A comprehensive and integrated hospital decision support system for efficient and effective healthcare services delivery using discrete event simulation

Muhammed Ordu, Eren Demir, Chris Tofallis, Murat Gunal

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Abstract

The difficulty that hospital management has been experiencing over the past decade in balancing demand and capacity needs is unprecedented in the United Kingdom. Due to a shortage of capacity, hospitals cannot treat all patients. We developed a whole hospital-level decision support system to assess and respond to the needs of local populations. We integrated a comparative forecasting approach and discrete event simulation modelling using Hospital Episode Statistics and local datasets. It is clear from the literature that this level of whole hospital simulation model has never been developed before (an innovative decision support system). First, the demands of all hospital specialties were forecasted, and the forecasts were embedded into the simulation model as input. Secondly, a simulation model was developed to capture the patient pathway of all specialties. The model integrates every component of a hospital to aid with efficient and effective use of scarce resources (e.g., staff and beds). As a result, the hospital can meet the increasing demand with its current resources. According to the scenario analysis, the hospital bed occupancy rate will reach the national target (i.e., 85%), and the total hospital revenue will increase by approximately 13%, with a 10% increase in A&E and outpatient and a 20% increase in inpatient demand. In conclusion, the hospital-level simulation model can become a crucial instrument for decision-makers to provide an efficient service for hospitals in England and other parts of the world.
Original languageEnglish
Article number100248
Number of pages18
JournalHealthcare Analytics
Volume4
Early online date1 Sept 2023
DOIs
Publication statusPublished - 31 Dec 2023

Keywords

  • Discrete event simulation
  • Efficiency and productivity
  • Experimental design
  • Forecasting
  • Healthcare services delivery
  • Hospital decision support system

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