"The purpose of this study is to examine the impact of the medicare law on a particular hospital: Flow Memorial Hospital, Denton, Texas. The scope of this study is limited to an analysis of changes in hospital car at Flow Memorial Hospital resulting from medicare. These changes are examined on the basis of 1. number of patients and days of care; 2. hospital services by department; 3. the means of payment; and 4. social characteristics of the aged patient group. A detailed examination of aged patient care was made for the fiscal years 1966 and 1967. The 1966 year was the year immediately preceding medicare. The 1967 year was the first year of medicare. Longer time periods were used where the data were available and pertinent."-- leaf 1.

Thesis (M.P.H.)--University of Texas Health Science Center at Houston, School of Public Health, 2007. / Source: Masters Abstracts International, Volume: 46-01, page: 0311. Adviser: Osama Mikhail. Includes bibliographical references.

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This cross-sectional, non-experimental study evaluates associations between cohort membership, type of dental coverage, and utilization of dental services in all patients age 47 and over who received dental care at Virginia Commonwealth University’s (VCU) School of Dentistry in 2011. Structural Lag Theory poses that society’s institutions lag behind the actuality of a healthy and capable older adult population. The two dynamisms of the Structural Lag Theory were used for this study. The Dynamism of Changing Lives is represented by Cohort differences. Cohort differences include cohort size, people living longer and retaining more of their natural teeth along with different attitudes toward dental care. This dynamism impacts the Dynamism of Structural Change, represented by the institutions of dental coverage and utilization of dental services. Cohort membership is an independent variable. The dependent variable, utilization, is defined as Financial-Total amount spent and Procedural-Routine adult dental prophylaxis. Dental coverage, a dichotomous variable, is used as an independent and dependent variable. Descriptive statistics revealed employer provided dental coverage is the most prevalent type of dental coverage. However, when considered a payment source, out of pocket funding is the primary source of payment for dental services. Using Chi-square and logistic regression, examination of Cohorts (1-Greatest Generation, 2-Silent Generation, 3-Baby Boomer Generation) revealed that Cohort 2 had more dental coverage than Cohort 1, and Cohort 3 had more dental coverage than Cohort 2. Using logistic regression, Cohort 2 showed the highest level of Procedural utilization. Evaluating Financial utilization, multiple regression models showed Cohort 1 utilized more than Cohort 2 and Cohort 2 utilized more than Cohort 3. Those with dental coverage spend more on dental services, fees for routine adult dental prophylaxis make up the majority of the total amount spent, and those with dental coverage utilize more dental services when defined as total amount spent. Because they have experienced different social, political, economic, and technological changes at different times in their life course, the receipt of dental services by new cohorts of older people differs from previous ones. Findings from this study confirm that there is a structural lag in Medicare policy and its coverage of dental services.

This dissertation comprises three discrete empirical papers, with an introductory essay that evaluates the impact of different federal policies on prescription drug prices, utilization, and spending. Two main databases are used: (a) Medicaid State Drug Utilization Data and (b) the Medical Expenditure Panel Survey (MEPS) data. These two databases are designed to track Medicaid drug utilization and overall medical use and expenditures, respectively. The variables of interest in this dissertation are prescription drug price, prescription drug use and spending, and overall drug expenditures. The objective of the first paper (Chapter 2) is to examine whether oncology drug prices have significantly changed because the Medicaid rebate increased under the Patient Protection and Affordable Care Act (ACA). The analytic sample includes top-selling oncology drugs, both branded and generic, over an 8-year time period. The prices of top-selling oncology drugs in 2006 were followed through 2013 to find the extent to which drug prices have changed while controlling for state fixed-effect, package size, type of manufacturer, brand or generic, and drug strength. Thus, this study examines whether and to what extent oncology drug prices have changed after the increase in the Medicaid rebate under the ACA. The second paper’s objective (Chapter 3) is to study whether Medicare Part D has reduced racial disparities in diabetes drug use, coverage, and spending since its implementation in 2006. The analytic sample includes individuals aged 55 years and older who had diabetes from 2001 to 2010. Although the impact of Medicare Part D has been studied from different perspectives, its impact on racial disparities in drug use, coverage, and expenditures among diabetics has not been studied yet. The third paper (Chapter 4) focuses on the association between closing the Medicare doughnut hole and prescription drug utilization and spending for Medicare Part D beneficiaries with chronic diseases through 2013. The objective of the third paper is to determine whether the provisions of the ACA that close the coverage gap have affected prescription drug utilization and out-of-pocket (OOP) spending among Medicare seniors with Part D coverage.

