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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
31

Patient-centric care in the U.S. - A comparative study of patient satisfaction and quality care among for-profit physician-owned, corporate-owned, and not-for-profit hospitals

Sharma, Arun 12 October 2018 (has links)
This dissertation examines the effects of physician ownership of hospitals on the quality of patient-centric care in the U.S. The health care sector in the U.S. is becoming more aligned with markets and in turn, with consumers’ preferences. In consumer driven service industries, consumer satisfaction is considered a key criterion to judge quality. In the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) patient satisfaction surveys, physician-owned hospitals (POHs) get more top 5-Star ratings than other hospitals. However, it is not known whether higher perceived patient satisfaction is because of better inpatient experience or due to better health related outcomes. Ratings also do not clarify variations between specialty and general service POHs. The study compares the quality of care in POHs with that in other major forms of hospitals (corporate-owned, and not-for-profit). The Affordable Care Act (ACA) regulated physician ownership of hospitals due to concerns that physicians’ profit motive might negatively affect the quality of care. This non-experimental study used bivariate and multivariate analyses to examine variation in the quality of care among types of hospitals in 2017 and 2018 using patient satisfaction and clinical outcomes as indicators of quality. This study used two samples, a full and a restricted sample. Full sample compared all POHs (specialty and general service) with other hospitals. Restricted sample included only general service hospitals. Patients in POHs were found to have higher perceived satisfaction, and viewed providers’ practices more favorably in the full sample. In the restricted sample, however, not-for-profit (NFP) hospitals provided relatively better care. Corporate-owned hospitals had lowest patient satisfaction and poorest outcomes. Results indicate POHs are competitive with not-for-profit hospitals on patient satisfaction dimension of quality care. Multivariate analyses suggest that the effects of physician ownership go away when mediation by providers’ practices is considered. NFP hospitals, however, continue to provide better overall value of care. The results do not support reconsideration of the ACA restrictions on POHs. Patient satisfaction may be contingent upon patient-centric practices than type of hospital, but hospital ownership may affect preference for some practices over others. Outcomes may not matter when patients’ perceptions measure quality. / Ph. D. / The health care sector is becoming more closely linked to markets, and consumer experience and satisfaction, like any other consumer services industry due to growing influence of for-profit hospitals and hospital forms. Physician-owned hospitals are a relatively new form of hospitals in the U.S. Along with more traditional not-for-profit and corporate-owned hospitals; physician-owned hospitals compete for patients and patient dollars. Many physician-owned hospitals are specialty and surgical hospitals, in addition to general service hospitals. According to federal government surveys, patients usually perceive medical care provided by physician-owned hospitals to be of superior quality to that of other kinds of hospital. However, physician-owned hospitals are a type of for-profit hospital, and it is not clearly known if general service physician owned hospitals provide similar care as specialty hospitals. This research compared possible quality differences between specialty and general service physician-owned hospitals as well as with corporate-owned and not-for-profit hospitals. The results indicate that patients’ perceptions of quality of care are not consistent for physician-owned specialty and general service hospitals; the higher patient perception ratings for physician-owned hospitals reflect the better performance of specialty hospitals. In comparison with other hospitals, not-for-profit hospitals seem to provide better quality of care (tapped by both patient satisfaction and clinical outcomes) than for-profit hospitals. Corporate-owned hospitals were found to have lowest quality of care. Patients should consider tradeoffs between having better inpatient experiences and better outcomes of care.
32

Statistical and Machine Learning for assessment of Traumatic Brain Injury Severity and Patient Outcomes

Rahman, Md Abdur January 2021 (has links)
Traumatic brain injury (TBI) is a leading cause of death in all age groups, causing society to be concerned. However, TBI diagnostics and patient outcomes prediction are still lacking in medical science. In this thesis, I used a subset of TBIcare data from Turku University Hospital in Finland to classify the severity, patient outcomes, and CT (computerized tomography) as positive/negative. The dataset was derived from the comprehensive metabolic profiling of serum samples from TBI patients. The study included 96 TBI patients who were diagnosed as 7 severe (sTBI=7), 10 moderate (moTBI=10), and 79 mild (mTBI=79). Among them, there were 85 good recoveries (Good_Recovery=85) and 11 bad recoveries (Bad_Recovery=11), as well as 49 CT positive (CT. Positive=49) and 47 CT negative (CT. Negative=47). There was a total of 455 metabolites (features), excluding three response variables. Feature selection techniques were applied to retain the most important features while discarding the rest. Subsequently, four classifications were used for classification: Ridge regression, Lasso regression, Neural network, and Deep learning. Ridge regression yielded the best results for binary classifications such as patient outcomes and CT positive/negative. The accuracy of CT positive/negative was 74% (AUC of 0.74), while the accuracy of patient outcomes was 91% (AUC of 0.91). For severity classification (multi-class classification), neural networks performed well, with a total accuracy of 90%. Despite the limited number of data points, the overall result was satisfactory.
33

Empathy in Medicine: What is the Lived Experience of Teaching Empathy in Medical Education?

McCarthy Noviski, Krista Lynne January 2020 (has links)
No description available.

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