How to Identify Team-based Primary Care in the United States Using Medicare Data

Research output: Contribution to journalArticlepeer-review


Background:Studying team-based primary care using 100% national outpatient Medicare data is not feasible, due to limitations in the availability of this dataset to researchers.Methods:We assessed whether analyses using different sets of Medicare data can produce results similar to those from analyses using 100% data from an entire state, in identifying primary care teams through social network analysis. First, we used data from 100% Medicare beneficiaries, restricted to those within a primary care services area (PCSA), to identify primary care teams. Second, we used data from a 20% sample of Medicare beneficiaries and defined shared care by 2 providers using 2 different cutoffs for the minimum required number of shared patients, to identify primary care teams.Results:The team practices identified with social network analysis using the 20% sample and a cutoff of 6 patients shared between 2 primary care providers had good agreement with team practices identified using statewide data (F measure: 90.9%). Use of 100% data within a small area geographic boundary, such as PCSAs, had an F measure of 83.4%. The percent of practices identified from these datasets that coincided with practices identified from statewide data were 86% versus 100%, respectively.Conclusions:Depending on specific study purposes, researchers could use either 100% data from Medicare beneficiaries in randomly selected PCSAs, or data from a 20% national sample of Medicare beneficiaries to study team-based primary care in the United States.

Original languageEnglish (US)
Pages (from-to)118-122
Number of pages5
JournalMedical care
Issue number2
StatePublished - Feb 2021


  • Medicare
  • primary care
  • social network analysis

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health


Dive into the research topics of 'How to Identify Team-based Primary Care in the United States Using Medicare Data'. Together they form a unique fingerprint.

Cite this