The role of nurse practitioners in health sector reform in Iran (2011).
Bibliographic record
Abstract
BACKGROUND: Most countries use educated nurses called "nurse practitioners" (NPs) besides the family physicians for diagnosis, treatment, and specifically health education of the family. The main goal of this study was to redefine the role of NPs for better use of their capabilities in the so-called "family physician reform" in Iran. MATERIALS AND METHODS: This is a qualitative and comparative study carried out in three stages (triangulation method) in 2011. In the first stage, we conducted a literature review to design a conceptual framework. The second stage was a comparative study on four countries. In this study, we focused on the role of NPs, which in turn helped to redefine this role in the health sector reform of Iran. In the third stage, two expert panels were involved and the suggested roles were confirmed. RESULTS: In the United States, NPs are licensed by the state in which they practice and have a national board certification. In Canada, nurses involved in clinics should participate in specific training course of diagnosis and management of health care after registration. In Austria, nurses in Nursing homes and maternity do some of the medical procedures under the supervision of the physicians. In the United Kingdom, NPs increasingly substitute for GPs in the care of minor illness and routine management of chronic diseases. CONCLUSIONS: There is still debate in nursing and medical circles about what the focus of the NP roles should be. In Iran, whereas a noticeable reform toward "family physician" is ongoing, redefining the nurses' role is essential. They can perform more active roles in associating with GPs in the clinics of family physicians, both in urban and rural areas, even with higher degrees of autonomy.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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 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".