Daniolou Sofia, Rapp Andreas, Haase Celina, Ruppert Alfred, Wittwer Marlene, Scoccia Pappagallo Alessandro, Pandis Nikolaos, Kressig Reto W, Ienca Marcello
Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Clever.Care AG, Basel, Switzerland.
Front Digit Health. 2021 Feb 4;2:602093. doi: 10.3389/fdgth.2020.602093. eCollection 2020.
The widespread adoption of digital health technologies such as smartphone-based mobile applications, wearable activity trackers and Internet of Things systems has rapidly enabled new opportunities for predictive health monitoring. Leveraging digital health tools to track parameters relevant to human health is particularly important for the older segments of the population as old age is associated with and higher care needs. In order to assess the potential of these digital health technologies to improve health outcomes, it is paramount to investigate which digitally measurable parameters can effectively improve health outcomes among the elderly population. Currently, there is a lack of systematic evidence on this topic due to the inherent heterogeneity of the digital health domain and the lack of clinical validation of both novel prototypes and marketed devices. For this reason, the aim of the current study is to synthesize and systematically analyse which digitally measurable data may be effectively collected through digital health devices to improve health outcomes for older people. Using a modified PICO process and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, we provide the results of a systematic review and subsequent meta-analysis of digitally measurable predictors of morbidity, hospitalization, and mortality among older adults aged 65 or older. These findings can inform both technology developers and clinicians involved in the design, development and clinical implementation of digital health technologies for elderly citizens.
诸如基于智能手机的移动应用程序、可穿戴活动追踪器和物联网系统等数字健康技术的广泛采用，迅速为预测性健康监测带来了新机遇。利用数字健康工具来追踪与人类健康相关的参数，对于老年人群体尤为重要，因为老年与更高的护理需求相关。为了评估这些数字健康技术改善健康结果的潜力，调查哪些可数字化测量的参数能够有效改善老年人群的健康结果至关重要。目前，由于数字健康领域固有的异质性以及新型原型和上市设备缺乏临床验证，关于这一主题缺乏系统性证据。因此，本研究的目的是综合并系统分析通过数字健康设备可以有效收集哪些可数字化测量的数据，以改善老年人的健康结果。我们使用经过修改的PICO流程和PRISMA（系统评价和Meta分析的首选报告项目）框架，提供了一项针对65岁及以上老年人中发病率、住院率和死亡率的可数字化测量预测因素的系统评价及后续Meta分析的结果。这些发现可为参与老年公民数字健康技术设计、开发和临床应用的技术开发者和临床医生提供参考。
