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 journalArticlepeer-review

10 Citations (Scopus)


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
Pages (from-to)531-544
Number of pages14
JournalIEEE Transactions on Automation Science and Engineering
Issue number2
Publication statusPublished - 2018 Apr
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 IEEE.


  • Bottleneck
  • coefficient of variation (CV)
  • diagnose-to-surgery process
  • lung cancer
  • mean waiting time
  • waiting-time performance (WTP)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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