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评估 interRAI 跌倒临床评估方案、Scott 跌倒风险筛查以及在住宅长期护理中使用的补充跌倒风险评估工具的预测准确性:一项回顾性队列研究。

Evaluation of the Predictive Accuracy of the interRAI Falls Clinical Assessment Protocol, Scott Fall Risk Screen, and a Supplementary Falls Risk Assessment Tool Used in Residential Long-Term Care: A Retrospective Cohort Study.

机构信息

School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario.

出版信息

Can J Aging. 2020 Dec;39(4):521-532. doi: 10.1017/S0714980820000021. Epub 2020 Mar 16.

Abstract

Falls in residential long-term care (LTC) facilities continue to be a leading cause of injury for residents and cost for the health care system. Interdisciplinary clinical teams are responsible for assessing risk levels for their residents and developing appropriate care plans and interventions in response. This study compares the predictive accuracy of three separate fall risk assessment tools: the interRAI Falls Clinical Assessment Protocol (CAP), derived from the LTC Facility (LTCF) or Minimum Data Set (MDS) 2.0 assessments; the Scott Fall Risk Screen; and a modified Fall Risk Tool that was implemented as part of a provincial Fall Reduction Strategy in Nova Scotia. To conduct this retrospective cohort study, secondary data were collected from 1,553 LTC residents with interRAI assessments completed between March 1, 2015 and September 29, 2016, across Nova Scotia and New Brunswick. For each resident, data were collected regarding the three fall risk assessments, along with fall incident data for use in sensitivity, specificity, and logistic regression analyses. This study found that although all three tools had limitations with sensitivity or specificity thresholds, the interRAI Falls CAP delivered the highest accuracy with a c-statistic of 0.673, compared with the Scott Fall Risk Screen at 0.529 and the modified Fall Risk Tool at 0.609. When diseases that have been established to be a risk factor for falls were added to the model, the overall accuracy of the interRAI Falls CAP combined with those covariates increased to 0.749. These results suggest that the best practice guidelines for fall risk assessment be revisited, and that the interRAI Falls CAP could potentially be updated to include certain diseases and controls for optimal predictive ability.

摘要

居住式长期护理(LTC)机构中的跌倒仍然是导致居民受伤和医疗系统成本增加的主要原因。跨学科临床团队负责评估居民的风险水平,并制定相应的护理计划和干预措施。本研究比较了三种独立的跌倒风险评估工具的预测准确性:来自长期护理机构(LTCF)或最低数据集(MDS)2.0 评估的 interRAI 跌倒临床评估协议(CAP);Scott 跌倒风险筛查;以及作为新斯科舍省跌倒减少策略的一部分实施的改良跌倒风险工具。为了进行这项回顾性队列研究,从 2015 年 3 月 1 日至 2016 年 9 月 29 日期间在新斯科舍省和新不伦瑞克省完成 interRAI 评估的 1553 名 LTC 居民中收集了二级数据。对于每位居民,收集了有关三种跌倒风险评估的信息,以及跌倒事件数据,用于进行敏感性、特异性和逻辑回归分析。这项研究发现,尽管所有三种工具在敏感性或特异性阈值方面都存在局限性,但 interRAI 跌倒 CAP 的准确性最高,c 统计量为 0.673,而 Scott 跌倒风险筛查为 0.529,改良跌倒风险工具为 0.609。当添加已知会增加跌倒风险的疾病到模型中时,interRAI 跌倒 CAP 与这些协变量结合的整体准确性增加到 0.749。这些结果表明,应重新审视跌倒风险评估的最佳实践指南,并且 interRAI 跌倒 CAP 可能会更新,以纳入某些疾病和控制措施,以获得最佳预测能力。

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