Generic Entry and The Effect on Prices in the Prescription Drug Market
by Sahana Giridharan
Abstract
Drug firms have utilized a variety of strategies that contribute to rising drug prices in the U.S. for the last few years. Strategic entry timing and number of indications a drug is approved might be two factors that contribute to this rise in prices. While there have been some studies uncovering a positive relationship between generic entry and branded prices, there has been little research done on the effects of generic entry on generic prices thus far. This work can impact policy aimed at decreasing generic drug prices and increasing competition in the generic drug market. Oncology and inflammatory bowel disease (IBD) are two disease areas that have a high price burden to patients in the U.S. today, hence using Medicare Part B Average Sales Price (ASP) data, I analyze the effect of entry timing on the price of 24 drugs in these two indication areas. Using the Drugs@FDA Database, I collect data on the FDA approval date of a drug, and on the indications a drug is approved for. Utilizing OLS, my results suggest that later entry times lead to lower drug prices, with a 1 year increase in entry time resulting in a 6.99% increase in prices. Results also suggest that an increase of 1 in the number of indications a drug is approved for leads to a 49.79% decrease in drug price. This could suggest that having existing generic competitors in the pharmaceutical market decreases generic prices, and that number of indications is a strong indicator of drug price. If the current work is confirmed by future studies similar to this studying entry time and price in the generic pharmaceutical market, it is possible that future drug policy should focus on promoting competition within the pharmaceutical market to lower generic prices.
Professor Frank Sloan, Faculty Advisor
Professor Grace Kim, Faculty Advisor
Professor Kent Kimbrough, Faculty Advisor
JEL Codes: L11; I11; C3
The Effects of Pharmaceutical Price Regulation on Probability of Patenting in OECD Countries
by Rachel Korn
Abstract
The introduction of parallel trade mechanisms allowing for the free trade of pharmaceutical goods in the European Economic Area represents a significant departure from the standard monopolistic competition pricing structure in the pharmaceutical market, in which firms have a great deal of control over pricing. Another mechanism, external reference pricing, also contributes to undermining traditional price structures by imposing a price ceiling on drugs. As these methods of regulating pricing in the healthcare market are receiving growing interest in countries such as the United States, it is prudent to consider their effects. It is apparent that parallel trade and external reference pricing decrease average drug costs, but little has been said about their effects on drug availability. Using global patent data from the European Patent Office PATSTAT database as a proxy for drug availability, I investigate how parallel trade and external reference pricing affect the decision of firms to file a pharmaceutical patent in a given country. I accomplish this through a logistic regression model with a difference-in-differences approach to estimate the probability of patenting a pharmaceutical in an OECD country, given that a patent has previously been approved in the United States. I find that the presence of parallel trade in a country significantly decreases the probability of patenting and increases patent lag time while external reference pricing unexpectedly increases the probability of patenting and decreases patent lag time. These findings demonstrate the complexity in attempting to create policy to regulate rising pharmaceutical prices, as doing so may increase affordability of existing drugs in a country while decreasing availability of new ones.
Professor Michelle Connolly, Faculty Advisor
JEL Codes: I1, I11, I19
Analysis of Brain Diagnoses and the Incidence of Chronic Traumatic Encephalopathy (CTE)
by Arjun Lakhanpal
Abstract
Chronic traumatic encephalopathy (CTE) has become a significant area of scientific inquiry in relation to various sports with contact exposure, specifically boxing and professional football, resulting from many individuals who participated in these sports being diagnosed with CTE neuropathology after death. This paper contributes to the CTE literature by analyzing the various predictors of the progression of neurodegenerative disorders, including CTE, that are associated with a history of head impact exposure. In addition, it analyzes how manner of death shifts depending on an individual’s clinical brain diagnosis, which is a decision based upon the clinical record and case review of a patient.
Through data from the NIH NeuroBioBank, the VA-BU-CLF Brain Bank, and data self-collected from living individuals with symptoms associated with CTE, this paper explores an analysis of various brain diagnoses through a large control population and small subset of athletes and veterans. Logistic regression models are established to analyze explanatory variables of clinical brain diagnosis, manner of death, and CTE presence and severity.
