Using a Virtual Hospital for Piloting Patient Flow Decongestion Interventions

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

Abstract

It is beyond the capacity of the human mind to process large amounts of interdependent information, such as predicting the dynamic behavior of a complex system and evaluating the short and long term effects of potential interventions aimed to improve its operations. At the same time, it is extremely costly to test these interventions with the real world system subject to improvement. Fortunately, we have moved to an era where advancements in computing and software technology have provided us the capabilities to build virtual complex systems (simulation models), that can serve as risk-free digital platforms for running pilot experiments with potential system interventions and obtain comparative data for decision support and optimization. This paper presents two case studies in a healthcare setting, where a simulation model named HESMAD (Hospital Event Simulation Model: Arrivals to Discharge) was applied to pilot potential interventions proposed by hospital professionals or researchers that are aimed at minimizing hospital patient flow congestion episodes. It was demonstrated that simulation modelling is not only an effective approach to conduct virtual experiments for evaluating proposed intervention ideas from healthcare professionals, but also an ideal vehicle for piloting scientific research outcomes from data science researchers. Some experience-based discussions on various issues involved in simulation modelling, such as validation of the simulation model and interpretation of simulation results are also provided.

Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings
EditorsJianxin Li, Sen Wang, Shaowen Qin, Xue Li, Shuliang Wang
Place of PublicationCham, Switzerland
PublisherSpringer
Pages605-616
Number of pages12
ISBN (Electronic)9783030352318
ISBN (Print)9783030352301
DOIs
Publication statusPublished - 2019
Event15th International Conference on Advanced Data Mining and Applications, ADMA 2019 - Dalian, China
Duration: 21 Nov 201923 Nov 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11888 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Advanced Data Mining and Applications, ADMA 2019
CountryChina
CityDalian
Period21/11/1923/11/19

Keywords

  • Decision support
  • Optimization
  • Patient flow
  • Pilot study
  • Simulation modelling
  • Virtual experiments

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  • Cite this

    Qin, S. (2019). Using a Virtual Hospital for Piloting Patient Flow Decongestion Interventions. In J. Li, S. Wang, S. Qin, X. Li, & S. Wang (Eds.), Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings (pp. 605-616). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11888 LNAI). Springer. https://doi.org/10.1007/978-3-030-35231-8_44