Role of the advanced nurse practitioner within the vascular team: A qualitative study of vascular physicians and nurses
Bibliographic record
Abstract
Objective: To assess the perception of Advanced Nurse Practitioners (ANP) by physicians and nurses in vascular medicine. As the status of ANP in France was recently enacted by law in 2018, we aimed to investigate physicians and nurses working with patients suffering from Peripheral Artery Disease (PAD) to gather their opinions and draw the cooperation outlines these practitioners could have with an ANP. Methods: A qualitative study based on in-depth interviews was conducted among healthcare practitioners taking care of patients with PAD: 10 physicians working either in a private practice settings or hospital settings or both, and eight nurses working within a hospital inpatients vascular unit. Verbatim responses were extracted and coded according to a continuous thematization method. Results: Three main features emerged from participants' responses. Vascular medicine has a specific organization with a significant lack of time and staff to fulfill the mission regarding patients' severity of illness. Second, the ANP is wanted to fill part of this gap. The expected benefits include a smoother care pathway and increased capacity for cardiovascular education and prevention, especially during consultations. Lastly, some clarification is required to integrate such new practitioners within vascular teams already in place. Conclusion: Advanced nurse practitioners could be the missing link in a "Vascular team" by creating a continuum in the care of patients with PAD, ensuring clinical assessment, nursing supervision, adverse event screening, and renewing drug prescriptions with the required adaptations while ensuring essential part of therapeutic education adapted to each patient.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".