Centralized ambulance diversion policy using rolling-horizon optimization framework to minimize patient tardiness

Sohye Baek, Young Hoon Lee, Seong Hyeon Park

Research output: Contribution to journalArticlepeer-review

Abstract

Ambulance diversion (AD) is a common method for reducing crowdedness of emergency departments by diverting ambulance-transported patients to a neighboring hospital. In a multi-hospital system, the AD of one hospital increases the neighboring hospital’s congestion. This should be carefully considered for minimizing patients’ tardiness in the entire multi-hospital system. Therefore, this paper proposes a centralized AD policy based on a rolling-horizon optimization framework. It is an iterative methodology for coping with uncertainty, which first solves the centralized optimization model formulated as a mixed-integer linear programming model at each discretized time, and then moves forward for the time interval reflecting the realized uncertainty. Furthermore, the decentralized optimization, decentralized priority, and No-AD models are presented for practical application, which can also show the impact of using the following three factors: centralization, mathematical model, and AD strategy. The numerical experiments conducted based on the historical data of Seoul, South Korea, for 2017, show that the centralized AD policy outperforms the other three policies by 30%, 37%, and 44%, respectively, and that all three factors contribute to reducing patients’ tardiness. The proposed policy yields an efficient centralized AD management strategy, which can improve the local healthcare system with active coordination between hospitals.

Original languageEnglish
Article number266
JournalHealthcare (Switzerland)
Volume8
Issue number3
DOIs
Publication statusPublished - 2020

Bibliographical note

Funding Information:
Funding: This research was funded by National Research Foundation of Korea (NRF) grant number (2017R1E1A1A03070757 And The APC was funded by National Research Foundation of Korea (NRF).

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Health Policy
  • Health Information Management
  • Leadership and Management

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