未经评估:在SARS-CoV2大流行期间,远程医疗和家庭护理选择显着扩展。复杂的,现在存在支持家庭护理的远程监控技术。智能家居健康监测研究的进展表明,这些技术能够近乎实时地识别和预测健康变化。然而,很少有护士对这项技术足够熟悉,可以使用智能家居来优化患者护理或将他们的触角扩展到医疗保健接触点之间的家庭。
UNASSIGNED:这项工作的目的是探索护士与智能家居之间的伙伴关系,以实现对患者健康的自动远程监控和评估。我们介绍了一系列健康事件案例,以展示如何利用这种伙伴关系来有效检测和报告可由智能家居自动检测的临床相关健康事件。
UNASSIGNED:25名具有多种慢性健康状况的参与者。
UNASSIGNED:在25名患有多种慢性健康状况的参与者的家中安装了环境传感器。Motion,光,温度,和门的使用数据是连续收集的参与者\'家。健康事件和参与者相关行为的描述是通过每周与研究参与者进行的护理远程健康访问捕获的,并用于分析代表健康事件的传感器数据。2例充血性心力衰竭恶化的参与者,一例尿路感染,两例肠道炎症发作,研究了4例睡眠中断的参与者。
未经评估:对于每种情况,临床相关的健康事件与来自参与者家中安装的传感器的行为数据模式的基线变化相一致.在某些情况下,检测到的事件是由可用于预测事件的其他行为模式引发的。
UNASSIGNED:我们在本案例系列中发现了证据,表明在家庭环境中对患者行为进行连续的基于传感器的监测可能用于提供对健康事件的自动检测。对智能家居传感器数据的护理见解可用于启动预防策略并提供及时的干预。
UNASSIGNED:与智能家居合作的护士可以发现家中健康状况的恶化,从而进行早期干预。
UNASSIGNED: Telehealth and home-based care options significantly expanded during the SARS-CoV2 pandemic. Sophisticated, remote monitoring technologies now exist that support at-home care. Advances in the research of smart homes for health monitoring have shown these technologies are capable of recognizing and predicting health changes in near-real time. However, few nurses are familiar enough with this technology to use smart homes for optimizing patient care or expanding their reach into the home between healthcare touch points.
UNASSIGNED: The objective of this work is to explore a partnership between nurses and smart homes for automated remote monitoring and assessing of patient health. We present a series of health event cases to demonstrate how this partnership may be harnessed to effectively detect and report on clinically relevant health events that can be automatically detected by smart homes.
UNASSIGNED: 25 participants with multiple chronic health conditions.
UNASSIGNED: Ambient sensors were installed in the homes of 25 participants with multiple chronic health conditions. Motion, light, temperature, and door usage data were continuously collected from participants\' homes. Descriptions of health events and participants\' associated behaviors were captured via weekly nursing telehealth visits with study participants and used to analyze sensor data representing health events. Two cases of participants with congestive heart failure exacerbations, one
case of urinary tract infection, two cases of bowel inflammation flares, and four cases of participants with sleep interruption were explored.
UNASSIGNED: For each
case, clinically relevant health events aligned with changes from baseline in behavior data patterns derived from sensors installed in the participant\'s home. In some cases, the detected event was precipitated by additional behavior patterns that could be used to predict the event.
UNASSIGNED: We found evidence in this
case series that continuous sensor-based monitoring of patient behavior in home settings may be used to provide automated detection of health events. Nursing insights into smart home sensor data could be used to initiate preventive strategies and provide timely intervention.
UNASSIGNED: Nurses partnered with smart homes could detect exacerbations of health conditions at home leading to early intervention.