The Utility of Nursing Notes Among Medicare Patients With Heart Failure to Predict 30-Day Rehospitalization: A Pilot Study

• Published in: The Journal of cardiovascular nursing Vol. 37; no. 6; p. E181
• Main Authors: Kang, Youjeong, Topaz, Maxim, Dunbar, Sandra B, Stehlik, Josef, Hurdle, John
• Format: Journal Article
• Language: English
• Published: United States 01.11.2022
• Subjects: Aged; Electronic Health Records; Heart Failure - therapy; Humans; Medicare; Natural Language Processing; Patient Readmission; Pilot Projects; United States; United States
• ISSN: 1550-5049
• DOI: 10.1097/JCN.0000000000000871

For patients with heart failure (HF), there have been efforts to reduce the risk of 30-day rehospitalization, such as developing predictive models using electronic health records. Few previous studies used clinical notes to predict 30-day rehospitalization. The aim of this study was to assess the utility of nursing notes versus discharge summaries to predict 30-day rehospitalization among patients with HF. In this pilot study, we used free-text discharge summaries and nursing notes collected from a tertiary hospital. We randomly selected 500 Medicare patients with HF. We followed the natural language processing and machine learning pipeline for data analysis. Thirty-day rehospitalization risk prediction using discharge summaries (n = 500) produced an area under the receiver operating characteristic curve of 0.74 (Bag of Words + Neural Network). Thirty-day rehospitalization risk prediction using nursing notes (n = 2046) resulted in an area under the receiver operating characteristic curve of 0.85 (Bag of Words + Neural Network). Nursing notes provide a superior input to risk models for 30-day rehospitalization in Medicare patients with HF compared with discharge summaries.