These logistic regression models confirm previous research surrounding the potential racial influence present in Black populations with schizophrenia related diagnoses and illustrate the degree to which neurodegenerative disorders, specifically Parkinson’s Disease, are influenced by increased age. Specific to CTE, the analysis conducted through the sample population illustrates the influence of an extra year of football played at the professional level, while counteracting existing literature regarding the association between position and CTE.
Professor Jason Luck,Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: I10, Z20, J15
Myocardial Infarction, Health Behavior, and the Grossman Model
by Emma Mehlhop
Abstract
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.
Professor Charles Becker,Faculty Advisor
Professor M. Kate Bundorf, Faculty Advisor
Professor Grace Kim, Faculty Advisor
Professor Frank Sloan, Faculty Advisor
JEL Codes: I1, I10, I12
The Effects of Leveraged Buyouts on Health Outcomes
by Robert Williams
Abstract
Private equity firms first began acquiring hospitals in the United States during the early 1990s, yet the effects of private equity ownership on patient outcomes and treatment costs are still not clear. Some argue that although private equity firms are adept at improving operating efficiencies and introducing managerial expertise, these cost-cutting measures may come at the expense of patient outcomes.
Because acute myocardial infarctions (AMIs) serve as proxies for patient outcomes and treatment costs, I collect information on 30-day mortality rates and Medicare reimbursements for treatments of AMIs at US Medicare-certified short-term acute care general hospitals from 2014 to 2019. This paper uses fixed effects models to analyze the impact of leveraged buyouts, relative to strategic acquisitions, on patient outcomes. After integrating both hospital and time fixed effects, I find that private equity ownership does not lead to significant changes in Medicare reimbursements or mortality rates for AMI treatments.
Professor Ryan McDevitt, Faculty Advisor
Professor Grace Kim, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: I0, I110, G340
The Effects of Health IT Innovation on Throughput Efficiency in the Emergency Department
by Michael Levin
Abstract
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.
View Data (Email for Access)
Advisors: Michelle Connolly, Ryan McDevitt | JEL Codes: I1, I18, O33
Incentive Programs for Neglected Diseases
By Pranav Ganapathy
We propose and evaluate an auction mechanism for the priority review voucher program. The 2007 voucher program rewards drug developers for regulatory approval of novel treatments for neglected tropical diseases. Previous papers have proposed auctioning vouchers for the priority review voucher program but have offered neither a mathematical model nor a framework. We present a mechanism design problem with one pharmaceutical company producing one drug for a neglected tropical disease. The mechanism that maximizes the regulator’s expected surplus is a take-it-or-leave-it offer, with three different offers based on low, intermediate, and high neglected disease burdens. We demonstrate how mechanism design can be applied to settings in which the buyer pays for public access to a product with regulatory speed. Finally, this paper may be useful to policymakers seeking to improve access to voucher drugs through modifications of the program.
Advisors: Professor David Ridley, Professor Giuseppe Lopomo, Professor Michelle Connolly| JEL Codes: I1, D44, D82
The Impact of Medicare Nonpayment: A Quasi-Experimental Approach
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
The Effect of Early Life Economic Conditions on Child Health in Post-Soviet Russia
By Hemal Pragneshbhai Patel
The effect of the economic collapse on health has been extensively documented in Russia since the dissolution of the Soviet Union. The proportion of stunted children in Russia increased substantially in this period, but no study has investigated the mechanisms by which this economic collapse impacted child health outcomes. This paper uses an OLS regression followed by a Binder-Oaxaca decomposition to determine the specific economic factors that significantly contributed to this decrease in child heights.
Advisors: Professor Charles Becker | JEL Codes: I1; I14; J13
The Effect of Tourism on Child Health Outcomes in Roatán, Honduras
By Hemal Pragneshbhai Patel
Increased tourism, especially in developing economies, brings with it more economic opportunities and avenues for development. In Roatán, the largest of Honduras’ Caribbean Bay Islands, tourism has brought economic development that the island had never before experienced. However, the impact of this economic development brought by increasing cruise ship tourism on child health has yet to be investigated. The increase in economic development is expected to improve child health through improved absorbed nutrition, and this paper uses an OLS regression model to examine how differential exposure to tourism development during a child’s crucial early life developmental window impacts later life health outcomes, proxied by height-for-age Z-scores.
Advisors: Professor Dennis Clements, Professor Michelle Connolly | JEL Codes: I1; I15; Z32
