Ziad Obermeyer

School of Public Health
University of California at Berkeley
2121 Berkeley Way
Berkeley, CA 94704

E-Mail: EmailAddress: hidden: you can email any NBER-related person as first underscore last at nber dot org
Institutional Affiliation: University of California at Berkeley

NBER Working Papers and Publications

August 2019Who is Tested for Heart Attack and Who Should Be: Predicting Patient Risk and Physician Error
with Sendhil Mullainathan: w26168
In deciding whether to test for heart attack (acute coronary syndromes), physicians implicitly judge risk. To assess these decisions, we produce explicit risk predictions by applying machine learning to Medicare claims data. Comparing these on a patient-by-patient basis to physician decisions reveals more about low-value care than the usual approach of measuring average testing results. It more precisely quantifies over-use: while the average test is marginally cost-effective, tests at the bottom of the risk distribution are highly cost-ineffective. But it also reveals under- use: many patients at the top of the risk distribution go untested; and they go on to have frequent adverse cardiac events, including death, in the next 30 days. At standard clinical thresholds, these event rates sugg...

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