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Uncovering effective process improvement strategies in an emergency department using discrete event simulation

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  • Oh Hong Choon
  • Zhang Dali
  • Phua Tien Beng
  • Chow Peck Yoke Magdalene

Abstract

This study aimed to develop a discrete event simulation (DES) model that realistically represented the process flow of selected non-fever patients in Singapore General Hospital (SGH) Emergency Department (ED). This model was then to be employed to evaluate the impact of different operational strategies on two performance measures, namely, time to first consult (TFC) and turnaround time (TT) of patients at ED. The DES model is used to represent ED sub-processes, including screening, registration, triage, consultation, observation ward visits, procedure room processes, laboratory and diagnostic radiological testing. Upon validating the model by comparing its performance projection with historical data, it was then employed to evaluate effectiveness of several new operational strategies. In the validation, we use the data of ED patients from May 2011 to July 2011 to characterize the load, arrival and resource-utilization pattern of its patients. Medical records of randomly sampled patients from the same period were also reviewed to evaluate the utilization levels of laboratory, diagnostic radiological, observation ward resources among ED patients. On the basis of DES model projections, redeployment of doctors with their hourly availability matching patient arrival pattern would yield the best improvement among the evaluated operational strategies. The manpower redeployment strategy required no additional man-hour compared to baseline requirement. In addition, via numerical results for a set of potential operational strategies, we show that there exists ample room for improvement in TFC and TTs of selected non-fever patients at SGH ED.

Suggested Citation

  • Oh Hong Choon & Zhang Dali & Phua Tien Beng & Chow Peck Yoke Magdalene, 2014. "Uncovering effective process improvement strategies in an emergency department using discrete event simulation," Health Systems, Taylor & Francis Journals, vol. 3(2), pages 93-104, June.
    • Handle: RePEc:taf:thssxx:v:3:y:2014:i:2:p:93-104
    DOI: 10.1057/hs.2014.2
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