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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
PubMed
Summary
This summary is machine-generated.

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.

Keywords:
Functional Comorbidity Indexadministrative datachronic health conditionsworkers’ compensation

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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.