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    •   MOspace Home
    • University of Missouri-Columbia
    • Graduate School - MU Theses and Dissertations (MU)
    • Theses and Dissertations (MU)
    • Dissertations (MU)
    • 2021 Dissertations (MU)
    • 2021 MU Dissertations - Freely available online
    • View Item
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    An evaluation of an Electronic Medical Record (EMR) based system to characterize and correlate physician burnout and EMR use

    Wilkinson, Katie Lynn
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    [PDF] WilkinsonKatieResearch.pdf (2.106Mb)
    Date
    2021
    Format
    Thesis
    Metadata
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    Abstract
    Burnout disproportionately affects healthcare workers and continues to rise, contributing to cost, quality, and patient safety risk in an already overburdened United States healthcare system. While the causes of burnout are complex, evidence suggests that Electronic Medical Record use (EMR) is one major contributor due to the increased clerical burden that decreases patient contact time and disrupts the provider clinical workflow. The challenge of improving the physician EMR experience is exacerbated both by variability across venues and specialty. Targeted training and optimization efforts are generally deployed one-time at a clinic or specialty level but are challenging to deploy longitudinally and in surveillance mode due to the cost and effort of administering traditional survey instruments. To address this challenge, we deployed a single-item burnout measure (SIBM) at the University of Missouri Healthcare, an academic medical center (AMC), to test the feasibility and reliability of capturing longitudinal physician self-reported burnout through the EMR. We further evaluated the utility of the proposed EMR event logging data to discriminate presumed differences in workflow between venues (inpatient, outpatient, and emergency department) and specialty groups (primary care, surgical, non-surgical medical, and emergency) and then correlated the EMR data with the burnout data to demonstrate how this EMR-based longitudinal platform can be used to understand how varying EMR use correlated to burnout.
    URI
    https://hdl.handle.net/10355/93244
    Degree
    Ph. D.
    Thesis Department
    Informatics (MU)
     
    Bioinformatics (MU)
     
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    • Electrical Engineering and Computer Science electronic theses and dissertations (MU)
    • 2021 MU Dissertations - Freely available online

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