A Queueing Network Model for Analysis of Patient Transitions Within Hospitals

Hyo Kyung Lee, Albert J. Musa, Philip A. Bain, Kenneth Nelson, Christine Baker, Jingshan Li

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Safe and efficient patient transitions are of critical importance to ensure patient safety and care quality. To study patient transitions, this paper presents a queueing network model-based iteration method to model and analyze transitions between emergency department, intensive care unit, and general ward within a hospital. Routings with feedback flows are considered under general arrival and service processes, and the effects of blocking on performance measures are presented for both the mean and variability. It is shown that the iteration procedure is convergent and leads to acceptable accuracy of estimation, for both small- and large-sized hospitals. In addition, the impacts of bed capacity, admission rate, as well as arrival and service time variabilities are discussed. Such a method provides an efficient way to study patient transitions within hospitals.

Original languageEnglish
Article number8288827
Pages (from-to)6-20
Number of pages15
JournalIEEE Transactions on Automation Science and Engineering
Volume16
Issue number1
DOIs
Publication statusPublished - 2019 Jan
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

  • Emergency department (ED)
  • intensive care unit (ICU)
  • iteration procedure
  • patient transition
  • queueing network
  • ward

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A Queueing Network Model for Analysis of Patient Transitions Within Hospitals'. Together they form a unique fingerprint.

Cite this