Canadian Emergency Medicine and Critical Care Physician Perspectives on Pandemic Triage in COVID-19
Bibliographic record
Abstract
Abstract Purpose: Local and regional policies to guide the allocation of scarce critical care resources have been developed, but the views of prospective users are not understood. We sought to investigate the perspectives of Canadian acute care physicians towards triaging scarce critical care resources in the COVID-19 pandemic. Methods: We rapidly deployed a brief survey to Canadian emergency and critical care physicians in April 2020 to investigate current attitudes towards triaging scarce critical care resources and identify subsequent areas for improvement. Descriptive and between-group analyses along with thematic coding were used. Results: The survey was completed by 261 acute care physicians. Feelings of anxiety related to the pandemic were common (65%), as well as fears of psychological distress if required to triage scarce resources (77%). Only 49% of respondents felt confident in making resource allocation decisions. Both critical care and emergency physicians favored multidisciplinary teams over single physicians to allocate scarce critical care resources. Critical care physicians were supportive of decision making by teams not involved in patient care (3.4/5 vs 2.9/5 p=0.04), whereas emergency physicians preferred to maintain their involvement in such decisions (3.4/5 vs 4.0/5 p=0.007). Free text responses identified five themes for subsequent action including the need for further guidance on existing triage policies, ethical support in decision making, medico-legal protection, additional tools for therapeutic communications, and healthcare provider psychological support. Conclusion: There is an urgent need for collaboration between policymakers and frontline physicians to develop critical care resource triage policies that wholly consider the diversity of provider perspectives across practice environments.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".