Charles River Associates
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Chicago, IL 60606
Information about this author at RePEc
NBER Working Papers and Publications
|October 2017||Measuring the Potential Health Impact of Personalized Medicine: Evidence from MS Treatments|
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 ...
Forthcoming: Measuring the Potential Health Impact of Personalized Medicine: Evidence from MS Treatments, Kristopher Hult. in Economic Dimensions of Personalized and Precision Medicine, Berndt, Goldman, and Rowe. 2017
|December 2016||How Does Technological Change Affect Quality-Adjusted Prices in Health Care? Systematic Evidence from Thousands of Innovations|
with Sonia Jaffe, Tomas J. Philipson: w22986
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 is a central question for both positive and normative analysis of this sector. This is a question of the impact of new innovations on quality-adjusted prices in health care. 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...
|November 2012||Public Liabilities and Health Care Policy|
with Tomas J. Philipson: w18571
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.