Information about this author at RePEc
NBER Working Papers and Publications
|January 2017||Causes and Consequences of Fragmented Care Delivery: Theory, Evidence, and Public Policy|
with Brigham Frandsen, James B. Rebitzer: w23078
Fragmented health care occurs when care is spread out across a large number of poorly coordinated providers. We analyze care fragmentation, an important source of inefficiency in the US healthcare system, by combining an economic model of regional practice styles with an empirical study of Medicare enrollees who move across regions. Roughly sixty percent of cross-regional variation in care fragmentation is independent of patients’ clinical needs or preferences for care. A one standard deviation increase in regional fragmentation is associated with a 10% increase in care utilization. We distinguish between two sources of care fragmentation: primary care fragmentation, where a patient’s care is split across many general practitioners, and specialty fragmentation, where a patient’s care is sp...
|January 2015||The Local Influence of Pioneer Investigators on Technology Adoption: Evidence from New Cancer Drugs|
with David Molitor: w20878
Local opinion leaders may play a key role in easing information frictions associated with technology adoption. This paper analyzes the influence of physician investigators who lead clinical trials for new cancer drugs. By comparing diffusion patterns across 21 new cancer drugs, we separate correlated regional demand for new technology from information spillovers. Patients in the lead investigator's region are initially 36% more likely to receive the new drug, but utilization converges within four years. We also find that “superstar ” physician authors, measured by trial role or citation history, have broader influence than less prominent authors.
|March 2014||Negative Tests and the Efficiency of Medical Care: What Determines Heterogeneity in Imaging Behavior?|
with Jason Abaluck, Christopher Kabrhel, Ali Raja, Arjun Venkatesh: w19956
We develop a model of the efficiency of medical testing based on rates of negative CT scans for pulmonary embolism. The model is estimated using a 20% sample of Medicare claims from 2000- 2009. We document enormous across-doctor heterogeneity in testing decisions conditional on patient risk and show it explains the negative relationship between physicians' testing frequencies and test yields. Physicians in high spending regions test more low-risk patients. Under calibration assumptions, 84% of doctors test even when costs exceed expected benefits. Furthermore, doctors do not apply observables to target testing to the highest risk patients, substantially reducing simulated test yields.