The error of using returns-to-work to measure the outcomes of health care

Am J Ind Med. 1996 Jun;29(6):632-41. doi: 10.1002/(SICI)1097-0274(199606)29:6<632::AID-AJIM7>3.0.CO;2-L.


This article uses data from The Survey of Ontario Workers With Permanent Impairments. the world's largest survey of injured workers, to show that, as currently used, return-to-work is a misleading measure of the effectiveness of health care. The article discusses examples of two serious limitations on the use of return-to-work to measure the outcomes of health care, where health care refers to all the medical and rehabilitative services provided to a worker following a workplace injury. The first limitation is that return-to-work, like many other outcomes of health care, is influenced by factors that are not directly related to health care. Using a logit model to estimate the determinants of first absences from work after an injury, we find that socioeconomic characteristics, economic incentives, and job characteristics have a significant influence on return-to-work. The second limitation on return-to-work as an outcome measure is that the first return-to-work after an injury, like a hospital discharge, frequently marks the end of only the first of several episodes of work disability caused by the original injury. Using first post-injury returns-to-work as a proxy for recovery, we would assume that 85% of the Ontario workers recovered from their injury when, in fact, 61% had subsequent spells of work disability. We identified four mutually exclusive patterns of post-injury work and work disability. Multinomial logit estimates of the determinants of the patterns show that health care is only one of several influences on return-to-work. The results also demonstrate that if return-to-work is used to measure outcomes, it must be evaluated over a time horizon that permits multiple spells of work disability.

MeSH terms

  • Bias
  • Employment*
  • Epidemiologic Factors
  • Female
  • Health Status Indicators*
  • Humans
  • Likelihood Functions
  • Male
  • Models, Theoretical
  • Motivation
  • Multivariate Analysis
  • Occupational Diseases / rehabilitation*
  • Outcome Assessment, Health Care*
  • Sick Leave / statistics & numerical data*
  • Socioeconomic Factors