Indicators for Evaluating the Performance and Quality of Care of Ambulatory Care Nurses
Bibliographic record
Abstract
The quality and safety of nursing care vary from one service to another. We have only very limited information on the quality and safety of nursing care in outpatient settings, an expanding area of practice. Our aim in this study was to make available, from the scientific literature, indicators potentially sensitive to nursing that can be used to evaluate the performance of nursing care in outpatient settings and to integrate those indicators into the theoretical framework of Dubois et al. (2013). We conducted a scoping review in three databases (CINAHL, MEDLINE, and EMBASE) and the bibliographies of selected articles. From a total of 116 articles, we selected 22. The results of our study not only enable that framework to be extended to ambulatory nursing care but also enhance it with the addition of five new indicators. Our work offers nurses and managers in ambulatory nursing units indicators potentially sensitive to nursing that can be used to evaluate performance. For researchers, it presents the current state of knowledge on this construct and a framework with theoretical foundations for future research in ambulatory settings. This work opens an unexplored field for further research.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".