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Parametric hazard rate models for long-term sickness absence.

Petra C Koopmans¹, Corné A M Roelen, Johan W Groothoff

¹Department of Occupational Health Services, ArboNed Noord-Oost Nederland, Groningen, The Netherlands. petra.koopmans@arboned.nl

International Archives of Occupational and Environmental Health

|October 22, 2008

Summary

Parametric models better describe sickness absence and return to work durations than traditional Cox models. The exponential model fits sickness absence onset, while Gompertz-Makeham models fit return to work.

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Published on: October 23, 2020

Area of Science:

Occupational Health
Biostatistics
Epidemiology

Background:

Cox proportional hazard models are commonly used for sickness absence duration.
Parametric models are preferred when time is an independent variable.

Purpose of the Study:

Compare parametric hazard rate models for sickness absence onset and return to work.
Evaluate suitability of different parametric models for time-dependent processes.

Main Methods:

Prospective cohort study of 53,830 Dutch private sector employees.
Modeled time to long-term sickness absence (>6 weeks) and return to work.
Utilized parametric hazard rate models.

Main Results:

Exponential parametric model with constant hazard rate best described sickness absence onset.
Gompertz-Makeham models with declining hazard rates best described return to work.
Parametric models offer more flexibility than Cox models.

Conclusions:

Parametric models provide advantages for analyzing time-dependent processes like sickness absence and return to work.
Benefits of parametric models over Cox models are more pronounced for return to work than for sickness absence onset.