Purpose: The purpose of this study was to determine the influence of out-of-pocket prescription and healthcare costs on adherence to guideline recommended statins, angiotensin converting enzyme (ACE) inhibitors/angiotensin receptor blockers (ARB), and beta-blockers (BB) used for secondary prevention of coronary heart disease and the associations of adherence with cardiovascular mortality in community-dwelling Medicare beneficiaries ≥ 65 years. Methods: Data from the 2004, 2005, and 2006 Medicare Current Beneficiary Survey (MCBS) was utilized to conduct a retrospective, cross-sectional (i.e., multiple cohort) study. Dependent variables of interest included adherence to statins, ACE/ARBs or BBs, and all-cause mortality, with out-of-pocket (OOP) costs, and adherence to these medications the primary independent variables of interest in these models. Adherence was analyzed as a binary variable with ≥ 80 percent annual adherence the threshold utilized in primary analyses. Total OOP prescription costs for all medications and total OOP healthcare costs borne by the beneficiary were reported. Complex survey design-specified logistic regression with sampling weights was the main statistical analysis used. Sensitivity analyses on adherence thresholds and subgroups were additionally conducted. Results: A significant positive relationship between total OOP prescription costs and statin adherence was identified across observation years in the primary models. Similar relationships were noted for ACE/ARBs and BB in 2004, and ACE/ARBs in 2005. No significant association between adherence and total OOP healthcare costs was indicated in the primary models. Mortality could not be used as a clinical outcome of interest due to limitations with the data. Thus, acute coronary syndrome (ACS) events were used as the clinical outcome. At the ≥ 80 percent threshold, no significant reductions in ACS events were reported. However, various sensitivity analyses did suggest significant reductions in ACS events with ACE/ARBs. Additionally, significantly higher risk of ACS was noted when BB adherence thresholds were reduced to ≥ 60 percent. Conclusions: OOP prescription costs are a significant factor influencing adherence to these medications used for secondary prevention of CAD/MI in Medicare beneficiaries. Continuing to monitor how these costs impact adherence and ultimately outcomes will be critical, particularly given policy changes such as Medicare Part-D.

Thesis advisor: Mathis Wagner / The essays that comprise my dissertation analyze the interactions among old age labor supply, health, and Social Security system in the United States. In the first chapter of my dissertation, I provide estimate of the causal effect of Social Security Disability Insurance (SSDI) application on employment of denied applicants. Using exogenous variations of SSDI application decision, I find that the employment rate is 36 percentage points lower for the denied applicants than that of comparable non-applicants in the short-run. In the second chapter (with Matthew Rutledge and April Wu) we explore the relationship between individuals’ expectation on longevity and their plans for retirement in a quasi-experimental setting. The estimates in this paper suggest a large and statistically significant relationship between subjective life expectancy and retirement expectations: an individual who is one standard deviation more optimistic about living to age 75 has a greater probability of planning to work fulltime at 62 and 65 by 10 percent and 21 percent, respectively. In the third chapter of my dissertation (with Norma Coe and Matthew Rutledge) we identify the contribution of Medicare in explaining the retirement behavior of workers. We find individuals without access to retiree health insurance from work are 7.5 percentage points more likely to retire soon after their 65th birthdays and are 5.8 percentage points less likely to delay retirement until the Full Retirement Age (FRA) than those with that insurance. We interpret this finding as evidence that Medicare eligibility persuades more people to retire, because they can begin receiving federal health coverage. The findings of the research in my dissertation provide important insights in making the Social Security system more welfare enhancing for the older workers and the disabled as well as keeping it sustainable in the long-run. / Thesis (PhD) — Boston College, 2017. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

The first chapter investigates whether East German women became used to the requirement of working full-time under communism and thereby continued to work much longer hours than did their counterparts in the West after unification. The second chapter develops a rational habit formation model in labor supply using the idea of habits outlined in the first chapter. I show that the proposed model avoids the extreme behavior observed in the standard model in the literature where in the long-run hours of work could increase indefinitely or decrease to zero over time. The third chapter examines whether disabled elders who have private long-term care insurance consume fewer acute or post-acute Medicare covered services. / Thesis (PhD) — Boston College, 2004. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

For much of the early 1960s, House Ways and Means chairman Wilbur Mills represented the “One-Man Veto” on Medicare before eventually offering his reluctant support to the measure in 1964 and 1965. Ironically, this longtime opponent would be the one to suggest an expansion in the scope of the bill. Early proposals for Medicare only offered to cover hospital costs; Mills would call for physician costs to be covered, as well. The aim of this thesis is to show how Mills’s expansion of Medicare benefits in 1965 caused health care costs to skyrocket in the late 1960s, causing the fiscally conservative Mills to co-sponsor legislation for a single-payer national health insurance program along with Senator Edward Kennedy almost a decade later.

