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Browsing Theses and Dissertations by Subject "ACA"

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    Predictability of inpatient satisfaction scores based on hospital characteristics: quantitative analysis of HCAHPS survey data, 7/1/2013 through 6/30/2014
    (Colorado State University. Libraries, 2017) O'Barr, Gregory W., author; Makela, Carole, advisor; Holmquist-Johnson, Helen, committee member; Mallette, Dawn, committee member; Venneberg, Donald, committee member
    In the early 21st century, the U.S. healthcare industry is undergoing a myriad of changes that include a focus on reimbursements to hospitals from the Centers for Medicare and Medicaid Services (CMS) based on the perceptions of patients' satisfaction of their care. This study utilizes the survey results as administered through the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS©) survey along with nine hospital characteristics to determine predictive analysis of the scores based on the independent variables. The quantitative analysis utilized multiple regression to determine statistical significance of the variables and determine if the variables can predict the satisfaction scores. The hospital characteristics chosen include Academic, Baldrige Award, Faith Based, For Profit, MAGNETTM, Most WiredTM, Safety Net, Sole Provider, and System. The survey data were obtained through CMS's public domain and then filtered for acute care, non-specialty hospitals. With a total list of 3,100 hospitals, each hospital was coded to the unique characteristics. Once coding was completed, the full dataset was divided into combinations of the variables and data consisting of "All Variables", "Application Variables", "Non-Application Variables", "Low Response Rate on Survey", "Medium Response Rate on Survey", "High Response Rate on Survey", and grouping of hospitals defined by CMS's ten geographical regions. Through these multiple analysis of the data, the researcher was able to search for themes on the highest Adjusted R2 to show the predictive power with the intent of identifying a common culture through a high-level characteristic that would be the driver of patient satisfaction. The findings showed significance in the data, but lower than expected predictability based on the hospital characteristics. The highest predictive variables were from three CMS geographic regions with only one specific survey question, Willingness to Recommend Hospital (all variables). This was an unexpected finding and outside the literature reviewed. It focuses the question on the drivers of patient satisfaction as not associated with the hospital characteristics utilized in this study, but possibly with cultural and demographic issues that could contribute to future work.