Pathways to Independent Primary Care Clinical Practice: How Tall Is the Shortest Giant?
Bibliographic record
Abstract
Patients can be treated by a physician, a nurse practitioner (NP), or a physician assistant (PA) despite marked differences in the education and training for these three professions. This natural experiment allows examination of a critical question: What is the minimum education and training required to practice primary care? In other words, how tall is the shortest giant? State licensing requirements, not educational bodies, legislate minimum training. The current minimum is 6 years, which includes 27.5 weeks of supervised clinical experience (SCE), for NPs. In comparison, PAs train for 6 years with 45 weeks of SCE, and physicians for at least 8 years with 110 weeks of SCE. Initial, flawed studies show equivalent patient outcomes among the professions. If rigorous follow-up studies confirm equivalence, the content and length of medical education for primary care physicians should be reconsidered. Unmatched medical school graduates, with 7 years of training and 65 weeks of SCE, more than the required minimum for NPs, deserve to practice independently. So do PAs. If equivalence is not confirmed, the minimum requirements for NPs and/or PAs should be raised, including considering a required residency (currently optional). Alternatively, the scope of practice for the three professions could be defined to reflect differences in training. There is an urgent need to set aside preconceived notions and turf battles, conduct rigorous independent studies, and generate meaningful data on practice patterns and patient outcomes. This should inform optimal training, scope of practice, and workforce development for each invaluable primary care clinical practitioner.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.136 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".