Using an e-Delphi technique in achieving consensus across disciplines for developing best practice in day surgery in Ireland
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
Background: The benefits of day surgery are supported internationally by the provision of standards. However, standards from one health jurisdiction are not readily transferable to others as national health strategy, policy and funding are influencing factors. Objective: To determine, through consensus from experts in day surgery, a list of best practice statements for day surgery in Ireland. Methods: A three round e-Delphi technique. Professionals in surgery, anaesthesia, nursing and management involved in day surgery across all hospitals in Ireland were invited to participate as the expert panel. In round 1 a list of proposals for best practice were obtained from panel members. In round 2 experts were asked to rank each statement according to their importance on a nine point scale (1 = not important, 9 = high importance) using an online questionnaire. Consensus was set at 70%, meaning the items that 70% of people deemed to be important were carried over to round 3. A repeat online questionnaire was conducted with the remaining statements in round 3. Results: Round 1 provided 261 statements. These were grouped and reduced to 62 statements for ranking. Following the iterative process over the subsequent two rounds a final list of 40 statements were developed and grouped into six thematic areas. Conclusion: By using an e-Delphi process of gaining consensus among experts working in day surgical services, a list of best practice statements were developed.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it