A System-Theoretic Method for Modeling, Analysis, and Improvement of Lung Cancer Diagnosis-to-Surgery Process

Hyo Kyung Lee, Feng Ju, Raymond U. Osarogiagbon, Nicholas Faris, Xinhua Yu, Fedoria Rugless, Shan Jiang, Jingshan Li

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Early diagnosis and treatment of lung cancer are of significant importance. In this paper, a system-theoretic method is introduced to analyze the diagnosis-to-treatment process for lung cancer patients who receive surgical resections. The complex care delivery process is decomposed into a collection of serial processes, each consisting of combinations of various tests and procedures. Closed formulas are derived to estimate the mean and coefficient of variation of waiting time during the diagnosis-to-surgery process. Simple indicators based on the data collected on the clinic/hospital floor are derived to identify the bottlenecks, i.e., the waiting times that impede the whole delivery process in the strongest manner. In addition, by approximating waiting times using Gamma distributions, an algorithm is introduced to evaluate the waiting-time performance, i.e., the probability to finish the diagnosis-to-surgery process within a desired or given time interval. Finally, a case study at Baptist Memorial Health System is introduced to illustrate the applicability of the method and provide recommendations for improvement.

Original languageEnglish (US)
JournalIEEE Transactions on Automation Science and Engineering
DOIs
StateAccepted/In press - Jan 20 2017

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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