Impact of Primary Care Exception Expansion on Family Medicine Resident Billing During the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The Medicare Primary Care Exception (PCE) permits indirect supervision of residents performing lower-complexity visits in primary care settings. During the COVID-19 pandemic, Medicare expanded the PCE to all patient visits regardless of complexity. This study investigates how PCE expansion changed resident billing practices at a family medicine residency during calendar year 2020. We hypothesized that residents not constrained by the PCE would bill more high-level visits. METHODS: We queried billing codes from attendings' and residents' established evaluation and management visits associated with the University of Washington Family Medicine Residency (UWFMR) from January to December 2020. We used χ2 tests to compare resident and attending physicians' use of low/moderate and high-level codes by quarter. RESULTS: Resident high-complexity code use increased after PCE expansion in Q4 (odds ratio [OR] 3.50 [2.34-5.23]) compared to Q1. No change was observed among attending physicians (OR 1.05 [0.86-1.28]). Resident and attending billing patterns became more similar following PCE expansion. CONCLUSIONS: With the PCE expansion, senior family medicine resident physicians at UWFMR used higher-complexity billing codes at a rate approximating that of attending physicians. The findings of this study have implications regarding the financial well-being and sustainability of primary care residency training and raise a relevant policy question about whether the PCE expansion should persist. More research is needed to determine whether these findings were replicated in other primary care residency practices, the impact on resident education, and the impact on patient outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".