Simulating triage of patients into an internal medicine department to validate the use of an optimization-based workload score

Joseph Agor, Kendall McKenzie, Maria E. Mayorga, Osman Ozaltin, Riddhi S. Parikh, Jeanne Huddleston

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This study describes a simulation model that was used to evaluate a proposed workload score. The score was designed to assist in triaging patients into the hospital services of the Division of Hospital Internal Medicine at Mayo Clinic in an effort to more equitably balance workload among the division's provider teams (or services). The first part of this study was the development of a score, using Delphi surveys, conjoint analysis, and optimization methods, that accurately represents provider workload. A simulation model was then built to test the score using historical patient data. Preliminary simulation results reported the proportion of time that each provider team spent working at or above 'maximum utilization,' as defined by Mayo Clinic experts. The model yielded a 12.1% decrease (on average) in the proportion of time provider teams spent at or above maximum utilization, while simultaneously displaying a more balanced workload across provider teams.

Original languageEnglish (US)
Title of host publication2017 Winter Simulation Conference, WSC 2017
EditorsVictor Chan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2881-2892
Number of pages12
ISBN (Electronic)9781538634288
DOIs
StatePublished - Jun 28 2017
Event2017 Winter Simulation Conference, WSC 2017 - Las Vegas, United States
Duration: Dec 3 2017Dec 6 2017

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Other

Other2017 Winter Simulation Conference, WSC 2017
Country/TerritoryUnited States
CityLas Vegas
Period12/3/1712/6/17

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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