In 2011, Medicare patients represented the largest share of total readmissions and health costs when compared to all other patient categories. Because patient-centered care drives the use of health services, the U.S. Patient Protection and Affordable Care Act outlined improving the patient experience to reduce readmission rates; however, the relationship between patient experience and readmissions is not well understood. Grounded in systems theory, the purpose of this correlational study was to determine if the relationship between patient experience and readmission rates in Medicare Shared Savings Program accountable care organizations. Data from the Consumer Assessment of Healthcare Providers and Systems survey were gathered from the Centers for Medicare and Medicaid datasets to analyze patient experience measurements and readmission rates, while accounting for variation among Medicare service regions, number of assigned beneficiaries, and performance year. Using multiple linear regression to analyze the data, the model was used to predict Medicare's all-condition readmission rate (per 1000), R-²= .242, F (13, 634) 15.59, p < .001. The research question was answered partially; variation in the patient experience domain did not support all hypotheses. Because the Medicare population represents the fastest growing patient population within the U.S. health care system, continuous evaluation of policy and performance provides an evidence-based analysis to health administrators and providers who have pivotal roles in the creation of positive social change. Findings may be used to improve quality and service while reducing costs, which contributes to the sustainability of the U.S. Medicare program and its beneficiary population.

The United States (U.S.) healthcare system produces an enormous volume of data with a vast number of financial transactions generated by physicians administering healthcare services. This makes healthcare fraud difficult to detect, especially when there are considerably less fraudulent transactions than non-fraudulent. Fraud is an extremely important issue for healthcare, as fraudulent activities within the U.S. healthcare system contribute to significant financial losses. In the U.S., the elderly population continues to rise, increasing the need for programs, such as Medicare, to help with associated medical expenses. Unfortunately, due to healthcare fraud, these programs are being adversely affected, draining resources and reducing the quality and accessibility of necessary healthcare services. In response, advanced data analytics have recently been explored to detect possible fraudulent activities. The Centers for Medicare and Medicaid Services (CMS) released several ‘Big Data’ Medicare claims datasets for different parts of their Medicare program to help facilitate this effort. In this dissertation, we employ three CMS Medicare Big Data datasets to evaluate the fraud detection performance available using advanced data analytics techniques, specifically machine learning. We use two distinct approaches, designated as anomaly detection and traditional fraud detection, where each have very distinct data processing and feature engineering. Anomaly detection experiments classify by provider specialty, determining whether outlier physicians within the same specialty signal fraudulent behavior. Traditional fraud detection refers to the experiments directly classifying physicians as fraudulent or non-fraudulent, leveraging machine learning algorithms to discriminate between classes. We present our novel data engineering approaches for both anomaly detection and traditional fraud detection including data processing, fraud mapping, and the creation of a combined dataset consisting of all three Medicare parts. We incorporate the List of Excluded Individuals and Entities database to identify real world fraudulent physicians for model evaluation. Regarding features, the final datasets for anomaly detection contain only claim counts for every procedure a physician submits while traditional fraud detection incorporates aggregated counts and payment information, specialty, and gender. Additionally, we compare cross-validation to the real world application of building a model on a training dataset and evaluating on a separate test dataset for severe class imbalance and rarity. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Failure to collect reimbursement because of changing regulations negatively impacts hospital profitability. A multiple case study approach was used to explore the successful strategies billing managers employed to collect reimbursement for all legitimate Medicare claims. The target population for this study included 5 hospital billing managers from 3 organizations in the Northern New Jersey region. The complexity theory was used as a framework for assessing changing Medicare regulations and how the managers adapted to them. The data collection process for this study involved gathering data from participant interviews, documentation from the organizations of the participants, and government documented regulations and manuals. The logical and sequential order of data analysis for this study embraced Yin's 5-steps data analysis that includes compiling data, disassembling data, reassembling data, interpreting the data, and concluding. The successful strategies billing managers used that emerged as themes were remaining up to date with Medicare changing compliance regulations; enhancing communication with staff, multiple departments, and Medicare; and adopting a robust billing system and other systems that compliment billing. The implications of this study for social change include the potential to ensure access to patient care for benefiting families and communities through the sharing of successful strategies for Medicare claims.

