Physician Consolidation and Its Effect on Specialist Care:  A Causal Analysis with Machine Learning

Grant #: 75133
Grantee Institution: George Mason University
Principal Investigator: Alison Evans Cuellar, Ph.D.
Data set: Health Care Cost Institute
Grant Period: 12/15/17 – 12/14/18
Budget: $150,000

The goal of the project is inform policy discussions among federal and state regulators and help payers better understand the implications of physician consolidation into larger practices.  A number of studies have documented steady increases in physician prices at a time of increased physician consolidation, but the pattern has not been uniform across specialties or regions.  While there is hope that larger physician organizations can provide better-coordinated care, monitor population health, and improve quality, consolidation has also raised concerns among regulators and payers that greater physician market power could raise prices. Using data from the Health Care Cost Institute (HCCI) and other sources from 2011-2015, this study will provide estimates of how physician consolidation affects the price of care. In particular, the researchers will apply machine learning techniques to estimate how these impacts vary by type of service, marketplace sector, and community factors in order to provide policymakers, community leaders, and payers with results that have useful, straightforward interpretations. Deliverables will include a project work plan and final narrative and financial reports. The grantee will produce online maps and publications, and present findings to a variety of stakeholder audiences, including policymakers at the federal, state, and local levels and other key stakeholders, as part of the deliverables for this grant.