This project was aimed at defining, quantifying and analyzing the value of uncompensated care provided by physicians as part of the Yale Medical Group for the 2008 fiscal year. Using an opportunity cost model, uncompensated care was calculated for each department as a total of bad debt and free care and then compared to existing estimates of such care. Another aim of this study was to conduct an interdepartmental comparison of the value of such care as a percentage of departmental earnings. To undertake this study, a literature search was performed to determine previous estimates and models of uncompensated care by physicians. Primary financial data (including charges, payments and write-offs for Bad Debt and Free Care) from the Yale Medical Group for fiscal year 2008 was then collected, fed into the opportunity cost model and compared to published estimates. The results of this study showed that, as a whole, physicians at the Yale Medical Group provided $6,510,373.65 of Uncompensated Care (or 2.75% of Total Payments) with a departmental range of 0.57%-15.29% of Total payments. These results show that Faculty physicians at Yale provided a larger amount of Uncompensated care than the published estimates obtained from random sampling of almost 4000 physicians. The results also reveal large differences in levels of uncompensated care between departments at Yale.

Thesis (D.P.H.)--University of Michigan.

Dissertation (D.P.H.)--University of Michigan.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (leaves 86-95).

Thesis (Ph.D.)--Virginia Commonwealth University, 2010. / Prepared for: Dept. of Health Administration. Title from title-page of electronic thesis. Bibliography: leaves 133-143.

The value-based purchase requirement of the Patient Protection and Affordable Care Act puts pressure on hospital leaders to control cost while improving quality of care. The resource dependency theory was the theoretical framework for this correlational study. Archival data from the Centers for Medicare and Medicaid Services collected from 166 acute care urban hospitals for the Fiscal Year 2016. Multiple linear regression analysis was used to determine the relationship between nursing salaries per patient day, cost of uncompensated care as a percentage of net patient revenue, percentage of net income from patient services, and overall patient satisfaction for quality of care received. The multiple regression analysis results indicated the model as a whole to significantly predict overall patient satisfaction for quality of care for the Fiscal Year 2016, F (3,162) = 13.788, p = .000, and R2 = .203. In the final model, all 3 independent variables significantly predicted overall patient satisfaction for quality of care. Nursing salaries per patient day and percentage of net income from patient services were significant positive predictors of overall patient satisfaction for quality of care. Nursing salaries per patient day (� = .366, t = 5.120, p = .000) accounted for a higher contribution to the model than percentage of net income from patient services (� = .169, t = 2.374, p = .019). The cost of uncompensated care as a percentage of net patient revenue displayed a significant negative relationship with overall patient satisfaction for quality of care (� = .176, t = €2.458, p = .015). The implications of this study for positive social change include the potential to enhance the quality of care for patients while maintaining local hospitals' financial viability.

This dissertation project examines the effect of various state regulations such as Certificate-of-Need (CON) regulation, uncompensated care pools and community benefit requirement laws on hospital provision of uncompensated care and analyzes both for-profit and non-profit hospitals¡¯ responsiveness to the regulatory environment. The analysis of these regulations uses panel data econometric methods for a sample of hospitals in 17 states from 2002 to 2004. This study overcomes the limits of previous research that focused primarily on the effect of a single regulation in a given state. It uses three estimation methods: pooled Ordinary Least Squares (pooled OLS), random effects generalized least squares (GLS) and Hausman Taylor instrumental variable (HTIV) to obtain the parameter estimates. Weighing the advantages and disadvantages of each method, we interpret results based on the cross-validation of the GLS and HTIV estimates. Findings suggest that nonprofit and for-profit hospitals respond to some policy instruments similarly and others differently. For example, both nonprofit and for-profit hospitals respond to CON laws by increasing their uncompensated care provision. However, they respond to policy incentives such as community benefit requirement laws differently. Furthermore, regulatory interactions are found to significantly influence the uncompensated care provision by both nonprofit and for-profit hospitals. The dissertation helps policy makers formulate strategies to create incentives to enhance access to care for the economically disadvantaged. For example, implementing CON and providing public subsidies at the same time may offer better access to care for the uninsured than implementing either regulation alone. However, community benefit requirement laws do not appear to expand the amount of uncompensated care provided by nonprofit hospitals.

Source: Masters Abstracts International, Volume: 46-05, page: 2668. Adviser: Stephanie L. McFall. Includes bibliographical references.

Source: Masters Abstracts International, Volume: 46-01, page: 0311. Adviser: Carl Hacker. Includes bibliographical references.

This dissertation project examines the effect of various state regulations such as Certificate-of-Need (CON) regulation, uncompensated care pools and community benefit requirement laws on hospital provision of uncompensated care and analyzes both for-profit and non-profit hospitals' responsiveness to the regulatory environment. The analysis of these regulations uses panel data econometric methods for a sample of hospitals in 17 states from 2002 to 2004. This study overcomes the limits of previous research that focused primarily on the effect of a single regulation in a given state. It uses three estimation methods: pooled Ordinary Least Squares (pooled OLS), random effects generalized least squares (GLS) and Hausman Taylor instrumental variable (HTIV) to obtain the parameter estimates. Weighing the advantages and disadvantages of each method, we interpret results based on the cross-validation of the GLS and HTIV estimates. Findings suggest that nonprofit and for-profit hospitals respond to some policy instruments similarly and others differently. For example, both nonprofit and for-profit hospitals respond to CON laws by increasing their uncompensated care provision. However, they respond to policy incentives such as community benefit requirement laws differently. Furthermore, regulatory interactions are found to significantly influence the uncompensated care provision by both nonprofit and for-profit hospitals. The dissertation helps policy makers formulate strategies to create incentives to enhance access to care for the economically disadvantaged. For example, implementing CON and providing public subsidies at the same time may offer better access to care for the uninsured than implementing either regulation alone. However, community benefit requirement laws do not appear to expand the amount of uncompensated care provided by nonprofit hospitals.