Peer-Reviewed Publication
J Nurs Scholarsh2025;57(1):165-177.January 1, 2025Journal Article
Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure.
Sena Chae1, Anahita Davoudi2, Jiyoun Song3, Lauren Evans2, Kathryn H Bowles4,5, Margaret V Mcdonald2, Yolanda Barrón2, Se Hee Min6, Sungho Oh4, Danielle Scharp7, Zidu Xu8, Maxim Topaz2,8,9
1College of Nursing, The University of Iowa, Iowa City, Iowa, USA.
2Center for Home Care Policy & Research, VNS Health, New York, New York, USA.
3University of Pennsylvania School of Nursing, Department of Biobehavioral Health Sciences, Philadelphia, Pennsylvania, USA.
4NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA.
5Vice President and Director of the Center for Home Care Policy & Research, VNS Health, New York City, New York, USA.
6University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA.
7Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
8Columbia University School of Nursing, New York City, New York, USA.
9Data Science Institute, Columbia University, New York City, New York, USA.
Abstract
BACKGROUND: The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospita…
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