Nurse Practitioners in the Emergency Department
Bibliographic record
Abstract
Emergency department (ED) wait times, length of stay, and overcrowding are common issues in developed health care systems in many countries. These ED issues are multifactorial in nature and require further evaluation in an attempt to provide consistent, adequate health care to each patient. Authors in countries, such as Australia and the United Kingdom, have attempted to address the concerns of increasing wait times, length of stay, and overcrowding by establishing nurse practitioners (NPs) into the ED who practice in domains traditionally dominated by physicians. Unfortunately, Canadian health care system leaders lack experience in implementing the unique role of the NP in the ED. In addition, emergency department fast track (FT) models have been studied and operationalized in Australia and the United States to streamline care for less acute patients. However, it is evident from review of the literature that NPs, in the Canadian health care system, are underutilized within FT units. Despite the fact that NPs have been practicing since the 1960s, there remains confusion by the public and even health care professionals about their role, scope of practice, and capabilities. The purpose of this article is to provide a greater understanding of the NP role in Canada with the intent to elucidate current barriers and facilitators to having NPs practice in the ED setting through appraisal of national and international literature sources. The article also illustrates how FT units streamline patient care and are suitable areas for NP practice within the ED. In addition, the authors describe how assessment, implementation, and evaluation of the role of NPs in the ED might be facilitated through the use of a Participatory Evidence-informed Patient-focused Process for Advanced practice nursing role development, implementation, and evaluation (PEPPA framework).
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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 | 0.013 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".