Experiences of healthcare providers with a novel emergency response intubation team during COVID-19
Bibliographic record
Abstract
OBJECTIVES: In the early stages of the COVID-19 pandemic, there were significant concerns about the infectious risks of intubation to healthcare providers. In response, a dedicated emergency response intubation team (ERIT) consisting of anesthesiologists and allied health providers was instituted for our emergency department (ED). Given the high-risk nature of intubations and the new interprofessional team dynamics, we sought to assess health-care provider experiences and potential areas of improvement. METHODS: Surveys were distributed to healthcare providers at the University Health Network, a quaternary healthcare centre in Toronto, Canada, which includes two urban EDs seeing over 128,000 patients per year. Participants included ED physicians and nurses, anesthesiologists, anesthesia assistants, and operating room nurses. The survey included free-text questions. Responses underwent thematic analysis using grounded theory and were independently coded by two authors to generate descriptive themes. Discrepancies were resolved with a third author. Descriptive themes were distilled through an inductive, iterative process until fewer main themes emerged. RESULTS: A total of 178 surveys were collected (68.2% response rate). Of these, 123 (69%) participated in one or more ERIT activations. Positive aspects included increased numbers of staff to assist, increased intubation expertise, improved safety, and good team dynamics within the ERIT team. Challenges included a loss of scope (primarily ED physicians and nurses) and unfamiliar workflows, perceived delays to ERIT team arrival or patient intubation, role confusion, handover concerns, and communication challenges between ED and ERIT teams. Perceived opportunities for improvement included interprofessional training, developing clear guidelines on activation, inter-team role clarification, and guidelines on handover processes post-intubation. CONCLUSIONS: Healthcare providers perceived that a novel interprofessional collaboration for intubations of COVID-19 patients presented both benefits and challenges. Opportunities for improvement centred around interprofessional training, shared decision making between teams, and structured handoff processes.
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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 | 0.003 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".