Measuring health disparities using a continuous social risk factor

Abstract

Objective: To propose and evaluate a novel approach for measuring hospital-level disparities according to the effect of a continuous, polysocial risk factor on those outcomes.Study Setting: Our cohort consisted of Medicare Fee-for-Service (FFS) patients 65 years and older admitted to acute care hospitals for one of six common conditions or procedures. Medicare administrative claims data for six hospital readmission measures including hospitalizations from July 2015 to June 2018 were used.Study Design: We adapted existing methodologies that were developed to report hospital-level disparities using dichotomous social risk factors (SRFs). The existing methods report disparities within and across hospitals; we developed and tested modified approaches for both methods using the Agency for Healthcare Research and Quality Socioeconomic Status Index. We applied the adapted methodologies to six 30-day hospital readmission measures included in the Centers for Medicare & Medicaid Services Hospital Readmissions Reduction Program measures. We compared the within-and across-hospital results for each to those obtained from using the original methods and dichotomizing the AHRQ SES Index into "low" and "high" scores.Data Collection: We used Medicare FFS administrative claims data linked to U.S. Census data.Principal Findings: For all six readmission measures we find that, when compared with the existing methods, the methods for continuous SRFs provide disparity results for more facilities though across a narrower range of values. Measures of disparity based on this approach are moderately to highly correlated with those based on a dichotomous version of the same risk factor, while reflecting a fuller spectrum of risk. This approach represents an opportunity for detection of provider-level results that more closely align with underlying social risk. Conclusion:We have demonstrated the feasibility and utility of estimating hospital disparities of care using a continuous, polysocial risk factor. This approach expands the potential for reporting hospital-level disparities while better accounting for the multifactorial nature of social risk on hospital outcomes.

Why do we evaluate 30‐day readmissions in general medicine? A historical perspective and contemporary data

“…This type of analysis was recently demonstrated to provide a more accurate measure of both readmission risk at the individual level and ranking of inpatient QOC between hospitals. 27,28 It has been suggested that driving readmission rates lower to meet financial incentives may have unintended consequences on QOC. Reductions seen in 30-day and 1-year heart failure readmissions immediately following HRRP inception were associated with increases in 30-day and 1-year mortality.…”

“…Policy decisions may similarly benefit from considering readmissions in this manner. This type of analysis was recently demonstrated to provide a more accurate measure of both readmission risk at the individual level and ranking of inpatient QOC between hospitals 27,28 …”