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. 2021 Feb 4:2:602093.
doi: 10.3389/fdgth.2020.602093. eCollection 2020.

Digital Predictors of Morbidity, Hospitalization, and Mortality Among Older Adults: A Systematic Review and Meta-Analysis

Sofia Daniolou  1 , Andreas Rapp  2 , Celina Haase  3 , Alfred Ruppert  2 , Marlene Wittwer  2 , Alessandro Scoccia Pappagallo  4 , Nikolaos Pandis  5 , Reto W Kressig  6 , Marcello Ienca  1
Affiliations

Digital Predictors of Morbidity, Hospitalization, and Mortality Among Older Adults: A Systematic Review and Meta-Analysis

Sofia Daniolou et al. Front Digit Health. .

Abstract

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 multimorbidity 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.

Keywords: digital health (eHealth); elderly; hospitalization-; meta-analysis; mortality; predictor; systematic (literature) review.

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Conflict of interest statement

ARa, ARu, and MW were employed by Clever.Care AG. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. This study was funded by Innosuisse- Swiss Innovation Agency, Grant Number: 40158.1 INNO-ICT. This funding scheme is purposively designed to facilitate and promote collaboration between academia and private companies.

Figures

Figure 1
Figure 1
Flowchart.
Figure 2
Figure 2
Forest plots for predictors of Mortality.
Figure 3
Figure 3
Forest plots: predictors of Morbidity.
Figure 4
Figure 4
Publication bias for Mortality.
Figure 5
Figure 5
Publication bias for Morbidity.
See this image and copyright information in PMC

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