"Measuring the Potential Health Impact of Personalized Medicine: Evidence from MS Treatments"
Chapter in NBER's Economic Dimensions of Personalized and Precision Medicine and NBER Working Paper No. 23900
Individuals respond to pharmaceutical treatments differently due to the heterogeneity of patient populations. This heterogeneity can make it difficult to determine how efficacious or burdensome a treatment is for an individual patient. Personalized medicine involves using patient characteristics, therapeutics, or diagnostic testing to understand how individual patients respond to a given treatment. Personalized medicine increases the health impact of existing treatments by improving the matching process between patients and treatments and by improving a patient's understanding of the risk of serious side effects. In this paper, I compare the health impact of new treatment innovations with the potential health impact of personalized medicine. I find that the impact of personalized medicine depends on the number of treatments, the correlation between treatment effects, and the amount of noise in a patient's individual treatment effect signal. For multiple sclerosis treatments, I find that personalized medicine has the potential to increase the health impact of existing treatments by roughly 50 percent by informing patients of their individual treatment effect and risk of serious side effects.
"The Value of Medical Innovation Versus Industry Rewards" (with Tomas J. Philipson)
Value in Health
Objective: This paper provides systematic evidence on the share of the value of health generated by drugs and other health care goods and services that accrue to patients on the demand side versus the manufacturers on the supply side.
Method: We exploit a large data set with over 9,000 cost-effectiveness measures for various interventions, which we convert into measures of the shares of the value of improved health appropriated by the supply side using literature estimates of how patients value gains in health.
Results: We find that if patients value a quality-adjusted life year (QALY) at $450,000 the median share appropriated for drugs on the supply side is around 6 percent and has declined at 0.1 percent per year between 1997 and 2019. This compares to other health care interventions, such as screenings or medical procedures, which have a median value of 9 percent but decline at 0.3 percent per year over the same period. If patients value a QALY at $150,000 the median share appropriated for drugs and other health care interventions on the supply side is around 18 percent and 27 percent respectively.
Conclusion: Many policy debates center on the idea that the supply side is capturing too much of the value of the medical innovation that they generate. We find that for these interventions, a large share of the value of medical innovation accrues to patients on the demand side since the revenue to innovators is often far less than the patient’s value of these medical innovations.
American Journal of Health Economics and NBER Working Paper No. 22986
Medical innovations have improved survival and treatment for many diseases but have simultaneously raised spending on health care. Many health economists believe that technological change is the major factor driving the growth of the heath care sector. Whether quality has increased as much as spending – that is, whether new innovations raise or lower quality-adjusted prices in health care – is a central question for both positive and normative analysis of this sector. Previous research has provided anecdotal evidence on this issue. We perform a systematic analysis of the impact of technological change on quality-adjusted prices, with over six thousand comparisons of innovations to incumbent technologies. For each innovation in our dataset, we observe its price and quality, as well as the price and quality of an incumbent technology treating the same disease. Our main finding is that for about two-thirds (68%) of innovations, the innovation’s quality-adjusted price is higher than the incumbent’s. Despite this finding, we argue that quality-adjusted prices may fall or rise over time depending on how fast prices decline for a given treatment over time. We calibrate that price declines of 4% between the time when a treatment is a new innovation and the time when it has become the incumbent would be sufficient to offset the observed price difference between innovators and incumbents for a majority of the innovations. We conclude by discussing the conditions particular to the health care industry that may result in less rapid declines, or even increases, in quality-adjusted prices over time.
"Incremental Innovation and Pharmaceutical Productivity"
This paper investigates the role of novel and incremental innovation in biopharmaceutical markets. Previous research focusing only on novel innovation—FDA-approved new molecules—has led to the conclusion that the pharmaceutical industry is in a "productivity crisis," since R&D spending has increased exponentially while FDA-approved new molecules have remained flat over time. I find that incremental innovation—new drugs created by modifying existing FDA-approved molecules—accounts for 49% of the health impact of new innovations, and productivity has increased 30% between 1980 and 2009 when considering the health impact of both novel and incremental innovations. I construct and calibrate a model of how firms trade off between novel and incremental innovation to predict future innovation trends, and I find that the relative share of incremental innovation will fall by 12 percentage points during the 2010s and the productivity of new innovations will decline by 40% during this same period.
"Public Liabilities and Health Care Policy" (with Tomas J. Philipson)
NBER Working Paper No. 18571
Many countries have large future public liabilities attributable to health care programs. However, little explicit analysis exists about how health care policies affect these program liabilities. We analyze how reimbursement and approval policies affect public liabilities through their impact on the returns to medical innovation, a central factor driving spending growth. We consider how policies impact innovative returns through expected earnings, their risk-adjustment, and their timing and defaults through the approval process. Our analysis implies that cutbacks in government programs may raise government liabilities and expansions may lower them. We quantitatively calibrate these non-standard effects for the US Medicare program.
"Competition and Innovation in Pharmaceuticals" - In Progress
My research explores the relationship between competition and innovation in pharmaceuticals. I examine three main questions: (1) How does competition affect the incentive for firms to innovate? (2) How do market conditions affect the firms’ decision to invest in novel innovation (creating treatments from new molecules) versus follow-on or incremental innovation (creating treatments from already-approved molecules)? (3) What are the effects of antitrust policies, FDA approvals, and pharmaceutical mergers on the health value of innovation in disease categories with different levels of competition?
"Measuring the Value of Incremental Innovation Using Evidence from Medicare Part D" - In Progress
This paper uses the introduction of Medicare Part D, which significantly increased prescription drug coverage for the elderly, as an instrument to measure the effect of insurance on pharmaceutical innovation. I find that increases in prescription insurance coverage increased the innovation of both novel innovation—FDA-approved new molecules—and incremental innovation—new drugs created by modifying existing FDA-approved molecules—by 75% for diseases with the highest Medicare market share relative to the median. Exploiting the difference in the time it takes for novel and incremental innovations to be approved, I measure the effect of this increase in incremental innovation on health outcomes. I find that incremental innovation had a large effect on prescription drug utilization and decreased the probability of death by two tenths of a percentage point for diseases with the highest Medicare market share relative to the median.