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    • University of Missouri-Columbia
    • Graduate School - MU Theses and Dissertations (MU)
    • Theses and Dissertations (MU)
    • Dissertations (MU)
    • 2010 Dissertations (MU)
    • 2010 MU dissertations - Freely available online
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    Developing a model of psychiatric visit non-adherence

    Alafaireet, Patricia E.
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    [PDF] short.pdf (9.615Kb)
    [PDF] research.pdf (3.603Mb)
    Date
    2010
    Format
    Thesis
    Metadata
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    Abstract
    Non-adherence to psychiatry visits costs the US mental health care system more than one hundred billion dollars annually. Non-adherent visits undermine improvements to patient care quality, erode patient well-being, and prevent the effective use of technology driven improvements to health care quality. Psychiatric visit non-attendance is often perceived as an intractable problem, because of the direction taken in previous studies of the problem. Previous research into the issue of visit non-adherence focus either on specific patient demographics or on redundant scheduling methods, neither of which addresses quality of care issues or the development of useful tools to decrease visit non-adherence. This formative study addressed the issue of visit non-adherence by leveraging readily available electronic billing and scheduling system data, as well as data from an EMR, to identify and analyze a set of determinants of visit non-adherence. Three strategies, statistical analysis, machine learning/data mining and model comparison, were utilized in the analysis. Results from this multi-phase study provide a parsimonious set of visit non-adherence determinants and a useful model based on those determinants capable of supporting the development of predictive tools suitable for use in ambulatory health care services delivery.
    URI
    https://hdl.handle.net/10355/8335
    https://doi.org/10.32469/10355/8335
    Degree
    Ph. D.
    Thesis Department
    Health informatics program (MU)
    Rights
    OpenAccess.
    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
    Collections
    • Health Management and Informatics electronic theses and dissertations (MU)
    • 2010 MU dissertations - Freely available online
    • Health Informatics Program electronic theses and dissertations (MU)

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