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Measuring health disparities using a continuous social risk factor.

Jeph Herrin1,2,3, Andrea Barthel1, Demetri Goutos1,4

  • 1The Yale Center for Outcomes Research and Evaluation, Yale New Haven Health Systems Corporation, New Haven, Connecticut, USA.

Health Services Research
|September 23, 2022
PubMed
Summary

This study introduces a new method to measure hospital disparities using continuous social risk factors, offering a more accurate view of care differences. The approach better reflects how social determinants impact patient outcomes across healthcare facilities.

Keywords:
determinants of healthpatient outcomesquality of caresocial determinants of health

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Area of Science:

  • Health Services Research
  • Health Disparities
  • Social Determinants of Health

Background:

  • Measuring hospital-level disparities is crucial for equitable healthcare.
  • Existing methods often use dichotomous social risk factors (SRFs), which may oversimplify complex social realities.
  • A continuous approach to SRFs could provide a more nuanced understanding of disparities.

Purpose of the Study:

  • To propose and evaluate a novel method for measuring hospital-level disparities.
  • To assess the effect of continuous, polysocial risk factors on patient outcomes.
  • To compare a continuous SRF approach with existing dichotomous methods.

Main Methods:

  • Adapted existing methodologies for reporting hospital-level disparities.
  • Utilized the Agency for Healthcare Research and Quality (AHRQ) Socioeconomic Status (SES) Index as a continuous SRF.
  • Applied methods to six 30-day hospital readmission measures using Medicare Fee-for-Service (FFS) administrative claims data.

Main Results:

  • The continuous SRF approach identified disparity results for more facilities compared to existing methods.
  • Disparity measures showed moderate to high correlation with dichotomous SRF methods but reflected a fuller spectrum of risk.
  • The novel approach aligns provider-level results more closely with underlying social risk.

Conclusions:

  • Demonstrated the feasibility and utility of estimating hospital disparities using continuous, polysocial risk factors.
  • This expanded approach enhances the reporting of hospital-level disparities.
  • The method better accounts for the multifactorial nature of social risk on hospital outcomes.