Simulating wait time in healthcare: Accounting for transition process variability using survival analyses

Scott Levin, Maxim Garifullin

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

2 Scopus citations


Wait or queuing time is a principal performance measure for many discrete-event simulation (DES) models in healthcare. However, variation in wait time is often caused by both occupied downstream servers (e.g., beds) and organizational and human transition processes. DES models that attribute wait solely to occupied servers, ignoring transition process variability, face challenges in adequate baseline validation. Embedding regression models for survival data in DES to estimate patient wait times is a method capable of integrating the effects of transition processes with queuing. Developing these models as a sub-component is further valuable in understanding the socio-technical system factors that drive prolonged waits. These general methods are exhibited in a DES for a large urban hospital with a primary output of wait time in the emergency department (ED) for transfer to an inpatient bed (boarding time). Simulated boarding time is compared before and after accounting for transition processes using survival analysis.

Original languageEnglish (US)
Title of host publication2015 Winter Simulation Conference, WSC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781467397438
StatePublished - Feb 16 2016
EventWinter Simulation Conference, WSC 2015 - Huntington Beach, United States
Duration: Dec 6 2015Dec 9 2015

Publication series

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


OtherWinter Simulation Conference, WSC 2015
Country/TerritoryUnited States
CityHuntington Beach

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications


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