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Collider Bias in Administrative Workers’ Compensation Claims Data: A Challenge for Cross-Jurisdictional Research

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Abstract

Purpose

Workers’ compensation claims consist of occupational injuries severe enough to meet a compensability threshold. Theoretically, systems with higher thresholds should have fewer claims but greater average severity. For research that relies on claims data, particularly cross-jurisdictional comparisons of compensation systems, this results in collider bias that can lead to spurious associations confounding analyses. In this study, I use real and simulated claims data to demonstrate collider bias and problems with methods used to account for it.

Methods

Using Australian claims data, I used a linear regression to test the association between claim rate and mean disability durations across Statistical Areas. Analyses were repeated with nesting by state/territory to account for variations in compensability thresholds across compensation systems. Both analyses are repeated on left-censored data. Simulated claims data are analysed with Cox survival analyses to illustrate how left-censoring can reverse effects.

Results

The claim rate within a Statistical Area was inversely associated with disability duration. However, this reversed when Statistical Areas were nested by state/territory. Left-censoring resulted in an attenuation of the unnested association to non-significance, while the nested association remained significantly positive. Cox regressions with simulated claims data demonstrated how left-censoring can reverse effects.

Conclusions

Collider bias can seriously confound work disability research, particularly cross-jurisdictional comparisons. Work disability researchers must grapple with this challenge by using appropriate study designs and analytical approaches, and considering how it affects the interpretation of results.

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Data Availability

Case-level claims data contain potentially re-identifiable data and therefore cannot be publicly shared. Aggregate-level claims data used, NBA player data, and simulated data have been archived have all available on a public repository [27].

Code Availability

All cleaning, data simulation, and analytical code have been archived on a public repository [27].

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Acknowledgements

I would like to thank my supervisor and editor of this special edition, Professor Alex Collie, for his comments on an earlier version of this manuscript.

Funding

This study was funded by an Australian Research Council Discovery Project Grant (DP190102473), as part of the Compensation and Return to Work Effectiveness (COMPARE) Project, and by Safe Work Australia, a government statutory agency that develops national work health and safety and workers’ compensation policy.

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Authors and Affiliations

  1. School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC, 3181, Australia

    Tyler J. Lane

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  1. Tyler J. Lane
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This paper is the sole work of TJL.

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Correspondence to Tyler J. Lane.

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Conflict of interest

The author previously received salary support from funding provided by the workers’ compensation systems investigated in this study.

Ethical Approval

This study received ethics approval from the Monash University Human Research Ethics Committee (CF14/2995 – 2014001663).

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Lane, T.J. Collider Bias in Administrative Workers’ Compensation Claims Data: A Challenge for Cross-Jurisdictional Research. J Occup Rehabil 32, 161–169 (2022). https://doi.org/10.1007/s10926-021-09988-1

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