Bibliographic record
Abstract
OBJECTIVES: Triage algorithms are ubiquitous in emergency care settings, but the extent of their use in primary care is unknown. This study asks whether primary care practices prioritize patients with more acute service needs. METHODS: We used an audit study in which simulated patients were randomized to 2 clinical scenarios-a new patient seeking a routine check-up or a new patient seeking treatment for newly diagnosed hypertension-and attempted to schedule appointments with thousands of randomly selected primary care physicians across 10 states. We estimated the difference in appointment availability by clinical scenario. For scheduled appointments, we also estimated the difference in wait times by clinical scenario. RESULTS: While there was no difference in appointment availability, the mean wait time for simulated patients seeking a routine check-up was nearly 5 days longer than the mean wait time for simulated patients with hypertension. CONCLUSIONS: As demand for primary care increases while the supply remains stable, it will be important for practices to identify and prioritize patients with more acute service needs. Our results show that primary care physicians are already adopting such practices.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".