Introduction: Atypical Antipsychotics (AAPs) are approved by the Food and Drug Administration (FDA) for the treatment of schizophrenia and bipolar disorder. AAPs are commonly used off-label to treat depression, post-traumatic stress disorder and neuropsychiatric symptoms in dementia due to lack of alternative treatment options and treatment resistance. Concerns for off-label use arise since AAPs increase the risk of cardiovascular events and death. The objectives were 1) describe patterns of RU and costs among off-label AAPs users in a nationally representative population 2) identify prevalence of off-label use in the Medicare population 3) compare RU and costs between off-label AAPs users and non-users with mental health conditions in Medicare. Methods: For the first objective, the Medical Expenditure Panel Survey (MEPS) datasets were used. AAPs users greater than 18 years were identified in this cross-sectional study. Generalized Linear Models (GLM) were used to estimate costs among users and non-users after controlling for age sex, gender, insurance type, marriage status, income and comorbidity index. For the second and third objective, Medicare datasets were used to identify prevalence, RU, and costs of off-label use in Medicare beneficiaries 18 years and older. RU and costs between propensity score matched AAPs user and non-user cohorts were compared in a retrospective cohort study. Results: The adjusted odds of having an office-based outpatient (OR=2.47, 95%CI: 1.55-3.92) or inpatient (OR=1.63, 95%CI: 1.26-2.10) visit were significantly higher among off-label AAPs users. Adjusted office-based visit ($1,943 vs. $1,346), prescription ($4,153 vs. $1,252) and total ($10,694 vs. $4,823) costs were significantly higher among users (p<0.0001). Among Medicare beneficiaries, approximately 37% of AAPs users had no FDA approved diagnosis. The typical off-label user was a white 70-year-old male. Common off-label uses were depression, anxiety and neurotic disorders and dementia. Off-label AAPs users had significantly higher mental health outpatient ($461 vs $297), prescription ($2,349 vs $282) and total ($3,665 vs $1,297) costs per beneficiary than non-users. About 30% of AAPs users had at least one mental health outpatient visit during the year versus 23% of non-users; no significant differences were found in inpatient visits. AAPs non-users had significantly higher all-cause inpatient costs ($6,945 vs. $4,841) per beneficiary (p Conclusion: In a nationally representative population comprising a younger age group AAPs users had higher all-cause RU and total costs than non-users. Off-label prescribing of AAPs continued to be a prevalent practice affecting 37% of Medicare AAPs users. Off-label AAPs users had higher mental health costs but no significant differences in all-cause total health care costs in a Medicare population. Off-label use of AAPs can be a cost-effective option if future research shows off-label use is associated with increased effectiveness, which offsets any additional costs.

The Hospital Value-Based Purchasing Program (HVBP), created by Section 3001 of the Patient Protection and Affordable Care Act passed in 2010, enacted a major industry shift in Medicare towards "pay for performance," or paying for high marks on a variety quality metrics rather than the traditional reliance on volume of care delivered. This study examines one of these quality metrics in particular: patient satisfaction. The trajectory of this paper begins with an overview of the current focus on patient satisfaction as a modern quality metric in American healthcare, contextualizes this emphasis on satisfaction within the intellectual movement of "patient-centered care," and moves on to a review of the relevant scholarship that attempts to explain the numerous determinants of patient satisfaction scores (with special attention to the inpatient hospital setting), as well as the robust academic debate over whether satisfaction is even an appropriate quality metric at all relative to clinical outcomes in care. The second half of my discourse moves on to more practical applications - first I break down the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey and the impact of its methodology on providers, then the Medicare HVBP program itself and its various directions towards the value-based care model. I conclude with a quantitative analysis of trends in patient satisfaction over time between 1) HVBP-participating providers (as of FY2014) and 2) those providers who have not opted in (including those ineligible to do so). My comparison aims to study the strength of the HVBP incentives to improve patient satisfaction in those subject to the financial incentive relative to those who are not. Additionally, I preface this analysis whether patient satisfaction scores are associated with either clinical process of care scores or outcome scores in the HVBP program. My research questions aim to shed light on the academic debate between patient satisfaction and more traditional clinical outcomes - are they related in the context of FY2014 HVBP? Are the new incentives to improve patient satisfaction actually doing so in a meaningful way among providers newly accountable to these incentives? Finally, in a market defined by zero-sum resources, is there evidence that a financial incentives around patient satisfaction are channeling resources and by extension improvement away from clinical outcome performance? I believe this last question is the true concern of patient satisfaction skeptics, and hope to address it with applicable data. By providing a thorough qualitative grounding in the topic followed by current quantitative analysis, my goal is to create an informed perspective on the use of patient satisfaction as a quality metric in U.S. healthcare, which can be applied meaningfully from policy, provider, and consumer vantage points. With patient satisfaction becoming increasingly more internalized in the value-based care model, these analyses of the initial results in HVBP potentially serve as predictive insight into provider behavior in this area moving forward.

In most markets, competition induces efficiency by ensuring that goods are priced according to their marginal cost. This is not the case in health insurance markets. This is due to the fact that the cost of a health insurance policy depends on the characteristics of the consumer purchasing it, and asymmetric information or regulation often precludes an insurer from matching the price an individual pays to her expected cost. This disconnect between cost and price causes inefficiency: When the premiums paid by consumers do not match their expected costs, consumers may sort inefficiently across plans. In this dissertation, I study the effects of policies used to alleviate selection problems. In Chapter 1, I develop a model to study the effects of risk adjustment on equilibrium prices and sorting. I simulate consumer choice and welfare with and without risk adjustment in the context of a Health Insurance Exchange. I find that when there is no risk adjustment, the market I study unravels and everyone enrolls in the less comprehensive plan. However, diagnosis-based risk adjustment causes over 80 percent of market participants to enroll in the more comprehensive plan. In Chapter 2, we study an unintended consequence of risk adjustment: upcoding. When payments are risk adjusted based on potentially manipulable risk scores, insurers have incentives to maximize those risk scores. We study upcoding in the context of Medicare, where private Medicare Advantage plans are paid via risk adjustment but Traditional Medicare is not. We find that when the same individual enrolls in a private plan her risk score is 5% higher than if she would have enrolled in Traditional Medicare. In Chapter 3, we study two forms of insurance for insurers: Reinsurance and risk corridors. Protecting insurers from risk can lower prices and improve competition by inducing entry into risky markets. It can also induce inefficiencies by causing insurers to manage risk less carefully. We use simulations to compare the power of reinsurance and risk corridors to protect insurers against risk while limiting efficiency losses. We find that risk corridors are always able to limit insurer risk with the lowest efficiency cost.