Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures
Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures
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DOI：
10.1016/j.jamda.2017.08.001
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发表时间：
2017-11-01
影响因子：
7.6
通讯作者：
Kerse, Ngaire
中科院分区：
文献类型：
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作者：
Klenk, Jochen;Becker, Clemens;Kerse, Ngaire
福尔斯是老年人受伤和残疾的主要原因，导致严重的健康和社会后果，包括骨折、生活质量差、丧失独立性和机构化。为了设计和提供充分的预防措施，准确理解和识别个人跌倒风险非常重要。然而，迄今为止，与估计心血管风险的模型相比，跌倒风险模型的性能较弱。这种缺陷可能由两个因素造成。首先，目前的模型认为风险因素对每个人来说都是稳定的，不会随着时间的推移而变化，这一假设并不反映现实生活中的经验。其次，目前的模型没有考虑个人暴露的相互作用，包括活动类型（例如，步行，进行转移）和环境风险（例如，照明，地板条件），其中进行活动。因此，我们建立了一个动态跌倒风险模型，该模型由随时间和暴露（活动背景）而变化的内在风险因素组成。电子健康传感器技术（例如，智能手机）开始实现对上述两个因素的连续测量。我们用FARSEEING数据库中真实福尔斯的例子来说明我们的模型。这个跌倒风险的动态框架增加了一些重要的方面，可以提高对跌倒机制、跌倒风险模型和跌倒预防干预措施的理解。(C)2017年AMDA -急性后和长期护理医学协会。
Falls are a major cause of injury and disability in older people, leading to serious health and social consequences including fractures, poor quality of life, loss of independence, and institutionalization. To design and provide adequate prevention measures, accurate understanding and identification of person's individual fall risk is important. However, to date, the performance of fall risk models is weak compared with models estimating, for example, cardiovascular risk. This deficiency may result from 2 factors. First, current models consider risk factors to be stable for each person and not change over time, an assumption that does not reflect real-life experience. Second, current models do not consider the interplay of individual exposure including type of activity (eg, walking, undertaking transfers) and environmental risks (eg, lighting, floor conditions) in which activity is performed. Therefore, we posit a dynamic fall risk model consisting of intrinsic risk factors that vary over time and exposure (activity in context). eHealth sensor technology (eg, smartphones) begins to enable the continuous measurement of both the above factors. We illustrate our model with examples of real-world falls from the FARSEEING database. This dynamic framework for fall risk adds important aspects that may improve understanding of fall mechanisms, fall risk models, and the development of fall prevention interventions. (C) 2017 AMDA - The Society for Post-Acute and Long-Term Care Medicine.