Note: This talk is also offered as a virtual webinar on April 4 at 6 p.m.

International procurement institutions have played an important role in drug supply. This paper studies price, delivery, and procurement lead time of drug supply for major infectious diseases (antiretrovirals, antimalarials, antituberculosis, and antibiotics) in 106 developing countries from 2007-2017 across four procurement institution types. We find that pooled procurement institutions lower prices: pooling internationally is most effective for small buyers and more concentrated markets, and pooling within-country is most effective for large buyers and less concentrated markets. Pooling can reduce delays, but at the cost of longer anticipated procurement lead times. Finally, pooled procurement is more effective for older-generation drugs, compared to intellectual property licensing institutions that focus on newer, patented drugs. We corroborate the findings using multiple identification strategies, including an instrumental variable strategy, the Altonji-Elder-Taber-Oster method, and reduced-form demand estimation. Our results suggest that the optimal mixture of procurement institutions depends on the trade-off between costs and urgency of need, with pooled international procurement institutions particularly valuable when countries can plan well ahead of time.

Coauthor: Nahim Bin Zahur (Queen’s University).

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Dr. Lucy Xiaolu Wang is a tenure-track Assistant Professor at University of Massachusetts Amherst, a Faculty Research Fellow at the Max Planck Institute for Innovation and Competition, Germany, and a Faculty Associate at the Canadian Centre for Health Economics. Her research focuses on the economics of innovation & digitization in health care markets (national and global), particularly in the biopharmaceutical and digital health industries. Dr. Wang earned her PhD in economics from Cornell University, her master’s degree in economics from Duke University, and her bachelor’s degree in applied economics (specialty: insurance) from Central University of Finance and Economics in Beijing, China. 

Note: This talk is also offered as an in-person seminar on April 5 at 12 p.m.

International procurement institutions have played an important role in drug supply. This paper studies price, delivery, and procurement lead time of drug supply for major infectious diseases (antiretrovirals, antimalarials, antituberculosis, and antibiotics) in 106 developing countries from 2007-2017 across four procurement institution types. We find that pooled procurement institutions lower prices: pooling internationally is most effective for small buyers and more concentrated markets, and pooling within-country is most effective for large buyers and less concentrated markets. Pooling can reduce delays, but at the cost of longer anticipated procurement lead times. Finally, pooled procurement is more effective for older-generation drugs, compared to intellectual property licensing institutions that focus on newer, patented drugs. We corroborate the findings using multiple identification strategies, including an instrumental variable strategy, the Altonji-Elder-Taber-Oster method, and reduced-form demand estimation. Our results suggest that the optimal mixture of procurement institutions depends on the trade-off between costs and urgency of need, with pooled international procurement institutions particularly valuable when countries can plan well ahead of time.

Coauthor: Nahim Bin Zahur (Queen’s University).

Image

Dr. Lucy Xiaolu Wang is a tenure-track Assistant Professor at University of Massachusetts Amherst, a Faculty Research Fellow at the Max Planck Institute for Innovation and Competition, Germany, and a Faculty Associate at the Canadian Centre for Health Economics. Her research focuses on the economics of innovation & digitization in health care markets (national and global), particularly in the biopharmaceutical and digital health industries. Dr. Wang earned her PhD in economics from Cornell University, her master’s degree in economics from Duke University, and her bachelor’s degree in applied economics (specialty: insurance) from Central University of Finance and Economics in Beijing, China. 

Co-sponsored by Peking University's Institute for Global Health and Development and the Asia Health Policy Program

Every year, hundreds of thousands of people suffer sudden cardiac death. What makes these deaths so tragic is that many of them are preventable, with an implanted cardioverter defibrillator (ICD) — if only we could know who was at high risk before they died. Using a massive new dataset of electrocardiograms (ECGs) linked to death certificates, we predict sudden cardiac death far better than current methods, both in a hold-out set of Swedish patients and in a completely independent dataset from Taiwan. We also show that high-risk patients — and only high-risk patients — who receive ICDs have significantly lower mortality. Finally, we create a generative model of the ECG waveform to tie what the model is ‘seeing’ back to underlying cardiac electrophysiology.

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Ziad Obermeyer's research uses machine learning to help doctors make better decisions and help researchers make new discoveries — by ‘seeing’ the world the way algorithms do. His work on algorithmic racial bias has impacted how many organizations build and use algorithms, and how lawmakers and regulators hold AI accountable. He is a co-founder of Nightingale Open Science and Dandelion Health, a Chan Zuckerberg Biohub Investigator, and a faculty research fellow at the National Bureau of Economic Research. He was named one of the 100 most influential people in AI by TIME magazine. Previously, he was an assistant professor at Harvard Medical School and continues to practice emergency medicine in underserved communities.