A Simulation Study on Demand Disruptions and Limited Resources for Healthcare Provision

Juliana Bowles, Ricardo M. Czekster*, Guilherme Redeker, Thais Webber

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Philanthropic hospitals in Brazil are in great part funded by the government and are daily accessed by a large portion of the population. As the Brazilian economy faces deep cuts in healthcare, managers are adjusting budgets and focusing on less expensive alternatives such as process improvements. Hospitals are even more impacted by the recent COVID-19 pandemic with widespread disruption on operational processes forcing them to stretch resources. Thus, it brings an opportunity to evaluate the actual performance of these settings under different scenarios where analysts may address bottlenecks and the impact on resources. Our focus is to quantify the capacity of an emergency department to support patient demand with limited resources in pre and post-pandemic scenarios. We use a 12-month longitudinal dataset consisting of pre-pandemic emergency occurrences and assigned resources.
Original languageEnglish
Title of host publicationFrom Data to Models and Back - 9th International Symposium, DataMod 2020, Revised Selected Papers
EditorsJuliana Bowles, Giovanna Broccia, Mirco Nanni
PublisherSpringer
Pages87-103
Number of pages17
ISBN (Electronic)978-3-030-70650-0
ISBN (Print)978-3-030-70649-4
DOIs
Publication statusPublished - 5 Mar 2021
Event9th International Symposium on From Data Models and Back, DataMod 2020 - Virtual, Online
Duration: 20 Oct 202020 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12611 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Symposium on From Data Models and Back, DataMod 2020
CityVirtual, Online
Period20/10/2020/10/20

Keywords

  • COVID-19
  • Emergency department
  • Healthcare processes
  • Process simulation

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