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Using the Functional Comorbidity Index with administrative workers' compensation data: Utility, validity, and
Jeanne M Sears1,2,3, Sean D Rundell1,4,5, Deborah Fulton-Kehoe2
1Department of Health Systems and Population Health, University of Washington, Seattle, Washington, USA.
American Journal of Industrial Medicine
|November 20, 2023
Summary
The Functional Comorbidity Index (FCI) derived from workers' compensation (WC) data shows low sensitivity for identifying chronic conditions and predicting work outcomes. Cross-state use of WC-based FCI may introduce confounding, necessitating caution and state-specific validation.
Area of Science:
- Occupational Health
- Health Services Research
- Biostatistics
Background:
- Chronic health conditions significantly affect worker outcomes but are difficult to quantify using administrative workers' compensation (WC) data.
- The Functional Comorbidity Index (FCI) is established for predicting functional outcomes in community settings but requires validation within WC populations.
- Assessing a WC-derived FCI for identifying chronic conditions and predicting work-related outcomes is crucial for improving worker health management.
Purpose of the Study:
- To validate a workers' compensation (WC)-based Functional Comorbidity Index (FCI) for identifying chronic conditions in injured workers.
- To evaluate the predictive validity of the WC-based FCI for key work-related outcomes.
- To assess the utility of the WC-based FCI for controlling confounding in multi-state studies.
Main Methods:
- Linked administrative WC data with prospective survey data from injured workers in Ohio and Washington.
- Collected survey data at 6 weeks and 6 months post-injury, using survey-derived FCI as the reference standard.
- Assessed predictive validity and confounding control using 6-month work-related outcomes.
Main Results:
- The WC-based FCI demonstrated high specificity but low sensitivity for identifying chronic conditions, with weak associations with work outcomes.
- Survey-based FCI indicated higher comorbidity in Ohio (mean=1.38) vs. Washington (mean=1.14); WC-based FCI showed the reverse (Ohio mean=0.10 vs. Washington mean=0.33).
- Substituting WC-based FCI in multi-state models shifted state effect estimates away from null (8.95% change), unlike survey-based FCI (<1% change).
Conclusions:
- The WC-based FCI may identify specific worker subsets with chronic conditions but is less effective for estimating overall prevalence.
- Cross-state application of the WC-based FCI can introduce significant confounding, potentially distorting study findings.
- Recommend state-specific validation using reliable reference standards before employing WC-based FCI in multi-state research.
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