A resource-constrained, multi-unit hospital model for operational strategies evaluation under routine and surge demand scenarios. Issue 2 (3rd April 2019)

• Record Type: Journal Article
• Authors: TariVerdi, Mersedeh; Miller-Hooks, Elise; Kirsch, Thomas; Levin, Scott
• Is Part Of: IISE transactions on healthcare systems engineering. Volume 9:Issue 2(2019)
• Page Start: 103
• Page End: 119
• Publication Date: 2019-04-03
• Subjects: Hospital modeling and management -- patient flow modeling -- predictive models -- queueing network in health care -- resource management; Biomedical engineering -- Periodicals; Medical informatics -- Periodicals; Medical care -- Periodicals; 610.28
• DOI: 10.1080/24725579.2019.1584132
• Languages: English
• ISSNs: 2472-5579

Abstract

Abstract: A patient-based, resource-constrained, multi-unit hospital model is presented for evaluating hospital performance in routine and surge demand scenarios. Physical spaces, patients, medical providers and resources associated with patient care paths spanning hospital units are identified and explicitly modeled. While hospital operations have been extensively studied in the literature, these works primarily focus on individual units and implicitly assume an abundance of resources. This article seeks to fill this gap with a proposed modeling framework that is built on an open queueing network conceptualization of the hospital. The model takes a patient-based perspective. This perspective reveals bottlenecks that are created through interactions between units that arise through shared resources or common downstream capacity requirements as a function of patient needs. That is, interdependencies between units in a hospital emanate from resources (staff and stuff) shared across units, but also depend on the needs of the patients moving through cross-unit care paths. Information critical to hospital modeling obtained through interviews with Johns Hopkins Hospital System personnel is synthesized and applied in developing a generic, urban hospital. The generic hospital model and related predictive models were developed to examine the benefits of the proposed approach.