Document Type

Article

Publication Date

1-1-2023

Journal / Book Title

Journal of Global Information Management

Abstract

Artificial intelligence (AI) significantly revolutionizes and transforms the global healthcare industry by improving outcomes, increasing efficiency, and enhancing resource utilization. The applications of AI impact every aspect of healthcare operation, particularly resource allocation and capacity planning. This study proposes a multi-step AI-based framework and applies it to a real dataset to predict the length of stay (LOS) for hospitalized patients. The results show that the proposed framework can predict the LOS categories with an AUC of 0.85 and their actual LOS with a mean absolute error of 0.85 days. This framework can support decision-makers in healthcare facilities providing inpatient care to make better front-end operational decisions, such as resource capacity planning and scheduling decisions. Predicting LOS is pivotal in today’s healthcare supply chain (HSC) systems where resources are scarce, and demand is abundant due to various global crises and pandemics. Thus, this research’s findings have practical and theoretical implications in AI and HSC management.

DOI

10.4018/JGIM.323059

Rights

This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License (CC-BY) (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and production in any medium, provided the author of the original work and original publication source are properly credited.

Published Citation

Alnsour, Y., Johnson, M., Albizri, A., & Harfouche, A. H. (2023). Predicting Patient Length of Stay Using Artificial Intelligence to Assist Healthcare Professionals in Resource Planning and Scheduling Decisions. Journal of Global Information Management (JGIM), 31(1), 1-14. https://doi.org/10.4018/JGIM.323059

Download
Link to Publisher

Share

COinS