Medicare is vital to the health and well-being of many American seniors. However, due to its complexity, beneficiaries often need assistance navigating the federal health insurance system. GeorgiaCares, Georgia’s State Health Insurance Assistance Program (SHIP), provides free and unbiased Medicare information and counseling. The aims of this thesis were to evaluate GeorgiaCares outreach events to discern the social and demographic characteristics of participants and decipher how to best market the events. Participants of nine GeorgiaCares outreach events (n=81) completed anonymous surveys; mixed-methods data analysis revealed the typical participant to be a 71-year-old African American female. Findings suggest an effective way to assist beneficiaries in Medicare-related decisions is through the formation of community partnerships. Suggestions to market outreach events include partnering with churches and grocery stores to disseminate information and enlisting the support of community leaders to overcome barriers of distrust.

To study the decision-making model behind how physicians making prescribing decisions, we studied the effects of the introduction of Medicare Part D in 2006 on numbers and characteristics of medications prescribed by physicians. We identified a significant increase in overall number of medications prescribed due to Medicare Part D but did not find any effects on the number of antibiotics. The result suggests there exist factors distinguishing antibiotics from other medications that led to a change in incentives to prescribe antibiotics, such as costs of antibiotics resistances. . We also identified the heterogeneity responses to Medicare Part D with respect to physician’s employment status, primary care relationship and patient’s gender and diagnostic categories.

The purpose of this study was to investigate the impact of Medicare Part D on prescription utilization, health services utilization, and health care expenditures in the general Medicare population – as well as Medicare sub-populations, including non-Hispanic blacks (NHBs), Hispanics, near poor individuals, and persons with higher disease burden. A retrospective analysis of Medicare beneficiaries (N=32,228) was conducted using the Medical Expenditure Panel Survey 2002 to 2009 data. Multivariable quantile regression was used to estimate the following outcomes, adjusting for socio-demographic characteristics: 1) number of prescription fills; 2) out-of-pocket (OOP) drug expenditures; 3) total drug expenditures; 4) OOP health care expenditures; 5) total health care expenditures; 6) number of hospitalizations; and 7) number of emergency department (ED) visits between the pre-Part D (2002-2005) and post-Part D (2006-2009) periods. All expenditures were inflation-adjusted to 2009 dollars. The average age of the study sample was 71.0 (SD=14.5). In the general Medicare population, Part D was associated with decreases in OOP drug expenditures (-25.7% to -33.6%; p<0.0001) and OOP health care expenditures (-22.1% to -24.3%; p<0.0001) as well as increases in the number of prescription fills (5.8% to 8.4%; p<0.0001) and total drug expenditures (75th percentile: 5.5%; 90th percentile: 10.2%; p<0.0001). Part D was not associated with changes in total health care expenditures in the general Medicare population. Changes in hospitalizations and ED visits were tested at the 90th percentile, and the results were not statistically significant. In sub-group analyses based on race/ethnicity, non-Hispanic whites (NHWs) experienced more significant reductions in OOP drug and/or health care expenditures when compared with NHBs and Hispanics. Near poor beneficiaries experienced larger reductions in OOP drug expenditures than beneficiaries with middle- to high-income, while Medicare beneficiaries with three or more conditions experienced more substantial reductions in OOP drug and OOP health expenditures after Part D was introduced, compared with those with fewer than three conditions. Part D resulted in increases in medication utilization and reductions in OOP drug and OOP health care expenditures among Medicare beneficiaries. Part D was not associated with differences in total health care spending. The effects of Part D were more pronounced in Medicare subgroups, including NHWs, near poor individuals, and patients with higher chronic disease burden. / text