Social Determinants of Health Improve Predictive Accuracy of Clinical Risk Models for Cardiovascular Hospitalization, Annual Cost, and Death

Gmerice Hammond, Kenton Johnston, Kristine Huang, Karen E. Joynt Maddox

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Background: Risk models in the private insurance setting may systematically underpredict in the socially disadvantaged. In this study, we sought to determine whether US minority Medicare beneficiaries had disproportionately low costs compared with their clinical outcomes and whether adding social determinants of health (SDOH) into risk prediction models improves prediction accuracy. Methods and Results: Retrospective observational cohort study of 2016 to 2017 Medicare Current Beneficiary Survey data (n=3614) linked to Medicare fee-for-service claims. Logistic and linear regressions were used to determine the relationship between race/ethnicity and annual costs of care, all-cause hospitalization, cardiovascular hospitalization, and death. We calculated the observed-to-expected (O:E) ratios for all outcomes under 4 risk models: (1) age+sex, (2) model 1+clinical comorbidity adjustment, (3) model 2+SDOH, and (4) SDOH alone. Our sample was 44% male and 11% black or Hispanic. Among minorities, adverse clinical outcomes were inversely related to cost. After multivariable adjustment, blacks/Hispanics had higher rates of cardiovascular hospitalization (incidence rate ratio, 1.78; P=0.012) but similar annual costs ($-336, P=0.77) compared with whites. Among whites, models 1 to 4 all showed similar O:E ratios, suggesting high accuracy in risk prediction using current models. Among minorities, adjustment for age, sex, and comorbidities underpredicted all-cause hospitalization by 20% (O:E, 1.20) and cardiovascular hospitalization by 70% (O:E, 1.70) and overpredicted death by 21% (O:E, 0.79); adding SDOH brought O:E near 1 for all outcomes. Among both groups, the SDOH risk model alone performed with equal or superior accuracy to the model based on clinical comorbidities. Conclusions: A paradoxical relationship was observed between clinical outcomes and costs among racial and ethnic minorities. Because of systematic differences in access to care, cost may not be an appropriate surrogate for predicting clinical risk among vulnerable populations. Adjustment for SDOH improves the accuracy of risk models among racial and ethnic minorities and could guide use of prevention strategies.

Original languageEnglish
Article numbere006752
Pages (from-to)290-299
Number of pages10
JournalCirculation: Cardiovascular Quality and Outcomes
DOIs
StateAccepted/In press - 2020

Keywords

  • cohort studies
  • ethnic groups
  • health policy
  • linear models
  • primary prevention

Fingerprint

Dive into the research topics of 'Social Determinants of Health Improve Predictive Accuracy of Clinical Risk Models for Cardiovascular Hospitalization, Annual Cost, and Death'. Together they form a unique fingerprint.

Cite this