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    The Relationship of Nurse Staffing in Acute Care Hospitals on 30-Day Readmissions in an Era of Pay for Performance

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    Issue Date
    2017-12-31
    Author
    Boos, Ginny
    Publisher
    University of Kansas
    Format
    176 pages
    Type
    Dissertation
    Degree Level
    Ph.D.
    Discipline
    Nursing
    Rights
    Copyright held by the author.
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    Abstract
    Provisions of the 2010 Affordable Care Act have placed hospitals in the center of financial accountability for reducing readmissions on key conditions and have heightened interest in identifying system-level interventions for improvement. Nurses are the frontline staff for providing many of the core care processes aimed at preventing readmissions. Hospital nurse staffing levels are an important work environment issue for nurses and understood to be a determinant of the quality of nursing care and patient outcomes. Budget costs associated with nurse staffing levels combined with movement from fee-for-service to payment on outcomes have added to the complex financial and practice environment. Mounting evidence links nurse staffing to patient outcomes, which are now associated with penalties under the Affordable Care Act pay-for-performance programs. The purpose of this descriptive correlational study was to determine the effects of acute care nurse staffing on readmissions within 30 days of hospital discharge among patients diagnosed with pneumonia, acute myocardial infarction, heart failure, chronic obstructive pulmonary disease, and elective total hip and knee arthroplasty during their index hospitalization. The Quality Health Outcomes Model provided the theoretical foundation. Vizient data from calendar year 2016 includes de-identified hospital-level and unit-level measures as well as patient-level discharge abstracts. The study included a cross-sectional sample of 42,876 patient discharge encounters from 30 nonprofit academic medical centers and integrated hospital systems across the U.S. that are participating members of Vizient (a voluntary alliance and network). There were three general phases of substantive analysis: a descriptive (univariate) analysis of each variable in the data set, a bivariate analysis to examine how the patient and hospital characteristics relate to readmissions, and a multilevel logistic regression analysis to test the research hypothesis that adult patients discharged from acute care hospitals with higher nurse staffing levels are less likely to have a readmission within 30 days, controlling for hospital characteristics and patient characteristics. Study findings showed that acute care hospital nurse staffing levels were associated with patient readmissions. Although hospitals with higher nursing hours per patient day (NHPPD) levels had lower readmissions within seven days of index discharge, higher nurse staffing levels were associated with greater odds for readmissions within 30 days when controlling for patient and hospital characteristics. These findings are paradoxical and suggest that there are multiple complex interrelationships interacting simultaneously that affect hospital readmissions. Staffing adequacy is essential for high quality patient care. Hospital reporting of productive, direct-care hours that are standardized with delineation between non-licensed and licensed staffing should be encouraged for consistent measurement comparison. Future studies are needed to expand knowledge on the relationship of nurse staffing levels on patient readmissions to inform nursing practice, health care organizations, and research because of the potential benefit to patient outcomes and inform financial decisions.
    URI
    http://hdl.handle.net/1808/27025
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    • KU Med Center Dissertations and Theses [464]
    • Dissertations [4473]

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    785-864-8983
    KU Libraries
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    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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