演講者簡介 : Professor Chan received his Ph.D. in Economics from Massachusetts Institute of Technology in 2013. He is currently an Assistant Professor of Health Research and Policy at Stanford University. His research fields are labor economics, organizational economics, and information, productivity.
演講摘要 : We study the problem of classification in the setting of radiology and connect it the economic literatures of selection and productivity. We develop a simple framework that uses the joint distribution of provider-specific decisions and outcomes to decompose variation in decisions and outcomes into skills and preferences. Radiologists vary in both their diagnostic rates (decision) and their false omission rates (outcomes), and radiologists with higher diagnostic rates have higher false omission rates. We rationalize these patterns with a model of diagnosis, in which radiologists with heterogenous diagnostic skill endogenously choose thresholds to minimize some function of false negatives and false positives. Radiologists wish to avoid false negatives more than false positives, and this imbalance increases with lower diagnostic skill. Variation in skills can explain 60% of variation in diagnostic decisions, and policies to improve skills generally improve welfare more than policies to harmonize preferences.
