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用ROC曲线分析验证亨德里希二号跌风险模型对住院患者的准确性
Chieh-Ying Hu1, Li-Chen Sun2, Ming-Yen Lin3
1Integrated Long-Term Care Services Center, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
The Kaohsiung journal of medical sciences
|February 17, 2024
概括
亨德里希二世跌倒风险模型 (HIIFRM) 在预测患者在标准值下跌的准确性有限. 较低的截止分数 (≥2) 显著提高了其对跌倒风险评估的辨别能力.
科学领域:
- 临床护理 临床护理
- 患者安全 患者安全
- 医疗保健风险管理 医疗保健风险管理
背景情况:
- 患者跌倒是医疗保健机构的一个重大问题,导致发病率和医疗保健成本增加.
- 准确的跌倒风险评估工具对于实施有效的预防策略至关重要.
- 亨德里希二世跌倒风险模型 (HIIFRM) 被广泛使用,但其预测准确性需要持续评估.
研究的目的:
- 评估亨德里希二世跌倒风险模型 (HIIFRM) 在台湾医疗中心预测跌倒的准确性.
- 确定HIIFRM的最佳切断点,以提高其预测性能.
- 分析HIIFRM分数在不同医院单位的分布.
主要方法:
- 追溯性研究分析电子病历和患者安全数据.
- 包括303个落事件和47,146个非落事件.
- 接收器操作特征 (ROC) 曲线分析,以评估各种HIIFRM截止分数的灵敏度,特异性和曲线下的面积 (AUC).
主要成果:
- 标准HIIFRM切线 (≥5) 显示在落体组中,中位数得分较高,但区分能力有限 (AUC=0.57).
- 内部医学,外科和瘤病房的HIIFRM分数≥5.5的流行率最高.
- 较低的HIIFRM切线分数 (≥2) 显示了可接受的区分能力 (AUC=0.75),识别了额外的跌倒事件.
结论:
- 标准的HIIFRM截止分数可能不是最佳的在这个人群下降预测.
- 调整HIIFRM截止分数可以显著提高其在识别患有跌倒风险的患者的准确性.
- 优化落风险评估工具对于提高患者安全和制定有针对性的预防策略至关重要.
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