A comparative analysis of the STAT taxonomy and T-NOTECHS for assessing trauma team non-technical skills: A secondary analysis using trauma video review
Bibliographic record
Abstract
BACKGROUND: Non-technical skills (NTS), such as leadership, communication and interaction, situational awareness, cooperation and resource management (CRM), and assessment and decision-making, are critical to optimizing team performance and reducing adverse events (AEs) during trauma resuscitations. This study investigates the association between NTS, assessed using the Trauma - NOn-TECHnical Skills (T-NOTECHS) tool, and AEs, classified using the STAT taxonomy. METHODS: This secondary analysis included 30 adult trauma team activations at Parkland Hospital, Dallas, Texas, with inclusion criteria of patients aged >16 years and trauma video recordings available from the Trauma Video Review Repository between January 1, 2019, and January 15, 2022. T-NOTECHS assessed NTS across five domains using a 5-point Likert scale (1 = poor, 5 = excellent). AEs were identified and categorized using the STAT taxonomy. Descriptive statistics summarized T-NOTECHS scores, AEs, and demographic factors. Poisson regression models examined associations between T-NOTECHS scores, AEs, and demographic variables with reported incidence rate ratios (IRRs). Overdispersion was assessed, and Quasi-Poisson and Negative Binomial models were used for robustness when necessary. RESULTS: T-NOTECHS scores ranged from 17 to 25, with a median of 22, indicating high team performance across domains. The total number of AEs ranged from 4 to 29, with a median of 9.5. Poisson regression analysis demonstrated a significant negative association between T-NOTECHS scores and AEs (IRR = 0.89, 95 % CI: 0.84-0.94, p < 0.001), indicating that each one-point increase in T-NOTECHS score was associated with an 11 % reduction in the expected rate of AEs. Age, sex, and Injury Severity Score (ISS) were not significant predictors of T-NOTECHS scores or AEs. Overdispersion assessments supported Poisson regression, with findings robust to Quasi-Poisson and Negative Binomial models. CONCLUSION: Higher non-technical performance, measured by T-NOTECHS, is strongly associated with fewer AEs in trauma resuscitations. These findings underscore the importance of structured training and assessment of NTS to enhance patient safety and team dynamics. Future studies should validate these results in larger datasets and explore interventions to further improve NTS in trauma care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.000 | 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".