Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, London, UK.
Department of Bioengineering, Imperial College London, London, UK.
BMC Geriatr. 2024 Sep 30;24(1):796. doi: 10.1186/s12877-024-05397-0.
Home monitoring systems utilising artificial intelligence hold promise for digitally enhanced healthcare in older adults. Their real-world use will depend on acceptability to the end user i.e. older adults and caregivers. We explored the experiences of adults over the age of 60 and their social and care networks with a home monitoring system installed on hospital discharge after sustaining a moderate/severe Traumatic Brain Injury (TBI), a growing public health concern.
A qualitative descriptive approach was taken to explore experiential data from older adults and their caregivers as part of a feasibility study. Semi-structured interviews were conducted with 6 patients and 6 caregivers (N = 12) at 6-month study exit. Data were analysed using Framework analysis. Potential factors affecting acceptability and barriers and facilitators to the use of home monitoring in clinical care and research were examined.
Home monitoring was acceptable to older adults with TBI and their caregivers. Facilitators to the use of home monitoring were perceived need for greater support after hospital discharge, the absence of sound and video recording, and the peace of mind provided to care providers. Potential barriers to adoption were reliability, lack of confidence in technology and uncertainty at how data would be acted upon to improve safety at home.
Remote monitoring approaches are likely to be acceptable, especially if patients and caregivers see direct benefit to their care. We identified key barriers and facilitators to the use of home monitoring in older adults who had sustained TBI, which can inform the development of home monitoring for research and clinical use. For sustained use in this demographic the technology should be developed in conjunction with older adults and their social and care networks.
利用人工智能的家庭监测系统有望为老年人的数字化增强医疗保健提供支持。它们在现实世界中的使用将取决于最终用户（即老年人及其护理人员）的可接受程度。我们研究了在因中度/重度创伤性脑损伤（TBI）出院后安装家庭监测系统的 60 岁以上成年人及其社会和护理网络的体验，这是一个日益受到关注的公共卫生问题。
为了探索老年人及其护理人员的经验数据，我们采用了定性描述方法，这是一项可行性研究的一部分。在研究结束时，对 6 名患者和 6 名护理人员（N=12）进行了半结构化访谈。使用框架分析对数据进行了分析。研究了影响家庭监测在临床护理和研究中可接受性的潜在因素，以及使用家庭监测的障碍和促进因素。
家庭监测得到了 TBI 老年患者及其护理人员的认可。家庭监测使用的促进因素是患者在出院后需要更多支持，监测系统没有声音和视频记录，以及为护理人员提供的安心感。采用家庭监测的潜在障碍是可靠性、对技术缺乏信心以及对如何利用数据来提高家庭安全的不确定性。
远程监测方法可能是可以接受的，特别是如果患者和护理人员认为这对他们的护理有直接好处。我们确定了在 TBI 患者中使用家庭监测的关键障碍和促进因素，这可以为家庭监测的研究和临床应用提供信息。对于在这一年龄段的持续使用，该技术应与老年人及其社会和护理网络共同开发。
