Nursing Quality Indicators in Emergency Nursing
Bibliographic record
Abstract
BACKGROUND: Nursing quality indicators (NQIs) are essential for evaluating and managing care, yet few validated NQIs exist for emergency nursing. The dynamic nature of this field demands specific, validated indicators. PURPOSE: The purpose of this review was to identify NQIs in adult emergency nursing using Donabedian's quality categories (structure, process, outcome) and explore their validation. METHODS: A scoping review was conducted including articles from 2010 to February 2023, using the Cumulative Index to Nursing and Allied Health Literature and Medline (Ovid) databases. RESULTS: Among 936 screened articles, 18 were included, identifying 85 NQIs across structure (n = 14), process (n = 45), and outcome (n = 26) in emergency nursing. However, the validation of these NQIs was limited. CONCLUSIONS: NQIs evaluate emergency nursing quality, primarily in process assessment. Future work should validate the NQIs identified in this review for adult emergency nursing and search for potential new ones.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".