Reliability of Predicting Early Hospital Readmission After Discharge for an Acute Coronary Syndrome Using

David D McManus1, Jane S Saczynski1, Darleen Lessard2

  • 1Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Medicine, Meyers Primary Care Institute, University of Massachusetts Medical School, Worcester, Massachusetts.

Insights

Early rehospitalization after acute coronary syndrome is common. An enhanced model, including factors beyond claims data, better predicts readmission risk for patients over 65 years. This improves hospital quality assessment.

Area of Science:

  • Cardiology
  • Health Services Research
  • Geriatrics

Background:

  • Early rehospitalization after acute coronary syndrome (ACS) is a significant concern.
  • Centers for Medicare and Medicaid Services (CMS) use claims data for risk-adjusted readmission models.
  • Factors beyond claims data may influence readmission risk.

Purpose of the Study:

  • To compare a CMS-like readmission prediction model with an enhanced model.
  • To identify additional clinical, psychosocial, and sociodemographic factors impacting readmission.
  • To assess the discriminative ability of the enhanced model.

Main Methods:

  • Analysis of 804 patients >65 years discharged after ACS (2011-2013).
  • Comparison of a claims-based model with an enhanced model including additional patient characteristics.
  • Principal components analysis used for model enhancement.

Main Results:

  • Enhanced model identified previous coronary intervention, chronic kidney disease, and low health literacy as significant predictors of readmission.
  • Lower serum sodium levels and current nonsmoker status were also associated with higher readmission risk.
  • The enhanced model demonstrated higher discriminative ability compared to the claims-based model.

Conclusions:

  • Measurable factors not included in CMS claims-based models influence ACS readmission.
  • Incorporating additional patient data can improve the accuracy of readmission risk models.
  • Enhanced risk models may offer a more valid assessment of hospital quality.

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