Failure to rescue as a nurse-sensitive indicator
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PROBLEM: The aim of this concept analysis was to clarify failure to rescure as a nurse-sensitive indicator. Although the concept of failure to rescue as a nurse-sensitive outcome has appeared in the nursing literature for over a decade, conceptual clarity is needed to address its variable and ambiguous use in health care. METHODS: Walker and Avant's eight-stage method of concept analysis was used to explore the concept of failure to rescue in nursing practice. Twenty-one papers were retrieved from Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE databases and selected for review and synthesis. RESULTS: Failure to rescue as a nurse-sensitive indicator was found to be a "failing to rescue" process characterized by a cascade of events, including four key attributes: (1) errors of omission in care, (2) failure to recognize changes in patient condition, (3) failure to communicate changes, and (4) failures in clinical decision making. CONCLUSIONS: Nurses have a pivotal role in "failing to rescue" through early recognition, escalation, and intervention of subtle changes signaling complications. Upstream strategies, such as the use of early warning sign indicators, structured communication, and teamwork, shift the discourse from failure to rescue, to processes in nursing practice of good catch events.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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 it