Kim Son Chae, Kaiser Jennifer, Bulson Julie, Hosford Tracy, Nurski Ashleigh, Sadat Carol, Kalinowski Nicole
School of Nursing Point Loma Nazarene University San Diego California USA.
Nursing Professional Practice and Development Spectrum Health Grand Rapids Michigan USA.
J Am Coll Emerg Physicians Open. 2022 Mar 17;3(2):e12693. doi: 10.1002/emp2.12693. eCollection 2022 Apr.
Violence is a major preventable problem in emergency departments (EDs), and validated screening tools are needed to identify potentially violent patients. We aimed to test the utility of the Aggressive Behavior Risk Assessment Tool (ABRAT) for screening patients in the ED.
A prospective cohort study was conducted among adult and pediatric patients aged ≥10 years visiting 3 emergency departments in Michigan between May 1, 2021, and June 30, 2021. Triage nurses completed the 16-item checklist using electronic health records (EHRs), and the occurrence of violent incidents were collected before ED disposition. A multivariate logistic regression model was applied to select a parsimonious set of items.
Among 10,554 patients, 127 had ≥1 violent incidents (1.2%). The regression model resulted in a 7-item ABRAT for EDs, including history of aggression and mental illness and reason for visit, as well as 4 violent behavior indicators. Receiver operating characteristics analysis showed that the area under the curve was 0.91 (95% confidence interval [CI], 0.87-0.95), with a sensitivity of 84.3% (95% CI, 76.5%-89.9%) and specificity of 95.3% (95% CI, 94.8%-95.7%) at the optimal cutoff score of 1. An alternative cutoff score of 4 for identifying patients at high risk for violence had a sensitivity and specificity of 70.1% and 98.9%, respectively.
The ABRAT for EDs appears to be a simple yet comprehensive checklist with a high sensitivity and specificity for identifying potentially violent patients in EDs. The availability of such a screening checklist in the EHR may allow rapid identification of high-risk patients and implementation of focused mitigation measures to protect emergency staff and patients.
暴力行为是急诊科可预防的主要问题，因此需要经过验证的筛查工具来识别潜在的暴力患者。我们旨在测试攻击行为风险评估工具（ABRAT）在急诊科筛查患者的效用。
对2021年5月1日至2021年6月30日期间在密歇根州3家急诊科就诊的年龄≥10岁的成人和儿科患者进行了一项前瞻性队列研究。分诊护士使用电子健康记录（EHR）完成了16项清单，并在急诊科处置前收集暴力事件的发生情况。应用多变量逻辑回归模型选择一组简洁的项目。
在10554名患者中，127人发生了≥1次暴力事件（1.2%）。回归模型得出了一个适用于急诊科的7项ABRAT，包括攻击史、精神疾病史、就诊原因以及4个暴力行为指标。受试者工作特征分析表明，曲线下面积为0.91（95%置信区间[CI]，0.87 - 0.95），在最佳截断分数为1时，敏感性为84.3%（95%CI，76.5% - 89.9%），特异性为95.3%（95%CI，94.8% - 95.7%）。用于识别暴力高风险患者的另一个截断分数为4时，敏感性和特异性分别为70.1%和98.9%。
急诊科ABRAT似乎是一个简单而全面的清单，对识别急诊科潜在的暴力患者具有较高的敏感性和特异性。电子健康记录中提供这样的筛查清单可能有助于快速识别高风险患者，并实施针对性的缓解措施以保护急诊医护人员和患者。
