Ariel Dora Stern

Harvard Business School
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NBER Working Papers and Publications

December 2017Characterizing the Drug Development Pipeline for Precision Medicines
with Amitabh Chandra, Craig Garthwaite
in Economic Dimensions of Personalized and Precision Medicine, Ernst Berndt, Dana Goldman, and John Rowe, editor
November 2017Characterizing the Drug Development Pipeline for Precision Medicines
with Amitabh Chandra, Craig Garthwaite: w24026
Precision medicines – therapies that rely on genetic, epigenetic, and protein biomarkers – create a better match between individuals with specific disease subtypes and medications that are more effective for those patients. These treatments are expected to be both more effective and more expensive than conventional therapies, implying that their introduction is likely to have a meaningful effect on health care spending patterns. In addition, precision medicines can change the expected profitability of therapies both by allowing more sophisticated pricing systems and potentially decreasing the costs of drug development through shorter and more focused trials. As a result, this could change the types of products that can be profitably brought to market. To better understand the landscape ...
August 2013Physician Beliefs and Patient Preferences: A New Look at Regional Variation in Health Care Spending
with David Cutler, Jonathan Skinner, David Wennberg: w19320
There is considerable controversy about the causes of regional variations in health care expenditures. Using vignettes from patient and physician surveys linked to fee-for-service Medicare expenditures, this study asks whether patient demand-side factors or physician supply-side factors explain these variations. The results indicate that patient demand is relatively unimportant in explaining variations. Physician organizational factors matter, but the most important factor is physician beliefs about treatment. In Medicare, we estimate that 35 percent of spending for end-of-life care, and 12 percent of spending for heart attack patients (and for all enrollees) is associated with physician beliefs unsupported by clinical evidence.
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