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Linking predictive and prescriptive analytics of elderly and frail patient hospital services

Williams, Elizabeth, Gartner, Daniel and Harper, Paul 2022. Linking predictive and prescriptive analytics of elderly and frail patient hospital services. Presented at: 10th IEEE International Conference on Healthcare Informatics (ICHI 2022), Rochester, MN, United States, 11-14 June 2022.

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Abstract

Predictive and prescriptive techniques are being evaluated to predict demand for inpatient services within South East Wales. This work is specifically focusing on multi-site hospital services for elderly and frail patients, using classification and regression trees to determine patient clusters with similar attributes, yielding results of up to 89.62% accuracy. By incorporating these results into mathematical models we aim to quantify the value of incorporating the clustering results in a deterministic and stochastic mathematical programme. Index Terms—Machine Learning, Mathe

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: In Press
Schools: Mathematics
Uncontrolled Keywords: Machine Learning, Mathematical Programming, Stochastic Programming
Additional Information: https://ohnlp.github.io/IEEEICHI2022/
Funders: KESS2
Date of First Compliant Deposit: 13 May 2022
Date of Acceptance: 31 March 2022
Last Modified: 15 Jun 2022 01:30
URI: https://orca.cardiff.ac.uk/id/eprint/149326

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