces,Status, Employment,Termination, Employment
D005260 Female Females
D005544 Forecasting The prediction or projection of the nature of future problems or existing conditions based upon the extrapolation or interpretation of existing scientific data or by the application of scientific methodology. Futurology,Projections and Predictions,Future,Predictions and Projections
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000046 Academic Medical Centers Medical complexes consisting of medical school, hospitals, clinics, libraries, administrative facilities, etc. Medical Centers, Academic,Medical Centers, University,University Medical Centers,Academic Medical Center,Center, Academic Medical,Center, University Medical,Centers, Academic Medical,Centers, University Medical,Medical Center, Academic,Medical Center, University,University Medical Center
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000367 Age Factors Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time. Age Reporting,Age Factor,Factor, Age,Factors, Age

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