A comparative analysis of the STAT taxonomy and T-NOTECHS for assessing trauma team non-technical skills: A secondary analysis using trauma video review.

Anisa Nazir, Eliane M Shore, Ryan P Dumas, Caitlin Fitzgerald, Melissa McGowan, Charles Keown-Stoneman, Teodor Grantcharov, Brodie Nolan
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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.

STAT分类和T-NOTECHS用于评估创伤小组非技术技能的比较分析:使用创伤视频回顾的二次分析。
背景:非技术技能(NTS),如领导力、沟通和互动、态势感知、合作和资源管理(CRM)以及评估和决策,对于优化团队绩效和减少创伤复苏期间的不良事件(ae)至关重要。本研究调查了使用创伤-非技术技能(T-NOTECHS)工具评估的NTS与使用STAT分类法分类的ae之间的关系。方法:该二次分析包括德克萨斯州达拉斯帕克兰医院的30个成人创伤小组的激活,纳入标准为年龄在bb0 - 16岁之间的患者和创伤视频回顾库中2019年1月1日至2022年1月15日的创伤视频记录。T-NOTECHS使用5分李克特量表(1 =差,5 =优)评估5个领域的NTS。使用STAT分类法对ae进行识别和分类。描述性统计总结了T-NOTECHS评分、ae和人口统计学因素。泊松回归模型检验了T-NOTECHS评分、ae和人口统计学变量与报告发病率比(IRRs)之间的关系。评估过度分散,必要时使用准泊松和负二项模型来保证稳健性。结果:T-NOTECHS得分范围从17到25,中位数为22,表明跨领域的高团队绩效。ae的总数为4 ~ 29,中位数为9.5。泊松回归分析显示T-NOTECHS评分与ae之间呈显著负相关(IRR = 0.89, 95% CI: 0.84-0.94, p < 0.001),表明T-NOTECHS评分每增加1分,预期ae发生率降低11%。年龄、性别和损伤严重程度评分(ISS)不是T-NOTECHS评分或ae的显著预测因子。过度分散评估支持泊松回归,结果对准泊松和负二项模型具有鲁棒性。结论:由T-NOTECHS测量的较高的非技术性能与创伤复苏中较少的ae密切相关。这些发现强调了对NTS进行结构化培训和评估以提高患者安全和团队动力的重要性。未来的研究应该在更大的数据集中验证这些结果,并探索进一步改善创伤护理中NTS的干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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