Ambient Independence Measures for Guiding Care Transitions

指导护理过渡的环境独立措施

• 批准号: 9251721
• 负责人: JEFFREY A KAYE
• 金额: $ 49.59万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-06-01 至 2019-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9251721
• 关键词: Acute; Address; Adult; Age; Aging; Algorithms; American; Appointment; Assisted Living Facilities; Behavior; Behavioral; Body Weight Changes; Caregivers; Caring; Chronic; Chronic Disease; Clinic; Clinical; Clinical Research; Clinical Trials; Cognitive; Collection; Communities; Data; Decision Making; Dementia; Deterioration; Devices; Disease; Early Diagnosis; Early Intervention; Early identification; Elderly; Environment; Event; Family; Friends; Goals; Health; Health Care Costs; Home environment; Homes for the Aged; Independent Living; Individual; Information Systems; Intervention; Knowledge; Life; Long-Term Care; Longitudinal Studies; Measures; Methodology; Methods; Modeling; Monitor; Morbidity - disease rate; Motion; Motor; Nursing Homes; Outcome; Pattern; Performance; Persons; Pharmaceutical Preparations; Phonation; Physiological; Population; Provider; Psyche structure; Quality of life; Randomized; Reporting; Research; Research Methodology; Resource Sharing; Risk; Services; Sleep; Socialization; Stress; Syndrome; System; Technology; Telephone; Testing; Time; United States; Weight; Wireless Technology; Woman; Work; aging population; base; care recipients; caregiving; clinically significant; community setting; cost; disability; economic value; follow-up; forgetting; frailty; improved; informal care; medication compliance; patient home care; prevent; public health relevance; residence; sensor; social engagement; tool; trend; walking speed

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.

描述（由申请人提供）：我们迅速衰老的人口将导致越来越多的人通过痴呆症，脆弱和其他衰老综合症患独立性丧失的风险。预计到2030年，有20％以上的美国人口将超过65岁，其中许多人将无法独立生活，预计将在2030年飙升，以协助抚养老年人，预计为抚养老年人提供的高昂费用。可以通过帮助个人保持独立和在家中尽可能长时间地独立并在家中避免这种费用。这本身就是一个重要的目标，因为人们普遍认为，可以留在自己家中的人们的生活质量更高。我们研究的长期目标是开发系统，以提高我们由于慢性疾病和衰老而无效监测重要健康变化的能力，从而及时干预以防止可避免的健康恶化或失去独立性。已经提出，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措施，以最大程度地减少发病率和成本。但是，此类技术的影响尚不清楚，并且未经测试的假设将使老年人保持独立。拟议的项目将评估此类技术如何为护理过渡干预做出贡献。我们将专门研究流动性，睡眠，药物使用，体重变化和社交参与度的实时模式，以确定可能表明维持独立性能力的趋势。使用过去五年来我们在数百名老年人家中开发和测试的技术，我们将确定使用这种环境独立性措施（AIMS）是否使用了在个人自然生活环境中分发的不引人注目的传感器收集的，有助于对过渡到不同水平的护理进行决策。我们的具体目的是：1）开发新的算法（结合行为和生理数据），以确定目的数据中的趋势，这些数据表明急性或慢性变化可能会损害独立性并进行分析以确定哪些目标数据对护理过渡专业人员最有价值； 2）开发一个自动化系统，以呈现目标，以便以供应的基础来照顾团队，从而预警对临床随访的需求进行了预警。作为此目标的一部分，我们将创建一个可共享的资源，以促进目标和相关技术的使用，从而使其他人可以在其研究或护理环境中使用这种方法； 3）通过确定使用目标数据是否有助于护理人员做出有关从独立生活到更高护理水平的过渡并改变这些决定的结果的决定，从而验证了高级社区环境中的目标指标。