How to Identify Team-based Primary Care in the United States Using Medicare Data
Bibliographic Data
| ID | 9101039 |
|---|---|
| Authors | Yong-Fang Kuo (0000-0003-1927-0927, Internal Medicine and Sealy Center on Aging, corresponding author), Yu-Li Lin (0000-0003-4721-9387, Preventive Medicine and Population Health), Daniel C Jupiter (0000-0002-3235-0473, General Department of Preventive Medicine), Daniel Jupiter (Preventive Medicine and Population Health) |
| Year | 2021 |
| Volume | 59 |
| Issue | 2 |
| Pages | 118-122 |
| Publication date | 2021-02-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/mlr.0000000000001478 |
| PMID | 33273297 |
| OpenAlex | W3106925439 |
| Language | EN |
| References cited | 7 |
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
Family medicine · MEDLINE · Political science · Primary care · Chronic Disease Management Strategies · Healthcare Systems and Technology · Medicine · Primary Care and Health Outcomes
| Citation velocity | historical |
|---|---|
| Highly cited | No |