Healthcare providers’ perceptions of a situational awareness display for emergency department resuscitation: a simulation qualitative study
Bibliographic record
Abstract
IMPORTANCE: Emergency resuscitation of critically ill patients can challenge team communication and situational awareness. Tools facilitating team performance may enhance patient safety. OBJECTIVES: To determine resuscitation team members' perceptions of the Situational Awareness Display's utility. DESIGN: We conducted focus groups with healthcare providers during Situational Awareness Display development. After simulations assessing the display, we conducted debriefs with participants. SETTING: Dual site tertiary care level 1 trauma centre in Ottawa, Canada. PARTICIPANTS: We recruited by email physicians, nurses and respiratory therapist. INTERVENTION: Situational Awareness Display, a visual cognitive aid that provides key clinical information to enhance resuscitation team communication and situational awareness. MAIN OUTCOMES AND MEASURES: Themes emerging from focus groups and simulation debriefs. Three reviewers independently coded and analysed transcripts using content qualitative analysis. RESULTS: We recruited a total of 33 participants in two focus groups (n = 20) and six simulation debriefs with three 4-5 member teams (n = 13). Majority of participants (10/13) strongly endorsed the Situational Awareness Display's utility in simulation (very or extremely useful). Focus groups and debrief themes included improved perception of patient data, comprehension of context and ability to project to future decisions. Participants described potentially positive and negative impacts on patient safety and positive impacts on provider performance and team communication. Participants expressed a need for easy data entry incorporated into clinical workflow and training on how to use the display. CONCLUSION: Emergency resuscitation team participants felt the Situational Awareness Display has potential to improve provider performance, team communication and situational awareness, ultimately enhancing quality of care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".