A resource-constrained, multi-unit hospital model for operational strategies evaluation under routine and surge demand scenarios

Mersedeh TariVerdi, Elise Miller-Hooks, Thomas Kirsch, Scott Levin

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)103-119
Number of pages17
JournalIISE Transactions on Healthcare Systems Engineering
Volume9
Issue number2
DOIs
StatePublished - Apr 3 2019

Keywords

  • Hospital modeling and management
  • patient flow modeling
  • predictive models
  • queueing network in health care
  • resource management

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Safety Research
  • Public Health, Environmental and Occupational Health

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