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Health Care Delivery: Establishing Links Between Evidence and Practice

Paper Session

Saturday, Jan. 6, 2018 8:00 AM - 10:00 AM

Marriott Philadelphia Downtown, Grand Ballroom Salon J
Hosted By: Health Economics Research Organization
  • Chair: Jay Bhattacharya, Stanford University

The Adoption and Diffusion of Medical Technology: Evidence From Cardiac Valve Procedures

Ariel Dora Stern
,
Harvard University
Robert Huckman
,
Harvard University

Abstract

: New health care technologies have saved millions of lives but have also been implicated in health care cost growth. The adoption of new technologies itself is a learning process, often involving physician learning and tradeoffs in quality and productivity as clinicians move from older to newer procedures. We consider the early years of uptake for a new cardiac procedure—transcatheter aortic valve replacement (TAVR)—and its implications for physician procedure mix and patient outcomes. In its first three years, TAVR grew to include over 1/3 of all aortic valve replacement procedures in New York State, which serves as the setting for our empirical analysis. Using data on all aortic valve replacement procedures performed over the period leading up to and spanning the procedure’s introduction, we document uptake across physicians and hospitals as well as patterns of access and receipt among (potential) patients. We ask whether the uptake of TAVR is correlated with prior utilization of SAVR – the more-intensive incumbent technology – at the physician and/or facility level. We find that a hospital’s pre-TAVR level of specialization in SAVR positively predicts both TAVR adoption and intensity of use. That is, hospitals that were specialized in the old procedure were more likely to take-up the new technology. We also find that surgeons’ early experience with TAVR predicts subsequent intensity of use. With respect to outcomes, we observe meaningfully shorter post-procedure length of stay in hospital following TAVR relative to SAVR, however differences in
post-procedure mortality for the the two technologies are difficult to discern. The insights from this project are relevant for a broader understanding of the impact of technology diffusion on physician treatment decisions, the accumulation of technology-specific experience by physicians, patient access to new therapies, and health care productivity.

Are Mammograms Helpful for Some Women but Harmful for Others? Evidence From the Canadian National Breast Screening Study

Amanda Kowalski
,
Yale University

Abstract

TBA

Coordination Within Teams and The Cost of Health Care

Leila Agha
,
Dartmouth College
Keith Ericson
,
Boston University
Kimberly Geissler
,
University of Massachusetts-Amherst
Benjamin Lupin
,
Boston University
James Rebitzer
,
Boston University

Abstract

We examine how primary care physicians (PCPs) assemble teams of specialists and the impact of team formation on spending. In our model, PCPs can make costly investments in relationships with specialists that have benefits for care coordination. We define a team-based coordination of care measure, “referral concentration,” based on referral flows. PCPs who have higher referral concentration (i.e. work with fewer specialists) invest more in relationship- specific capital and have better outcomes. We examine commercial patients in the Massachusetts All-Payer Claims Database and Medicare patients nationwide. Referral concentration has a low correlation with existing patient-based coordination of care measures. Conditional on health status, higher referral concentration leads to significantly lower spending for both commercial and Medicare patients. The effect of referral concentration is robust to two different identification strategies. First, we instrument for changes in referral concentration using Medicare patients who move across regions, and find a significant effect on spending.
Second, we use specialist fixed effects, comparing the spending of individuals who see the same specialist, but come from PCPs with different referral concentration.
Discussant(s)
David Meltzer
,
University of Chicago
Atheendar Venkataramani
,
University of Pennsylvania
Jay Bhattacharya
,
Stanford University
JEL Classifications
  • I1 - Health