ResearchWorks Archive
    • Login
    View Item 
    •   ResearchWorks Home
    • Dissertations and Theses
    • Industrial engineering
    • View Item
    •   ResearchWorks Home
    • Dissertations and Theses
    • Industrial engineering
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Systems Modeling of Lung Cancer Screening Programs to Improve Quality

    Thumbnail
    View/Open
    Nandakumar_washington_0250O_16428.pdf (2.442Mb)
    Author
    Nandakumar, Archana
    Metadata
    Show full item record
    Abstract
    The main aim of this thesis is to study the factors that affect the quality of lung cancer screening with special focus on community based lung cancer screening programs. The variation in false positives and other outcomes found across screening centers and across different healthcare elements within a screening center motivates the need to study this problem. Conceptual modeling and simulation modeling are the systems modeling tools employed to study this problem. This conceptual modeling portion of the thesis, deduces some qualitative insights on the importance of the role of lung cancer screening program coordinators and database management systems used in screening programs. The simulation modeling portion of the thesis utilizes a Monte Carlo simulation extended from the conceptual model. The scope of the model was restricted to the factors of importance identified by an advisory board from participating institutions. Analysis of the model develops quantitative insights on the impact of these identified factors and processes on the overall quality outcomes of the screening program as indicated by the false positive rate, early detection rate, radiation induced harms and quit rates in the smoking cessation program. In addition to the typical factors such as nodule detection sensitivity and nodule length variation, the simulation model observes the effect of recall bias in smoking history and shared decision making visits on the quality outcomes of lung cancer screening. It is concluded that, following a nodule management system like LUNGRADS can help achieve the best balance of the quality outcomes, establishing peer evaluation committees that reduce the variation in nodule length could significantly improve quality and that there should be increased focus on helping candidates quit smoking earlier on in the screening process. Though recall bias in smoking history affects false positive rate in a statistically significant way, the effect on the process is quantitatively small when compared to other factors like nodule detection sensitivity and nodule length variation.
    URI
    http://hdl.handle.net/1773/37157
    Collections
    • Industrial engineering [60]

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV
     

     

    Browse

    All of ResearchWorksCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV