A Markov chain approach to study flow disruptions on surgery in emergency care

Xiufeng Shao, Jingshan Li, Douglas A. Wiegmann

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

The work flow of surgical operations in emergency department can be interrupted due to various disruptions. Reducing such disruptions is of significant importance to ensure successful operations. In this paper, we introduce a continuous time Markov chain model to analyze the disruptions and their impacts. Analytical formulas have been derived to evaluate the probabilities of normal operations and disruptions. A continuous improvement method has been developed to identify the disruption that impedes surgical operation in the strongest manner. Such a disruption is referred to as the bottleneck disruption (BN-d). Reducing the interruption time of the BNd can lead to the largest improvement in normal operation. An application of the method at an emergency department of a large academic medical center is presented to illustrate the effectiveness of the model and the improvement approach. It is discovered that the disruption due to coordination problem is the system bottleneck. © 2013 IEEE.
Original languageEnglish
Title of host publication2013 IEEE International Conference on Automation Science and Engineering, CASE 2013
Pages990-995
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 IEEE International Conference on Automation Science and Engineering, CASE 2013 - Madison, WI, United States
Duration: 17 Aug 201320 Aug 2013

Publication series

NameIEEE International Conference on Automation Science and Engineering
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference2013 IEEE International Conference on Automation Science and Engineering, CASE 2013
PlaceUnited States
CityMadison, WI
Period17/08/1320/08/13

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work is supported in part by NSF Grant No. CMMI-1233807.

Research Keywords

  • bottleneck
  • continuous time Markov chain
  • Emergency care
  • flow disruptions
  • surgery

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