Protected 911: Development, Implementation, and Evaluation of a Pre-hospital COVID-19 High-Risk Response Team
Bibliographic record
Abstract
Patients with COVID-19 who require aerosol-generating medical procedures (such as endotracheal intubation) are challenging for paramedic services. Although potentially lifesaving for patients, aerosolizing procedures carry an increased risk of infection for paramedics, owing to the resource limitations and complexities of the pre-hospital setting. In this paper, we describe the development, implementation, and evaluation of a novel pre-hospital COVID-19 High-Risk Response Team (HRRT) in Peel Region, in Ontario, Canada. The mandate of the HRRT was to attend calls for patients likely to require aerosolizing procedures, with the twofold goal of mitigating against COVID-19 infections in the service while continuing to provide skilled resuscitative care to patients. Modelled after in-hospital ‘protected code blue’ teams, operationalizing the HRRT required several significant changes to standard paramedic practice, including the use of a 3-person crew configuration, dedicated safety officer, call-response checklists, multiple redundant safety procedures, and enhanced personal protective equipment. Less than three weeks after the mandate was given, the HRRT was operational for a 12-week period during the first wave of COVID-19 in Ontario. HRRT members attended ~70% of calls requiring high risk procedures and was associated with improved quality of care indicators. No paramedics in the service contracted COVID-19 during the program.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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; 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".