Menard Heidi E, Castro-Pearson Sandra, Dahle Nate, Edmonds Stephanie W, Kozitza Brandy J, Webb Johanna J, Bryant Ruth A
Courage Kenny Rehabilitation Institute, part of Allina Health, Minneapolis, MN, USA.
Clinical Research Informatics and Analytics, part of Allina Health, Minneapolis, MN, USA.
Rehabil Nurs. 2025 Feb 1;50(1):24-32. doi: 10.1097/RNJ.0000000000000487. Epub 2025 Jan 8.
Many fall risk assessment tools exist. However, few of these fall risk assessment tools have been tested in the acute rehabilitation setting. The purpose of our study was to compare the accuracy of the Hendrich II Fall Risk Model (HIIFRM) and Sunnyview Test Scale in predicting falls. We also identified factors associated with falls in the rehabilitation patient.
In this retrospective cohort study, we extracted electronic health record data from two acute inpatient rehabilitation units and compared the predictive validity of the HIIFRM and the Sunnyview Test Scale.
Our sample included 134 fallers and 1,667 nonfallers. The HIIFRM and the Sunnyview Test Scale had similar predictive performance with area under the receiver operating characteristic curve (AUC) of .62 and .60, respectively.
The HIIFRM and the Sunnyview Test Scale had poor performance (AUC < .70) predicting falls in this acute rehabilitation setting. Using a fall risk assessment tool alone does not consider unique risk factors and makes implementation of individualized prevention interventions challenging. Nurses need a framework to use individualized factors to determine high fall risk. Further research is needed to clarify variables specific to the inpatient rehabilitation population.
Current fall risk assessment tools are inadequate in the inpatient rehabilitation setting; an individualized fall prevention plan is recommended to ensure patient safety.
存在多种跌倒风险评估工具。然而,这些跌倒风险评估工具中很少有在急性康复环境中进行过测试。我们研究的目的是比较亨德里希二世跌倒风险模型(HIIFRM)和桑尼维尤测试量表在预测跌倒方面的准确性。我们还确定了与康复患者跌倒相关的因素。
在这项回顾性队列研究中,我们从两个急性住院康复单元提取了电子健康记录数据,并比较了HIIFRM和桑尼维尤测试量表的预测效度。
我们的样本包括134名跌倒者和1667名未跌倒者。HIIFRM和桑尼维尤测试量表的预测性能相似,受试者操作特征曲线(AUC)下面积分别为0.62和0.60。
在这种急性康复环境中,HIIFRM和桑尼维尤测试量表在预测跌倒方面表现不佳(AUC < 0.70)。仅使用跌倒风险评估工具未考虑独特的风险因素,使得实施个体化预防干预具有挑战性。护士需要一个框架来利用个体化因素确定高跌倒风险。需要进一步研究以阐明住院康复人群特有的变量。
当前的跌倒风险评估工具在住院康复环境中并不充分;建议制定个体化的跌倒预防计划以确保患者安全。