An intelligent scheduling of non-critical patients admission for emergency department

Eva Bruballa, Alvaro Wong*, Dolores Rexachs, Emilio Luque

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The combination of the progressive growth of an aging population, increased life expectancy and a greater number of chronic diseases all contribute significantly to the growing demand for emergency medical care, and thus, causing saturation in Emergency Departments (EDs). This saturation is usually due to the admission of non-urgent patients, who constitute a high percentage of patients in an ED. The Agent-based Model (ABM) is one of the most important tools that helps to study complex systems and explores the emergent behavior of this type of department. Its simulation more accurately reflects the complexity of the operation of real systems. Our proposal is the design of an ABM to schedule the access of these non-critical patients into an ED, which can be useful for the service management dealing with the actual growing demand for emergency care. We suppose that a relocation of these non-critical patients within the expected input pattern, provided initially by historical records, enables a reduction in waiting time for all patients, and therefore, it will lead to an improvement in the quality of service. It would also allow us to avoid long waiting times. This research offers the availability of relevant knowledge for Emergency Department managers in order to help them make decisions to improve the quality of the service, in anticipation of the expected growing demand of the service in the very near future.

Original languageEnglish
Article number8945359
Pages (from-to)9209-9220
Number of pages12
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

Keywords

  • Agent-based modeling and simulation (ABMS)
  • decision support systems (SDS)
  • Emergency Department (ED)
  • length of stay (LoS)
  • response capacity

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