Role of Human Factor and Non Technical Skills in Anaesthetic Nursing Practice: A Case Study
Bibliographic record
Abstract
The role of the anaesthetic nurse specialist is about change and adaptation, consisting of many skills including educator, advisor, change agent and innovator.Expertise, knowledge and skills acquired, range not only from years of experience, but now through a more formal educational specialist pathway at graduate level.The anaesthetic specialized role is to enhance patient outcomes and experience by delivering individually tailored care in the Perioperative phase.The need to improve the quality of patient care and reform the NHS into an organization fit for the future has been the focus of many debates in national government, but in the end, it all comes down to efficacy.Effectiveness, value for money and productivity are the drivers in the development of many new specialized roles, especially in the Perioperative environment.Staff development and education is vital, nevertheless, in these current times of budget cuts and austerity measures continuing professional development can be sacrificed.Therefore as a specialist practice nurses, we must be innovative in finding ways in improving our practice and developing our knowledge and skills.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".