Evaluating the dynamic behavior of information technology systems in healthcare using markov simulation

Olufemi A. Omitaomu, Mohammed Olama, Ozgur Ozmen, Laura L. Pullum, Teja Kuruganti, Hilda B. Klasky, Merry Ward, Angela Laurio, Jean M. Scott, Jonathan Nebeker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In recent years, the safety and reliability of information technology (IT) systems in the healthcare industry are of increasing importance. In this paper, we propose an approach for monitoring and predicting reliability degradation in Health IT (HIT) using Markov chain (MC). A MC model provides an opportunity to represent highly dynamic systems, such as HIT, in a succinct manner to simulate the evolution of the system over time in discrete time steps. The model can also represent system behavior that varies over a long duration. Consequently, using electronic health records (EHR) data from systems such as the Veterans Affairs’ Corporate Data Warehouse systems, we defined clinical workflow as a Transaction Process Model (TPM). The TPM represents a set of states in the Consult workflow. It is also an ideal workflow description and has several degrees of freedom. The TPM is then converted into a MC representation and the EHR data is used to compute transition probabilities between the nodes in the MC. The original MC representation is perturbed by changing the transition probabilities to simulate alternative system workflow paths and identifying scenarios that could impact system reliability. We present scenarios that illustrate the proposed approach and discuss some of the insights from the results.

Original languageEnglish
Title of host publicationIISE Annual Conference and Expo 2019
PublisherInstitute of Industrial and Systems Engineers, IISE
ISBN (Electronic)9781713814092
StatePublished - 2019
Event2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019 - Orlando, United States
Duration: May 18 2019May 21 2019

Publication series

NameIISE Annual Conference and Expo 2019

Conference

Conference2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019
Country/TerritoryUnited States
CityOrlando
Period05/18/1905/21/19

Funding

The first author thank Yunhe Feng for his assistance with some of the figures. This work is sponsored by the US Department of Veterans Affairs. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the

Keywords

  • Markov chain
  • Perturbation algorithm
  • Process improvement
  • Process monitoring
  • System reliability

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