Title: A conceptual model to improve the patient flow during COVID-19

Authors: Abdesselam Bougdira; Asmae Mazti; Hayat Sedrati; Fayssal Jhilal; Saaid Amzazi; Chakib Nejjari; Hassan Ghazal

Addresses: Laboratory of Engineering Sciences, Sidi Mohamed Ben Abdellah University, Fez, Morocco ' Department of Pathology, Hassan II University Hospital, Fez, Morocco; Faculty of Medicine, Sidi Mohamed Ben Abdellah University, Fez, Morocco ' National School of Computer Sciences and Systems Analysis, Mohammed V University, Rabat, Morocco ' Faculty of Pharmacy, Mohammed VI University of Health Sciences, Casablanca, Morocco ' Department of Epidemiology and Biostatistics, International School of Public Health, Mohammed VI University of Health Sciences, Casablanca, Morocco ' Department of Epidemiology and Public Health, Faculty of Medicine, University Sidi Mohammed Ben Abdellah, Fez, Morocco; Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, Morocco ' National Center for Scientific and Technical Research (CNRST), Rabat, Morocco; School of Medicine, Mohammed VI University of Health Sciences, Casablanca, Morocco

Abstract: In the COVID-19 context, hospitals across the globe endeavour to manage the unprecedented flow of patients. Challenges are related to the unexpected increase in patients, extra waiting time for cleaning and decontamination of inpatient beds, congested queueing in treatment areas, and waiting time in crowding rooms. This research introduces a new conceptual model to bring a broader, patient-centred, and traceability-based view of patient flow in a clinical setting in the context of COVID-19. The model design opts for four interrelated modes procedural, technical, operational, and contextual. These modes lay the basis of a patient flow solution before starting its development. The feasibility of the proposed model is shown through a usage scenario and developed user interfaces. Results have shown that a knowledge representation of the patient's real-time information can enable better patient flow monitoring. In addition, it would support intelligent healthcare systems that reuse and share pieces of declarative knowledge. Such functionality would enhance the management of patient flow and improve dealing with the patient flow challenges imposed by the COVID-19 pandemic. Moreover, the presented proof of concept laid the ground for future applicability in various clinical settings facing similar infectious disease crises.

Keywords: patient flow; clinical setting; COVID-19; traceability; ontology; artificial intelligence; conceptual modelling; hospital systems.

DOI: 10.1504/IJMEI.2024.135684

International Journal of Medical Engineering and Informatics, 2024 Vol.16 No.1, pp.82 - 95

Received: 23 Apr 2021
Accepted: 12 Sep 2021
Published online: 22 Dec 2023 *