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Lookup NU author(s): Dr Xiang XieORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Conventional hospital facility management (FM) focuses on reasonably allocating various resources to support core healthcare services from the perspectives of the FM department and hospital. However, since patients are the main service targets of hospitals, the patients’ demographic and hospitalization information can be integrated to support the patient-centric facility management, aiming at a higher level of patient satisfaction with respect to the hospital environment and services. Taking the pharmaceutical services in hospital inpatient departments as the case, forecasting the pharmaceutical demands based on the admitted patients’ information contributes to not only better logistics management and cost containment, but also to securing the medical requirements of individual patients. In patient-centric facility management, the pharmacy inventory is regarded as the combination of medical resources that are reserved and allocated to each admitted patient. Two forecasting models are trained to predict the inpatients’ total medical requirement at the beginning of the hospitalization and rectify the patients’ length of stay after early treatment. Specifically, once a patient is admitted to the hospital, certain amounts of medical resources are reserved, according to the inpatient’s gender, age, diagnosis, and their preliminary expected days in the hospital. The allocated inventory is updated after the early treatment by rectifying the inpatient’s estimated length of stay. The proposed procedure is validated using medical data from eighteen hospitals in a Chinese city. This study facilitates the integration of patient-related information with the conventional FM processes and demonstrates the potential improvement in patients’ satisfaction with better hospital logistics and pharmaceutical services.
Author(s): Xie X, Fang ZG, Chen L, Lu QC, Tan T, Ye Z, Pitt M
Publication type: Article
Publication status: Published
Online publication date: 23/06/2022
Acceptance date: 21/06/2022
Date deposited: 08/11/2022
ISSN (electronic): 2075-5309
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