Predicting readmission of heart failure patients using automated follow-up calls.

Shelby Inouye¹, Vasileios Bouras², Eric Shouldis³, Adam Johnstone³, Zachary Silverzweig², Pallav Kosuri⁴

¹Keck School of Medicine of USC, Los Angeles, CA, USA.

²CipherHealth, New York, NY, USA.

³Department of Internal Medicine, Charleston Area Medical Center, Charleston, WV, USA.

⁴Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, 02138, USA. pallavkosuri@fas.harvard.edu.

PubMed PMC DOI PDF

Abstract

BACKGROUND: Readmission rates for patients with heart failure (HF) remain high. Many efforts to identify patients at high risk for readmission focus on patient demographics or on measures taken in the hospital. We evaluated a method for risk assessment that depends on patient self-report following discharge from the hospital. METHODS: In this study, we investigated whether automated calls could b…

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