Surgical waitlist management: Perspectives from surgeons on surgical prioritization at a paediatric hospital
Bibliographic record
Abstract
Globally exacerbated surgical waitlists have provided the opportunity to reflect on prioritization and resource allocation decisions. The unique circumstances of paediatric surgery and consequences of surgical delay prompted the study reported in this paper. As part of a larger project to attend to prioritization in our surgical waitlists, we conducted a Quality Improvement study, the purpose of which is to understand surgeon's perspectives regarding the ethical and practical realities of surgical prioritization at our institution. The study comprises semi-structured interviews with nine full-time paediatric surgeons from a variety of subspecialties conducted at our institution, which is a tertiary paediatric hospital with ten surgical subspecialties in a publicly funded healthcare system. Participants articulated how they prioritize their waitlists, and how they understand ethical prioritization. These findings resonate with the growing public concern for ethical practice in healthcare delivery and transparency in prioritization and resource allocation practices. Specifically, more transparency, consistency, and support is required in prioritization practices. This work highlights the importance of institutional dialogue regarding surgical case prioritization. Because quality improvement work is necessarily site-specific, concrete generalizations cannot be offered. However, the insights gleaned from these interviews and the process by which they were gleaned are a valuable knowledge-sharing resource for any institution that is interested in ongoing quality improvement work. The objectives here were to clarify the goals of prioritization within the institution, improve prioritization practices, and make them more ethical and transparent.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 teacher head, 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".