Utility of Socioeconomic Status in Predicting 30-Day Outcomes after Heart Failure Hospitalization

Zubin J. Eapen*, Lisa A. McCoy, Gregg C. Fonarow, Clyde W. Yancy, Marie Lynn Miranda, Eric D. Peterson, Robert M. Califf, Adrian F. Hernandez

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Background-An individual's socioeconomic status (SES) is associated with health outcomes and mortality, yet it is unknown whether accounting for SES can improve risk-adjustment models for 30-day outcomes among Centers for Medicare & Medicaid Services beneficiaries hospitalized with heart failure. Methods and Results-We linked clinical data on hospitalized patients with heart failure in the Get With The Guidelines-Heart Failure database (January 2005 to December 2011) with Centers for Medicare & Medicaid Services claims and county-level SES data from the 2012 Area Health Resources Files. We compared the discriminatory capabilities of multivariable models that adjusted for SES, patient, and hospital characteristics to determine whether county-level SES data improved prediction or changed hospital rankings for 30-day all-cause mortality and rehospitalization. After adjusting for patient and hospital characteristics, median household income (per $5000 increase) was inversely associated with odds of 30-day mortality (odds ratio, 0.97; 95% confidence interval, 0.95-1.00; P=0.032) and the percentage of people with at least a high school diploma (per 5 U increase) was associated with lower odds of 30-day rehospitalization (odds ratio, 0.95; 95% confidence interval, 0.91-0.99). After adjustment for county-level SES data, relative to whites, Hispanic ethnicity (odds ratio, 0.70; 95% confidence interval, 0.58-0.83) and black race (odds ratio, 0.57; 95% confidence interval, 0.50-0.65) remained significantly associated with lower 30-day mortality, but had similar 30-day rehospitalization. County-level SES did not improve risk adjustment or change hospital rankings for 30-day mortality or rehospitalization. Conclusions-County-level SES data are modestly associated with 30-day outcomes for Centers for Medicare & Medicaid Services beneficiaries hospitalized with heart failure, but do not improve risk adjustment models based on patient characteristics alone.

Original languageEnglish (US)
Pages (from-to)473-480
Number of pages8
JournalCirculation: Heart Failure
Volume8
Issue number3
DOIs
StatePublished - May 4 2015

Keywords

  • heart failure
  • predictive models
  • risk stratification

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

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