Predicting Heart Failure Readmissions

J Cardiovasc Nurs. 2016 Mar-Apr;31(2):114-20. doi: 10.1097/JCN.0000000000000225.

Abstract

Objectives: In this study, the effects of sociodemographic and clinical factors on heart failure (HF) readmission risk were examined.

Background: Hospitals now incur financial penalties for excessive HF readmission rates; therefore, identifying factors associated with risk is essential for designing risk-reduction strategies.

Methods: A retrospective cohort study using chart reviews compared HF inpatients (N = 245) who were readmitted with those who were not readmitted.

Results: The sample included mostly white (64%) elderly (mean [SD] age, 69.8 [15.1] years) men (49%) and women (51%). Using Cox regression, the number of comorbidities (3-4 or 5-8) and type of comorbidities, specifically renal insufficiency (readmission ratio [RR], 1.7; P = .003), atrial fibrillation (RR, 1.7; P = .005), cardiomyopathy (RR, 1.5; P = .020), followed by a history of myocardial infarction/coronary artery disease (RR, 1.4; P = .055), were the predictors of HF readmission.

Conclusions: Targeting those with high-risk comorbidities is important in designing measures to prevent or delay readmission of HF patients.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Cohort Studies
  • Coronary Artery Bypass / statistics & numerical data
  • Female
  • Follow-Up Studies
  • Heart Failure / epidemiology*
  • Heart Failure / therapy*
  • Hospitalization / trends
  • Humans
  • Length of Stay / trends*
  • Male
  • Middle Aged
  • Patient Readmission / trends*
  • Prognosis
  • Risk Assessment
  • Vascular Surgical Procedures / statistics & numerical data