Ambient Independence Measures for Guiding Care Transitions

描述(申请人提供)：我们快速老龄化的人口将导致越来越多的人因痴呆症、虚弱和其他衰老症状而失去独立性。预计到2030年，帮助赡养老人的高昂医疗费用将飙升，届时美国将有超过20%的人口超过65岁，其中许多人将无法独立生活。通过帮助个人尽可能长时间地保持独立和呆在家里，可以避免其中的一些成本。这本身就是一个重要的目标，因为人们普遍认为，能够留在自己家里的人的生活质量更高。我们研究的长期目标是开发系统，提高我们不引人注意地监测由于慢性病和衰老而导致的重要健康变化的能力，允许及时干预，以防止本可避免的健康恶化或丧失独立性。有人提出，不断发展的传感器和其他技术提供了一种早期检测和干预的手段，将发病率和成本降至最低。然而，这些技术的影响还没有得到很好的理解，来自这些系统的数据将使老年人保持独立的假设也未经检验。拟议的项目将评估这些技术如何有助于护理过渡干预。我们将具体检查活动、睡眠、药物使用、体重变化和社交参与的实时模式，以确定可能表明保持独立性的能力受损的趋势。使用我们在过去五年中在数百个老年人之家开发和测试的技术，我们将确定这种使用分布在个人自然生活环境中的不显眼的传感器收集的环境独立性测量(AIMS)是否有助于做出过渡到不同护理水平的决策。我们的具体目标是：1)开发新的算法(结合行为和生理数据)，以识别AIMS数据中的趋势，表明可能危及独立性的急性或慢性变化，并进行分析，以确定哪些AIMS数据对护理过渡专业人员最有价值；2)开发一个根据需要向护理团队提供AIMS数据的自动化系统，提供临床随访需求的早期预警。作为这一目标的一部分，我们将创建一个可共享的资源，促进AIMS和相关技术的使用，允许其他人在他们的研究或护理环境中使用这种方法；以及3)通过确定AIMS数据的使用是否有助于护理者做出从独立生活向更高护理水平过渡的决策并改变这些决策的结果，在老年社区环境中验证AIMS指标。

DESCRIPTION (provided by applicant): Our rapidly aging population will result in an increasing number of people at risk for loss of independence through dementia, frailty and other syndromes of aging. The high cost of health care to assist the dependent elderly is expected to soar by 2030, when over 20% of the U.S. population will be over the age of 65, many of whom will be unable to live independently. Some of this cost can be avoided by helping individuals remain independent and at home for as long as possible. This is an important goal by itself, as it is generally accepted that quality of life is higher for people who can remain in their own homes. The long-term objective of our research is to develop systems that improve our ability to unobtrusively monitor important health changes due to chronic disease and aging, allowing timely intervention to prevent avoidable health deterioration or loss of independence. It has been suggested that evolving sensor and other technologies provide a means of early detection and intervention minimizing morbidity and cost. However, the impact of such technologies is not well understood, and the hypothesis that data from these systems will allow older adults to remain independent is untested. The proposed project will evaluate how such technologies may contribute to care transition interventions. We will specifically examine real time patterns of mobility, sleep, medication use, weight change and social engagement to identify trends that may indicate compromised ability to maintain independence. Using technologies that we have developed and tested over the past five years in hundreds of seniors' homes, we will determine if such Ambient Independence Measures (AIMs), collected using unobtrusive sensors distributed throughout an individual's natural living environment, aid in making decisions about transitions to different levels of care. Our specific aims are: 1) Develop new algorithms (combining behavioral and physiological data) to identify trends in AIMs data that indicate acute or chronic changes that may compromise independence and conduct analyses to determine what AIMs data is of most value to care transition professionals; 2) Develop an automated system for presenting AIMs data to care teams on an as-needed basis, providing an early warning of the need for clinical follow-up. As part of this aim, we will create a shareable resource that facilitates the use of AIMs and related technology, allowing others to use this approach in their research or care-giving settings; and 3) Validate the AIMs metrics in senior community settings by determining if the use of the AIMs data assists caregivers in making decisions about transitions from independent living to higher care levels and changes the outcomes of those decisions.