title: Computer modeling of lung cancer diagnosis-to-treatment process.
abstract: We introduce an example of a rigorous, quantitative method for quality improvement in lung cancer care-delivery. Computer process modeling methods are introduced for lung cancer diagnosis, staging and treatment selection process. Two types of process modeling techniques, discrete event simulation (DES) and analytical models, are briefly reviewed. Recent developments in DES are outlined and the necessary data and procedures to develop a DES model for lung cancer diagnosis, leading up to surgical treatment process are summarized. The analytical models include both Markov chain model and closed formulas. The Markov chain models with its application in healthcare are introduced and the approach to derive a lung cancer diagnosis process model is presented. Similarly, the procedure to derive closed formulas evaluating the diagnosis process performance is outlined. Finally, the pros and cons of these methods are discussed.
authors.affiliation: 1 Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI 53706, USA ; 2 Thoracic Oncology Research Group, Baptist Memorial Health System, Memphis, TN, USA ; 3 School of Public Health, University of Memphis, Memphis, TN, USA.
authors.forename: Feng
authors.initials: F
authors.lastname: Ju
authors.affiliation: 1 Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI 53706, USA ; 2 Thoracic Oncology Research Group, Baptist Memorial Health System, Memphis, TN, USA ; 3 School of Public Health, University of Memphis, Memphis, TN, USA.
authors.forename: Hyo Kyung
authors.initials: HK
authors.lastname: Lee
authors.affiliation: 1 Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI 53706, USA ; 2 Thoracic Oncology Research Group, Baptist Memorial Health System, Memphis, TN, USA ; 3 School of Public Health, University of Memphis, Memphis, TN, USA.
authors.forename: Raymond U
authors.initials: RU
authors.lastname: Osarogiagbon
authors.affiliation: 1 Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI 53706, USA ; 2 Thoracic Oncology Research Group, Baptist Memorial Health System, Memphis, TN, USA ; 3 School of Public Health, University of Memphis, Memphis, TN, USA.
authors.forename: Xinhua
authors.initials: X
authors.lastname: Yu
authors.affiliation: 1 Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI 53706, USA ; 2 Thoracic Oncology Research Group, Baptist Memorial Health System, Memphis, TN, USA ; 3 School of Public Health, University of Memphis, Memphis, TN, USA.
authors.forename: Nick
authors.initials: N
authors.lastname: Faris
authors.affiliation: 1 Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI 53706, USA ; 2 Thoracic Oncology Research Group, Baptist Memorial Health System, Memphis, TN, USA ; 3 School of Public Health, University of Memphis, Memphis, TN, USA.
authors.forename: Jingshan
authors.initials: J
authors.lastname: Li
keywords: Lung cancer quality improvement; Markov chain; analytical model; closed formula; discrete event simulation (DES); process modeling