Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study
Machine learning-based readmission prediction models utilizing nursing data provide basic data for evidence-based clinical decision support for high-risk discharge patients with complex conditions and facilitate early intervention. By integrating nursing data containing diverse patient information, these models can provide more comprehensive risk assessment and improve patient outcomes.
Authors
- Sunyoung Oh (ORCID: https://orcid.org/0000-0002-7323-6175)
- Mir Moon (ORCID: https://orcid.org/0000-0002-5086-6588)
- Eui Geum Oh (ORCID: https://orcid.org/0000-0002-6941-0708)
- Seunghyeon Cho (ORCID: https://orcid.org/0000-0002-2582-751X)
Institutions
- CJ CheilJedang (South Korea) (KR)
- Daejeon University (KR)
- Yonsei University (KR)
- Yale University (US)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-03-05
- DOI
- https://doi.org/10.2196/56671
- Citations
- 2
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 4.96