NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
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A Machine Learning Approach to Low-Value Health Care: Wasted Tests, Missed Heart Attacks and Mis-Predictions

Sendhil Mullainathan, Ziad Obermeyer

NBER Working Paper No. 26168
Issued in August 2019, Revised in December 2019

---- Acknowledgments ----

Previously circulated as "Who is Tested for Heart Attack and Who Should Be: Predicting Patient Risk and Physician Error." We acknowledge financial support from grant DP5 OD012161, from the Office of the Director of the National Institutes of Health, and grant P01 AG005842, from the National Institute on Aging. We are deeply grateful to Advik Shreekumar, as well as Adam Baybutt, Brent Cohn, Christian Covington, Shreyas Lakhtakia, Katie Lin, Ruchi Mahadeshwar, Jasmeet Samra, Cassidy Shubatt, and Aly Valliani, for outstanding research assistance; and to Amitabh Chandra, Xavier Gabaix, Jon Kolstad, Suchi Saria, Andrei Shleifer and Richard Thaler for very helpful feedback on a draft. We are also appreciative of seminar participants at several institutions for their thoughtful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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