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by Emma Mehlhop
This paper contributes an empirical test of Michael Grossman’s model of the demand for health and a novel application of the model to myocardial infarction (MI) incidence. Using data from the University of Michigan’s Health and Retirement Study (HRS), I test Grossman’s assumptions regarding the effects of hourly wage, sex, educational attainment, and age on health demand along with the effects of new variables describing health behaviors, whether or not a respondent is insured, and whether or not they are allowed sufficient paid sick leave. I use logistic regression to estimate health demand schedules using five different health demand indicators: exercise, doctor visits, drinking, smoking, and high BMI. I apply the Cox Proportional Hazard model to examine two equations for the marginal product of health investment both in terms of propensity to prevent death and to prevent MI, one of the leading causes of mortality in the United States. This study considers the effects of the aforementioned health demand indicators, among other factors, on the marginal product of health investment for the prevention of death compared to the prevention of MI. Additionally, there is significant evidence of a negative effect of health insurance on likelihood of exercising regularly, implying some effect of moral hazard on the health demand schedule.
Advisors: Professor Charles Becker, Professor Grace Kim, Professor Frank Sloan | JEL Codes: I1, I10, I12
By Michael Levin
Overcrowding in United States hospitals’ emergency departments (EDs) has been identified as a significant barrier to receiving high-quality emergency care, resulting from many EDs struggling to properly triage, diagnose, and treat emergency patients in a timely and effective manner. Priority is now being placed on research that explores the effectiveness of possible solutions, such as heightened adoption of IT to advance operational workflow and care services related to diagnostics and information accessibility, with the goal of improving what is called throughput efficiency. However, high costs of technological process innovation as well as usability challenges still impede wide-spanning and rapid implementation of these disruptive solutions. This paper will contribute to the pursuit of better understanding the value of adopting health IT (HIT) to improve ED throughput efficiency.
Using hospital visit data, I investigate two ways in which ED throughput activity changes due to increased HIT sophistication. First, I use a probit model to estimate any statistically and economically significant decreases in the probability of ED mortality resulting from greater HIT sophistication. Second, my analysis turns to workflow efficiency, using a negative binomial regression model to estimate the impact of HIT sophistication on reducing ED waiting room times. The results show a negative and statistically significant (p < 0.01) association between the presence of HIT and the probability of mortality in the ED. However, the marginal impact of an increase in sophistication from basic HIT functionality to advanced HIT functionality was not meaningful. Finally, I do not find a statistically significant impact of HIT sophistication on expected waiting room time. Together, these findings suggest that although technological progress is trending in the right direction to ultimately have a wide-sweeping impact on ED throughput, more progress must be made in order for HIT to directly move the needle on confronting healthcare’s greatest challenges.
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Advisors: Professor Ryan McDevitt, Professor Michelle Connolly | JEL Codes: I1, I18, O33
By Audrey Kornkven
In October 2008, a provision of the Deficit Reduction Act of 2005 known as Medicare “Nonpayment” went into effect, eliminating reimbursement for the marginal costs of preventable hospital-acquired conditions in an effort to correct perverse incentives in hospitals and improve patient safety. This paper contributes to the existing debate surrounding Nonpayment’s efficacy by considering varying degrees of fiscal pressure among hospitals; potential impacts on healthcare utilization; and differences between Medicare and non-Medicare patient populations. It combines data on millions of hospital discharges in New York from 2006-2010 with hospital-, hospital referral region-, and county-level data to isolate the policy’s impact. Analysis exploits the quasi-experimental nature of Nonpayment via difference-in-differences with Mahalanobis matching and fuzzy regression discontinuity designs. In line with results from Lee et al. (2012), Schuller et al. (2013), and Vaz et al. (2015), this paper does not find evidence that Nonpayment reduced the likelihood that Medicare patients would develop a hospital-acquired condition, and concludes that the policy is not likely the success claimed by policymakers. Results also suggest that providers may select against unprofitable Medicare patients when possible, and are likely to vary in their responses to financial incentives. Specifically, private non-profit hospitals appear to have been most responsive to the policy. These findings have important implications for pay-for-performance initiatives in American healthcare.
Advisors: Professor Charles Becker, Professor Frank Sloan, Professor Grace Kim| JEL Codes: I1, I13, I18
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
By Michael Karamardian
Because Medicare’s prospective payment system for long-term acute-care hospitals (LTCHs) makes a large lump-sum form of payment once patients reach a minimum length-ofstay threshold, LTCHs have a unique opportunity to maximize profits by strategically discharging patients as soon as the payment is received. This analysis explores how the level of competition between LTCHs in geographic markets affects the probability of a patient being strategically discharged. The results show that patients at LTCHs in more competitive markets have a lower probability of being strategically discharged than at those in less competitive markets, suggesting increased competition could help save Medicare funding.
Advisors: Kent Kimbrough and James Roberts | JEL Codes: D22, I11, I18