ABSTRACT 147
Bibliographic record
Abstract
Background and aims: To advance child and family-centred care, the CCU participated in the implementation of a hospital-wide initiative promoting family presence at nursing shift handover. Aims: We will describe the process and outcomes of work completed to prepare the clinical team to implement this new practice. Methods: Multiple strategies were utilized for implementation. Focus groups were held to explore needs related to the practice change. Informal practice development sessions promoted nurse engagement and unit champions were established. Member checking was completed and an implementation toolkit was designed. Nurses were oriented via interactive education meetings, practice simulation and self-learning products. Supportive literature was made available via technology-enabled platforms. Throughout, point of care support was offered by the champions and the leadership team. Nurse impact surveys at baseline and 6 weeks post-implementation are planned. Surveys use scales and open responses to explore key aspects of the new practice. Time studies will be carried out and compliance auditing with feedback will be completed at regular intervals. Results: Implementation of the practice change is expected to be completed in February 2014. Thus, results of surveys, work flow alterations along with unforeseen impacts will be reported thereafter. Conclusions: These findings are expected to guide future uptake of the practice across the hospital, and have positive impacts on child and family-centered care outcomes including; optimal health, patient safety, health equity, patient experience and provider satisfaction.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.617 | 0.417 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".