Clinicians’ reported use of clinical priority assessment criteria and their attitudes to prioritization for elective surgery: a cross‐sectional survey
Bibliographic record
Abstract
OBJECTIVES: To explore the attitudes of clinicians working in New Zealand publicly funded hospitals towards prioritizing patients for elective surgery, and their reported use of clinical priority assessment criteria (CPAC). DESIGN: A cross-sectional study using a postal questionnaire. The questionnaire drew on themes identified from an earlier qualitative study. Questions were closed and information was sought about perceptions of the need to prioritize patients, effective ways of doing so and the use of CPAC. SETTING: New Zealand. PARTICIPANTS: A national sample of cardiologists, cardiac, general and orthopaedic surgeons, and registrars. RESULTS: Three hundred and thirty-two clinicians responded to the survey (74.1%). Respondents generally agreed that a nationally consistent method of prioritizing patients for surgery was required but felt their clinical judgement was the most effective way of prioritizing patients. Current CPAC were considered to be administrative tools and there was marked variation in their reported use. Consistent use of CPAC using the constructs provided was more likely to be reported by cardiac specialists than general or orthopaedic surgeons. Other features of the hospital system in which surgeons worked also had a major impact on access to elective surgery. CONCLUSIONS: Clinicians recognized the need for a nationally consistent method of prioritizing patients. Although most did not consider current CPAC were effective in achieving this, many felt there was some potential in further development of tools. However, further development is problematic in the absence of objective measures of need and ability to benefit.
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How this classification was reachedexpand
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 | 0.078 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads 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".