Area deprivation index and cardiac readmissions: Evaluating risk-prediction in an electronic health record

Amber E. Johnson*, Jianhui Zhu, William Garrard, Floyd W. Thoma, Suresh Mulukutla, Kiarri N. Kershaw, Jared W. Magnani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

72 Scopus citations

Abstract

BACKGROUND: Assessment of the social determinants of post-hospital cardiac care is needed. We examined the association and predictive ability of neighborhood-1 evel determinants (area deprivation index, ADI), readmission risk, and mortality for heart failure, myocardial ischemia, and atrial fibrillation. METHODS AND RESULTS: Using a retrospective (January 1, 2011-December 31, 2018) analysis of a large healthcare system, we assess the predictive ability of ADI on 30-day and 1-year readmission and mortality following hospitalization. Cox proportional hazards models analyzed time-to-event. Log rank analyses determined survival. C-statistic and net reclassification index determined the model's discriminative power. Covariates included age, sex, race, comorbidity, number of medications, length of stay, and insurance. The cohort (n=27 694) had a median follow-up of 46.5 months. There were 14 469 (52.2%) men and 25 219 White (91.1%) patients. Patients in the highest ADI quintile (versus lowest) were more likely to be admitted within 1 year of index heart failure admission (hazard ratio [HR], 1.25; 95% CI, 1.03-1.51). Patients with myocardial ischemia in the highest ADI quintile were twice as likely to be readmitted at 1 year (HR, 2.04; 95% CI, 1.44-2.91]). Patients with atrial fibrillation living in areas with highest ADI were less likely to be admitted within 1 year (HR, 0.79; 95% CI, 0.65-0.95). As ADI increased, risk of readmission increased, and risk reclassification was improved with ADI in the models. Patients in the highest ADI quintile were 25% more likely to die within a year (HR, 1.25 1.08-1.44). CONCLUSIONS: Residence in socioeconomically disadvantaged communities predicts rehospitalization and mortality. Measuring neighborhood deprivation can identify individuals at risk following cardiac hospitalization.

Original languageEnglish (US)
Article numbere020466
JournalJournal of the American Heart Association
Volume10
Issue number13
DOIs
StatePublished - 2021

Funding

Dr Magnani has received significant research grants from the National Institutes of Health. The remaining authors have no disclosures to report.

Keywords

  • Electronic health record
  • Readmissions
  • Risk prediction
  • Social determinants of health

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

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