Staff perceptions of the implementation of a trauma video review program at a level I trauma center
Bibliographic record
Abstract
OBJECTIVES: Successful implementation of any new technology requires extensive engagement with front-line staff. We explored the perceptions of emergency department and trauma staff about a trauma video review program (TVR) prior to implementation of the first such program in Canada at our level I trauma center. METHODS: We conducted semi-structured individual interviews and in situ small group interviews with 35 multidisciplinary ED and trauma staff members of a teaching and research hospital in Toronto, Canada. We sought maximum variation in the sample of purposively selected participants. Interviews were recorded with audiotapes or detailed field notes, transcribed verbatim, coded, and analyzed using standard thematic analysis techniques. RESULTS: Participants expressed overall support for the concept of TVR, but there is a core sense of unease that influenced overall staff perceptions. Despite several departmental presentations, very few participants actually had a solid understanding of how the TVR worked. Many were apprehensive about their own professional privacy, deeply concerned about vulnerable patients being filmed without consent, and questioned how video data would be used. Despite significant hesitancy, ED and trauma staff identified positive opportunities that TVR could bring, including providing an evidence base for quality improvement. CONCLUSIONS: TVR is an evolving approach to evaluate quality and patient safety in the trauma bay. As such it brings with it natural concerns and apprehension from staff regarding privacy, confidentiality, and how data will be captured and used. There is opportunity for these types of concerns to be addressed with a robust knowledge translation plan and engagement of staff throughout the implementation process.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".