Jung Hyesil, Park Hyeoun-Ae
1 College of Nursing, Seoul National University, South Korea.
West J Nurs Res. 2018 Dec;40(12):1785-1799. doi: 10.1177/0193945918766554. Epub 2018 Mar 24.
Cumulative data on patient fall risk have been compiled in electronic medical records systems, and it is possible to test the validity of fall-risk assessment tools using these data between the times of admission and occurrence of a fall. The Hendrich II Fall Risk Model scores assessed during three time points of hospital stays were extracted and used for testing the predictive validity: (a) upon admission, (b) when the maximum fall-risk score from admission to falling or discharge, and (c) immediately before falling or discharge. Predictive validity was examined using seven predictive indicators. In addition, logistic regression analysis was used to identify factors that significantly affect the occurrence of a fall. Among the different time points, the maximum fall-risk score assessed between admission and falling or discharge showed the best predictive performance. Confusion or disorientation and having a poor ability to rise from a sitting position were significant risk factors for a fall.
患者跌倒风险的累积数据已在电子病历系统中汇总,并且可以利用这些数据在入院时间至跌倒发生期间检验跌倒风险评估工具的有效性。提取住院期间三个时间点评估的亨德里奇二世跌倒风险模型得分,并用于检验预测效度:(a) 入院时,(b) 从入院到跌倒或出院的最大跌倒风险得分时,以及 (c) 跌倒或出院前即刻。使用七个预测指标检验预测效度。此外,采用逻辑回归分析确定显著影响跌倒发生的因素。在不同时间点中,入院至跌倒或出院期间评估的最大跌倒风险得分显示出最佳预测性能。意识模糊或定向障碍以及从坐姿起身能力差是跌倒的显著风险因素。