Demand and Capacity Modelling for Acute Services using Discrete Event Simulation

Eren Demir, Murat Gunal, David Southern

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
86 Downloads (Pure)

Abstract

Increasing demand for services in England with limited healthcare budget has put hospitals under immense pressure. Given that almost all National Health Service (NHS) hospitals have severe capacity constraints (beds and staff shortages) a decision support tool (DST) is developed for the management of a major NHS Trust in England. Acute activities are forecasted over a 5 year period broken down by age groups for 10 specialty areas. Our statistical models have produced forecast accuracies in the region of 90%. We then developed a discrete event simulation model capturing individual patient pathways until discharge (in A&E, inpatient and outpatients), where arrivals are based on the forecasted activity outputting key performance metrics over a period of time, e.g., future activity, bed occupancy rates, required bed capacity, theatre utilisations for electives and non-electives, clinic utilisations, and diagnostic/treatment procedures. The DST allows Trusts to compare key performance metrics for 1,000’s of different scenarios against their existing service (baseline). The power of DST is that hospital decision makers can make better decisions using the simulation model with plausible assumptions which are supported by statistically validated data.
Original languageEnglish
Pages (from-to)33-40
Number of pages8
JournalHealth Systems
Volume6
Issue number1
Early online date11 Mar 2016
DOIs
Publication statusPublished - 1 Mar 2017

Keywords

  • simulation
  • decision support system
  • hospital capacity
  • hospital resources

Fingerprint

Dive into the research topics of 'Demand and Capacity Modelling for Acute Services using Discrete Event Simulation'. Together they form a unique fingerprint.

Cite this