Column from DMEC: Does Industry Influence Return-to-Work Durations?

MDGuidelines contributes a column to DMEC’s (Disability Management Employer Coalition) @Work magazine. The authors were Kerri Wizner, MPH, Head of Epidemiology MDGuidelines team – Alight Solutions; Gage Koeller, MPH, Research Analyst, MDGuidelines team – Alight Solutions; Justine Ahle, MS, Senior Product Manager, MDGuidelines team – Alight Solutions

Full article here: https://dmec.org/resources/work-magazine/2025-integrated-disability-and-absence-management-issue/

Publication date: June, 2025

Many factors influence the length of an employee’s return to work (RTW) duration after an injury or illness. Employers often ask what role their industry plays in estimating the duration and how much emphasis should be placed on an employer’s approach based on industry.

Questions about injury and illness duration estimates are common, and most employers want to know about duration time frames in their industry. One common response: Does a broken arm take longer to heal in a sedentary job in a hospital or in an aviation tower?

Data helps tell the story. And (spoiler alert) industry classifications alone are not as helpful to employers as you might think, in part because the North American Industry Classification System (NAICS) categorizes similar industries,¹ which can be misleading. For example, the finance industry includes investment bankers, financial salesmen, and local bank employees despite significant differences in hours, job demand, and workplace culture. Even within the same industry, job demand and workplace culture may differ significantly and result in different RTW durations.

For example, three NAICS codes for education encompass elementary and secondary schools (6111); junior colleges (6112); and colleges, universities, and professional schools (6113). These three codes include most teachers, but there is no information on the socioeconomic status of the school, teacher salary, or job demands, which can be important. For example, teachers in low-income, urban schools may experience more stress and lower job satisfaction compared with teachers in higher income, suburban, and rural settings.² These differences can impact mental health, burnout, and staff turnover.

An analysis of population data can demonstrate how using broad industry codes does not tell the whole story. In a group of 661 teachers diagnosed with depression, RTW duration varied dramatically: 82 teachers returned to work in less than two weeks, 201 had a duration of three months to a year, and 174 were away from work more than a year.³

Among this population, salaries differed significantly. There may be more similarities among different industries when examining factors like health insurance access, job demand, and organizational health.⁴

In an analytic model of factors that influence recovery durations, a 55-year-old man with a medium physical job demand in the manufacturing industry can expect to return to work from generalized anxiety in 48 days versus 47 days in the retail industry — a duration change of one day. An employee with hip osteoarthritis can expect to return to work after 58 days in manufacturing versus 57 days in retail.

The physical demand of an employee’s position, access to health benefits, organizational culture, age, salary, and comorbidities may affect the RTW duration more than industry alone.⁴ Employers should, therefore, not limit their claims data review to only those in one industry. There is much to learn across industry, and the more data, the stronger the analysis. If employers wish to optimize their RTW durations, they should focus on accommodating lighter-duty assignments, providing flexibility in scheduling, and improving workplace culture, depending on their employee’s condition and needs.

References

1. United States Census. North American Industry Classification System. 2022. www.census.gov/naics/
2. Ouellette R, Frazier S, Shernoff E, et al. Teacher Job Stress and Satisfaction in Urban Schools: Disentangling Individual-, Classroom-, and Organizational-Level Influences. Behav Ther. 2018;49(4):494-508. doi:10.1016/j.beth.2017.11.011
3. MDGuidelines. Proprietary data.
4. Wu A, Roemer E, Kent K, et al. Organizational Best Practices Supporting Mental Health in the Workplace. J Occup Environ Med. 2021;63(12):e925-e931. doi:10.1097/JOM.0000000000002407