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Personalizing Health Care: Using Economics to Target Treatments

Paper Session

Friday, Jan. 4, 2019 8:00 AM - 10:00 AM

Hilton Atlanta, 303
Hosted By: Health Economics Research Organization
  • Chair: Gautam Gowrisankaran, University of Arizona

Selection with Skills: Evidence from Radiologists

David C. Chan
,
Stanford University
Matthew Gentzkow
,
Stanford University

Abstract

Agents in a wide range of settings exhibit variation in decisions and outcomes. We note that this variation is jointly determined by skills and preferences, and we develop a simple framework that uses the joint distribution of provider-specific decisions and outcomes to decompose variation into skills and preferences. We apply this framework in the setting of pneumonia diagnosis by radiologists. Radiologists vary in both their diagnostic rates (decisions) 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. Lower-skilled radiologists have less tenure and are more verbose, while female radiologists are more averse to false negatives. We consider counterfactual radiologists with varying skills and preferences. Homogenizing skill reduces 60% of the variation in diagnosis rates and eliminates variation in false omission rates. Imposing fixed diagnostic thresholds also reduces false omission rates for the same average diagnostic rate.

Extrapolation using Selection and Moral Hazard Heterogeneity from within the Oregon Health Insurance Experiment

Amanda Kowalski
,
University of Michigan

Abstract

I aim to shed light on why emergency room (ER) utilization increased following the Oregon
Health Insurance Experiment but decreased following a Massachusetts policy. To do so, I unite
the literatures on insurance and treatment effects. Under an MTE model that assumes no more
than the LATE assumptions, comparisons across always takers, compliers, and never takers
can inform the impact of polices that expand and contract coverage. Starting from the Oregon
experiment as the “gold standard," I make comparisons within Oregon and extrapolate my findings to Massachusetts. Within Oregon, I find adverse selection and heterogeneous moral hazard. Although previous enrollees increased their ER utilization, evidence suggests that subsequent enrollees will be healthier, and they will decrease their ER utilization. Accordingly, I can reconcile the Oregon and Massachusetts results because the Massachusetts policy expanded coverage from a higher baseline, and new enrollees reported better health.

The Impacts of Hospital Delivery Practices on Infant Health

David Silver
,
Princeton University
David Card
,
University of California-Berkeley
Alessandra Fenizia
,
University of California-Berkeley

Abstract

Risk-adjusted rates of cesarean delivery vary widely across hospitals. We use discharge records for low-risk first births in California, merged to vital statistics and inpatient and outpatient data for the year after birth, to study the impacts of these differences on infant health. We classify hospitals within local health care markets as having high or low c-section rates, and use relative distance from a mother’s home to the nearest high versus low c-section hospital as an instrumental variable for the type of hospital at delivery. Proximity to a high c-section hospital leads to more cesarean deliveries, fewer vaginal births after prolonged labor, and higher average Apgar scores. Infants of complying mothers are more likely to visit the emergency department in the year after birth but less likely to be readmitted to hospital. They also have lower infant mortality, driven by a reduction in the joint probability of prolonged labor and subsequent death. A simple cost-benefit calculation suggests that re-allocating births to high-c-section hospitals could lead to net social benefits.
Discussant(s)
Pierre-Thomas Léger
,
University of Illinois
Sebastian Fleitas
,
University of Leuven
Matthew Notowidigdo
,
Northwestern University
JEL Classifications
  • I1 - Health
  • L1 - Market Structure, Firm Strategy, and Market Performance