Teo, Kareen and Yong, Ching Wai and Chuah, Joon Huang and Hasikin, Khairunnisa and Salim, Maheza Irna Mohd and Hum, Yan Chai and Lai, Khin Wee (2022) Assessing clinical usefulness of readmission risk prediction model. In: 6th Kuala Lumpur International Conference on Biomedical Engineering, BioMed 2021, 28-29 July 2021, Virtual, Online.
Full text not available from this repository.Abstract
Readmission manifests signs of degraded quality of care and increased healthcare cost. Such adverse event may be attributed to premature discharge, unsuccessful treatments, or worsening comorbidities. Predictive modeling provides useful information to identify patients at a higher risk for readmission for targeted interventions. Though many studies have proposed readmission risk predictive models and validated their discriminative ability with performance metrics, few examined the net benefit realized by a predictive model. We compared traditional logistic regression against modern neural network to predict unplanned readmission. An added value of 7 on discriminative ability is observed for modern machine learning model compared to regression. A cost analysis is provided to assist physicians and hospital management for translating the theoretical value into real cost and resource allocation after model implementation. The neural network model is projected to contribute 15× more savings by reducing readmissions. Aside from constructing better performing models, the results of our study demonstrate the potential of a clinically helpful prediction tool in terms of strategies to reduce cost associated with readmission. © 2022, Springer Nature Switzerland AG.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | Universiti Malaya [Grant no. IF015-2021] |
| Uncontrolled Keywords: | Cost benefit analysis; Forecasting; Patient treatment; Risk assessment; Adverse events; Comorbidities; Cost saving; Discriminative ability; Health care costs; Performance metrices; Predictive models; Quality of care; Readmission; Risk prediction models; Hospitals |
| Subjects: | R Medicine T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Biomedical Engineering Department Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 12 Feb 2025 08:01 |
| Last Modified: | 12 Feb 2025 08:01 |
| URI: | http://eprints.um.edu.my/id/eprint/43429 |
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