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Selection with Variation in Diagnostic Skill:Evidence from Radiologists

CIREQ-McGill Seminar 2019-2020
joint with the Department of Economics, McGill University

Leacock 429 (McGill University, 855 Sherbrooke West)

Organizer Laura Lasio (McGill University)

 

RÉSUMÉ

Physicians, judges, teachers, and agents in many other settings differ systematically in the decisions they make when faced with similar cases. Standard approaches to interpreting and exploiting such differences assume they arise solely from variation in preferences. We develop an alternative framework that allows variation in both preferences and diagnostic skill, and show that both dimensions are identified in standard settings under quasi-random assignment. We apply this framework to study pneumonia diagnoses by radiologists. Diagnosis rates vary widely among radiologists, and descriptive evidence suggests that a large component of this variation is due to differences in diagnostic skill. Our estimated model suggests that radiologists view failing to diagnose a patient with pneumonia as more costly than incorrectly diagnosing one without, so that less-skilled radiologists optimally choose lower diagnosis thresholds. Variation in skill can explain 55 percent of the variation in diagnostic decisions, and policies that improve skill perform better than uniform decision guidelines. Failing to account for skill variation can lead to highly misleading results in research designs that use agent assignments as instruments.

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