A Digital Health Service for Elderly People with Balance Disorders and Risk of Falling: A Design Science Approach

Digital home care interventions and quality of primary care for older adults: a scoping review

BACKGROUND

Population aging is forcing the transformation of health care. Long-term care in the home is complex and involves complex communication with primary care services. In this scenario, the expansion of digital health has the potential to improve access to home-based primary care; however, the use of technologies can increase inequalities in access to health for an important part of the population. The aim of this study was to identify and map the uses and types of digital health interventions and their impacts on the quality of home-based primary care for older adults.

METHODS

This is a broad and systematized scoping review with rigorous synthesis of knowledge directed by the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The quantitative data were analyzed through descriptive statistics, and the qualitative data were analyzed through basic qualitative content analysis, considering the organizational, relational, interpersonal and technical dimensions of care. The preliminary results were subjected to consultation with stakeholders to identify strengths and limitations, as well as potential forms of socialization.

RESULTS

The mapping showed the distribution of publications in 18 countries and in the Sub-Saharan Africa region. Older adults have benefited from the use of different digital health strategies; however, this review also addresses limitations and challenges, such as the need for digital literacy and technological infrastructure. In addition to the impacts of technologies on the quality of health care.

CONCLUSIONS

The review gathered priority themes for the equitable implementation of digital health, such as access to home caregivers and digital tools, importance of digital literacy and involvement of patients and their caregivers in health decisions and design of technologies, which must be prioritized to overcome limitations and challenges, focusing on improving quality of life, shorter hospitalization time and autonomy of older adults.

Global scientific trends in healthy aging in the early 21st century: A data-driven scientometric and visualized analysis

Background

According to the World Health Organization (WHO), healthy aging is the process of developing and maintaining the functional capacity for health in old age. A rapidly growing number of research studies on healthy aging have been conducted worldwide. The purpose of this research work is to explore global scientific landscape of healthy aging research over the last 22 years.

Methods

Scientific publications on healthy aging from January 1, 2000 to October 11, 2022 were retrieved from the Web of Science Core Collection (WoSCC) on October 11, 2022. A total of 6420 publications were included in the scientometric analysis. VOSviewer (1.6.18) was used to conduct scientometric and visualized analysis.

Results

The publication growth rate was 35.68 from 2000 to 2021. The United States of America (USA) led in both productivity and citations. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA was prominent in terms of both the highest citation count and the highest average citation count. The National Institute on Aging (NIA) and Evans, Michele K. were the most influential organization and author, respectively. Research hotspots in healthy aging were identified based on the co-occurrence analysis of keywords: (1) physical activity and mental health of older adults; (2) diseases impacting the health and lifespan of older adults; and (3) neuroscience. Our analysis indicates that gut microbiota, loneliness, frailty, mitochondria and resilience were the emerging themes in healthy aging research.

Conclusions

The quantity of annual publications on healthy aging has rapidly increased over the past 22 years, especially during 2018-2021. This analysis identified the status, trends, hot topics, and frontiers of healthy aging research. These findings will help researchers quickly understand the global representation of healthy aging research, influence resource dissemination, promote international collaborations, guide policy formulation, and improve health services for older adults.

Healthy Ageing: A Decision-Support Algorithm for the Patient-Specific Assignment of ICT Devices and Services

In response to rapid population ageing, digital technology represents the greatest resource in supporting the implementation of active and healthy ageing principles at clinical and service levels. However, digital information platforms that deliver coordinated health and social care services for older people to cover their needs comprehensively and adequately are still not widespread. The present work is part of a project that focuses on creating a new personalised healthcare and social assistance model to enhance older people's quality of life. This model aims to prevent acute events to favour the elderly staying healthy in their own home while reducing hospitalisations. In this context, the prompt identification of criticalities and vulnerabilities through ICT devices and services is crucial. According to the human-centred care vision, this paper proposes a decision-support algorithm for the automatic and patient-specific assignment of tailored sets of devices and local services based on adults' health and social needs. This decision-support tool, which uses a tree-like model, contains conditional control statements. Using sequences of binary divisions drives the assignation of products and services to each user. Based on many predictive factors of frailty, the algorithm aims to be efficient and time-effective. This goal is achieved by adequately combining specific features, thresholds, and constraints related to the ICT devices and patients' characteristics. The validation was carried out on 50 participants. To test the algorithm, its output was compared to clinicians' decisions during the multidimensional evaluation. The algorithm reported a high sensitivity (96% for fall monitoring and 93% for cardiac tracking) and a lower specificity (60% for fall monitoring and 27% for cardiac monitoring). Results highlight the preventive and protective behaviour of the algorithm.