723 Provincial Burn Mass Casualty Incident Planning: Preliminary Results
Bibliographic record
Abstract
Abstract Introduction Burn mass casualty incident (BMCI) response planning includes involving relevant stakeholders, assessing regional burn care capacity, and addressing the specialized needs of burn patients. An essential component of these processes is an evaluation of existing resources and plans. In this study, a province with three important elements—a singular health authority to plan for, two burn centres, and updated health technology—was selected for evaluation. Aim What are the current policies, protocols, and practices that address a provincial response to a BMCI? Methods In this ethics approved case study, qualitative description methodology was used for data analysis. Data were gathered from documents outlining the health system response to a mass casualty incident from the health system internal emergency response plans. Health care professionals directly involved in the response were recruited for interviews. Participants were recruited from prehospital emergency management services, hospital emergency departments, inpatient burn units, and a provincial patient transport department. Interviews were conducted online, recorded, and transcribed. Qualitative description was used to code common themes across documents and transcripts. Results Thirteen documents and nine participant interviews were included. Only two documents included burn-specific considerations. Current policies and protocols were limited to all-hazards mass casualty incident planning and did not address specialized needs of burn care. Current plans were based on assumptions that all burn patients would be triaged and transported to burn centres and that surge capacity would be adequate to accommodate for increased demands. Prehospital participants (n=3) felt that existing plans would adequately manage a BMCI. Six participants stated the current plans were not sufficient to manage a BMCI. A comprehensive description of the complex health system response to a potential BMCI was obtained. Some major deficiencies identified included a lack of strategies to bolster burn care staffing capacity such as just-in-time training resources for non-burn trained staff or utilization of outpatient burn clinic staff. Considerations for increased operating room and wound care resources were absent. Conclusions Current provincial all hazards response plans are not sufficient to support adequate response to a BMCI and need to be amended to address the specialized needs of burn patients. Strategies for expanding capacity such as care of burn patients at non burn facilities and utilization of outpatient clinics must be integrated into future plans. Applicability of Research to Practice The provincial health authority needs to support BMCI response planning efforts to better address this unique hazard prior to an incident occurring for best patient outcomes.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".