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Artificial Intelligence–Powered Digital Health Platform and Wearable Devices Improve Outcomes for Older Adults in Assisted Living Communities: Pilot Intervention Study

机译:人工智能供电的数字健康平台和可穿戴设备改善了辅助生活社区中老年人的结果:试点干预研究

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摘要

BackgroundWearables and artificial intelligence (AI)–powered digital health platforms that utilize machine learning algorithms can autonomously measure a senior’s change in activity and behavior and may be useful tools for proactive interventions that target modifiable risk factors. ObjectiveThe goal of this study was to analyze how a wearable device and AI-powered digital health platform could provide improved health outcomes for older adults in assisted living communities. MethodsData from 490 residents from six assisted living communities were analyzed retrospectively over 24 months. The intervention group (+CP) consisted of 3 communities that utilized CarePredict (n=256), and the control group (–CP) consisted of 3 communities (n=234) that did not utilize CarePredict. The following outcomes were measured and compared to baseline: hospitalization rate, fall rate, length of stay (LOS), and staff response time. ResultsThe residents of the +CP and –CP communities exhibit no statistical difference in age (P=.64), sex (P=.63), and staff service hours per resident (P=.94). The data show that the +CP communities exhibited a 39% lower hospitalization rate (P=.02), a 69% lower fall rate (P=.01), and a 67% greater length of stay (P=.03) than the –CP communities. The staff alert acknowledgment and reach resident times also improved in the +CP communities by 37% (P=.02) and 40% (P=.02), respectively. ConclusionsThe AI-powered digital health platform provides the community staff with actionable information regarding each resident’s activities and behavior, which can be used to identify older adults that are at an increased risk for a health decline. Staff can use this data to intervene much earlier, protecting seniors from conditions that left untreated could result in hospitalization. In summary, the use of wearables and AI-powered digital health platform can contribute to improved health outcomes for seniors in assisted living communities. The accuracy of the system will be further validated in a larger trial.
机译:背景技术和人工智能(AI) - 利用机器学习算法的功率数字健康平台可以自主地衡量高级活动和行为的变化,可能是针对目标可修改的风险因素的主动干预的有用工具。本研究的目标是分析可穿戴设备和AI供电的数字健康平台如何为辅助生活社区的老年人提供改善的健康结果。 Methable从六次辅助生活社区的490名居民进行了回顾性分析了24个月。干预组(+ CP)由3个社区组成,该社区利用了CarePredict(n = 256),对照组(-CP)包括3个群落(n = 234),该社区不利用CAREPREDICT。测量以下结果并与基线进行比较:住院率,跌倒率,逗留时间(LOS)和工作人员答复时间。结果的+ Cp和-CP社区的居民表现出年龄(p = .64)的统计学差异(p = .63),以及每个居民的工作人员服务时间(p = .94)。数据显示,+ CP社区呈现39%的住院率(P = .02),下降率下降69%(P = .01),保持长度为67%(P = .03) -cp社区。员工警告确认和达到居民在+ CP社区中的提高37%(p = .02)和40%(p = .02)。 ConclusionsThe AI供电的数字健康平台提供了社区工作人员提供关于每个居民的活动和行为可操作的信息,可用于识别老年人是在一个健康下降的风险增加。工作人员可以使用此数据更早地介入,保护老年人免受未经治疗的条件可能导致住院治疗。总之,使用可穿戴物和AI供电的数字健康平台可以有助于提高辅助生活社区中老年人的健康结果。系统的准确性将在更大的试验中进一步验证。

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