Explore the potential of having Physician Assistants (PAs) working in critical care in Manitoba – A literature review
Bibliographic record
Abstract
Intro: Critical care medical staffing has been an emerging issue due to the change in the IPS standard and the ACGME resident duty hour restrictions. Currently, no PAs is working in Manitoba's critical care. Due to the health care system transformation, implementing PAs to critical care is a possible solution to achieve financial sustainability for Manitoba health care. Methods: Articles evaluated for this literature review were collected using Scopus and PubMed with searching keywords mainly include "physician assistant", “intensive care”, "critical care" and "cost-effectiveness". Results: 143 articles were found through the searching engine, of which 9 articles were identified relevant to PAs effects in critical care, 7 articles were relevant to PAs cost effectiveness. Conclusion: Based on the review, PAs are proven to be safe and adequate in providing patient care in critical care compared to other traditional providers. PAs are economically efficient in many medicine subspecialties and in-direct data is supporting PA's cost effectiveness in ICU. Thus, implementing PAs into critical care in Manitoba could positively contribute to critical care staffing in the midst of the provincial health care system transformation.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".