Assessing the Impacts of an Aging Population on Rising Healthcare and Pharmaceutical Expenditures within the United States
By Rahul Sharma
This paper studies the impact of aging on rising healthcare and pharmaceutical expenditures in the United States with the goal of contextualizing the future burden of public health insurance on the government. Precedent literature has focused on international panels of multiple countries and hasn’t identified significant correlation between age and healthcare expenditures. This paper presents a novel approach of identifying this correlation by using a US sample population to determine if age impacts an individual’s consumption of healthcare services and goods. Results suggest that age has a significant impact on healthcare and pharmaceutical expenditures across private and public insurance.
Advisors: Gilliam D. Saunders-Schmidler and Grace Kim | JEL Codes: H51, H53, I12, I13, I18, I38
The Professor and the Coal Miner: The effect of socioeconomic and geographical factors on breast cancer diagnosis and survival outcome
By Shelley Chen
Previous studies reported that patients who live farther from cancer centers do not necessarily experience delayed cancer detection and shortened survival. However, the results are biased because of the incomplete observation of patient survival, which cannot be properly accounted for with the multivariable regression model. In this thesis, I isolated the effect of the breast cancer patient’s distance to a comprehensive cancer center on the stage of diagnosis and survival using the Cox Proportional Hazards model. I linked data from the Kentucky Surveillance, Epidemiology, and End Results 18, the Kentucky Life Tables, and the Kentucky Area Health Resource Files and identified 37654 patients diagnosed with breast cancer. I estimated the effect of distance on marginal probability of cancer mortality, controlling for non-cancer related death, socioeconomic status, and demographic factors in patients. After controlling for covariates, travel distance between the patient and the nearest comprehensive cancer center was statistically significantly on the breast cancer mortality probability, but not on the stage of diagnosis. In the Kentucky population, patients who were located farther from comprehensive cancer centers experience an increased marginal probability of mortality (proportional hazard = 1.004; 95% CI: [1.000502 1.007311]). The linkage of SEER 18 and AHRF data provided more comprehensive information on the socioeconomic risk factors of cancer mortality than past study datasets. For the stage of diagnosis, a low physician to population ratio and high county-level Medicaid coverage were associated with more advanced stages of diagnosis. In turn, a more advanced stage of diagnosis, lower physician to population ratio, and identification as African American increased the marginal probabilities of mortality.
Advisor: Charles Becker, Kent Kimbrough | JEL Codes: I1, I13, I14 | Tagged: B
By Rahul Nayak
This study uses the National Ambulatory Medical Care Survey (2006-2010) and Health Tracking Physician Survey (2008) to study the incentives and characteristics that explain physician generic prescribing habits. The findings can be characterized into four main categories: (1) financial/economic, (2) informational, (3) patient- dependent and (4) drug idiosyncratic effects. Physicians in practices owned by HMOs or practices that had at least one managed care contract are significantly more likely to prescribe generic medicines. Furthermore, physicians who have drug industry influence are less likely to prescribe generic medicines. This study also finds consistent evidence that generic prescribing is reduced for patients with pri- vate insurance compared to self-pay patients. Drug-specific characteristics play an important role for whether a drug is prescribed as a generic or brand-name – in- cluding not only market characteristics, such as monopoly duration length, public familiarity with the generic and the quality of the generic, but also non-clinical drug characteristics, such as the length of the generic name compared the length of the brand-name. In particular, the public’s familiarity with the generic has a large effect on the generic prescribing rate for a given drug. There are few differences between the generic prescribing habits of primary care physicians and specialists after controlling for the drugs prescribed.
Advisor: Frank Sloan | JEL Codes: D82, D83, I11, I13, I18 | Tagged:
Debunking the Cost-Shifting Myth: An Analysis of Dnamic Price Discrimination in California Hospitals
By Omar Nazzal
Cost-shifting, a dynamic form of price discrimination, is a phenomenon in which hospitals shift the burden of decreases in government-sponsored healthcare reimbursement rates to private health insurers. In this paper, I construct a data set spanning 2007 – 2011 that matches financial metrics of California hospitals to hospital- and market-specific characteristics with theoretical implications in price discrimination. The subsequent analysis is split into three stages. In the first and second stages, I use a fixed-effects OLS model to derive a point estimate of the inverse correlation between private revenue and government revenue that is consistent with recent empirical work in cost-shifting, a body of literature almost entirely reliant upon fixed-effects and difference-in-difference OLS. These types of models are encumbered by the inherent causality loop connecting public and private payment sources. I address this endogeneity problem in the third stage by specifying a fixed-effects 2SLS model based on an instrument for government revenue constructed with data from the California Department of Health Care Services and the U.S. Census. This instrument performed well in canonical tests for relevance and validity. I find that an increase in government payments causes an increase in private payments, and that the relationship is statistically-significant at all reasonable levels. In addition, I comment on properties of the data set that suggest that the original inverse correlation was due to inadequate measurements of market power. I conclude with policy implications and suggestions for future research.
Advisor: Frank Sloan | JEL Codes: I11, I13, I18, L11, L80 | Tagged:
By Ross Green
In the setting of a population with heterogeneous risk of illness, informational asymmetries in a competitive health insurance market can cause the gains from risk sharing to fall short of social optimality in equilibrium. Traditional policies meant to address the under-provision of insurance, like mandating open enrollment or community-rated premiums, can be prohibitively costly or impossible to implement. I consider three policy regimes in the context of a competitive insurance industry in which firms maximize profits by exerting effort to monitor the provision of health care. When multiple risk types are present in the population, I find that a subsidy rule based on the marginal costs of insuring high risks can induce a Pareto-improvement to risk sharing gains, at a cost to the efficiency of health care provision. The novelty of the subsidy rule lies in the way it incentives pooling equilibria.
Advisor: Curtis Taylor | JEL Codes: I0, I13, I18 | Tagged:
Health Care Utilization and Health Status of NCMS Elderly Enrollees in China: Evidence from CHARLS Data
By Pengpeng Wang
This study explores the effect of benefit designs and demographic factors on health care utilization and health status of elderly rural enrollees in the New Cooperative Medical Scheme, a rural health insurance program implemented by the Chinese government in 2003. Using the new data from CHARLS pilot study, we find that immediate reimbursement does not have a statistically significant effect on health utilization as suggested in a previous study, but instead on health status. Other policy-related factors neither have a significant effect due to limited data and large standard deviation nor display a consistent effect.
Advisor: Frank Sloan | JEL Codes: I13, I18 | Tagged:
Possibility of Cost Offset in Expanding Health Insurance Coverage: Using Medical Expenditure Panel Survey 2008
By Catherine Moon
The Patient Protection and Affordable Care Act aims to substantially reduce the number of the
uninsured over time and asserts that the financial burden of extending insurance coverage to the
previously uninsured will be offset by the benefit of the attendant improvement in their health.
Motivated by this policy, I explore whether health-insurance status and type affect one’s likelihood of
improving or maintaining health using the Medical Expenditure Panel Survey data. I build a set of
ordered regression models for health-status transitions under the first-order Markov assumption and
estimate it using maximum likelihood estimation. I perform a series of likelihood ratio tests for pooling to determine whether the latent propensity index is the same between adjacent initial health-status groups. Empirical results imply that expanding health care to the unwillingly uninsured due to severe
economic constraints and extending the scope of public insurance to that of private insurance will lead to improvement or maintenance of health for the relatively healthy population, implying the possibility of cost off-set in the expansion of coverage and the extension of scope.
Advisor: Frank Sloan, Michelle Connolly | JEL Codes: C12, C25, I12, I13, I18 | Tagged: