A Systematic Review of the Role of Gerontechnology and AI in Revolutionizing the Wellbeing Landscape for Aging Adults

A Systematic Review of the Role of Gerontechnology and AI in Revolutionizing the Wellbeing Landscape for Aging Adults

Suyesha Singh, Vaishnavi Nambiar
Copyright: © 2024 |Pages: 25
DOI: 10.4018/979-8-3693-1123-3.ch011
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Abstract

The application of AI in geriatric healthcare has become a revolutionary and essential solution to tackling the problems faced by older people. An important step toward providing patient-centered and cost-effective treatment, the integration of AI in geriatric healthcare will ultimately enhance the standard of life for older people. This chapter is a systematic review of the rapidly developing field of AI applications in geriatric healthcare. It provides a thorough analysis of the impact and potential of AI technologies in addressing the healthcare needs of the aging population. The review was conducted using PRISMA framework. Thirty-three articles were considered for final review from which five themes were deduced. The study will facilitate the development of relevant and inclusive solutions for healthcare of older individuals and hasten the possibility of greater wellbeing and inclusion of older adults in the technological innovativeness of the healthcare facilities.
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Introduction

The need for geriatric healthcare services is growing as the global population ages. The aging population presents particular healthcare issues, such as the requirement for comprehensive care management, various persistent diseases, and memory impairment. In the realm of geriatric healthcare, artificial intelligence (AI) has demonstrated to be an innovative force through delivering novel approaches to boost diagnosis and treatment, enhance patient care, and streamline the distribution of resources. The chapter aims to systematically analyze the recent trends in utilization of AI in the treatment of diverse range of problems faced by geriatric adults and reflect on its benefits and limitations, respectively.

The chapter begins by providing an overview of the relevance and significance of AI in geriatric healthcare, followed by the formulation of research question and strategy for conducting systematic literature review. Based on the selected studies, an elaborative and categorical understanding of the use of AI is provided. Lastly, authors provide the implications of the findings at the organizational and policy levels.

Relevance of Artificial Intelligence in Geriatric Healthcare

Plans for Individualized Treatment

Based on their distinct medical histories, genetic profiles, and preferences, geriatric patients can receive tailored treatment programs from AI-driven systems (Radenkovic et al., 2021; Alowais et al., 2023). These plans take into account an individual's drug schedule, restrictions on food, difficulties with movement, and other aspects to make sure the care is customized to meet their unique needs.

Virtual Surveillance and Telemedicine

Mobility issues or living in rural places can make frequent medical visits difficult for many older persons. Healthcare practitioners may now remotely monitor patients' vital signs, medication compliance, and general well-being thanks to AI-powered remote monitoring and telehealth systems. Additionally, telephone consultations provide older people with a convenient option to get healthcare services (Dantas et al., 2023; Sheikh et al., 2023; Meena et al., 2021), eliminating the need for in-person visits and dispensing prompt medical advice.

Prevention of Falls and Detection

The senior population is particularly vulnerable to falls, which frequently result in severe injuries and hospitalizations. AI-based fall detection systems watch a person's motions and look for odd patterns that might be signs of a fall using cameras, sensors, or wearable technology (Seng et al., 2023; Monge et al., 2023; Ahmed et al., 2024).

Administration of Medications

Elderly individuals may have complicated treatment regimens comprising many medications. AI can help with medication management by reminding patients to take their medications on time (Kolben et al., 2023; Bays et al., 2023), keeping track of drug interactions, and warning medical professionals and caregivers about potential problems.

Analytics for Predicting Medical Re-Admission

For senior patients, readmissions to the hospital are a typical cause for concern because they frequently arise from complications or poor post-discharge care. AI algorithms can examine patient data to forecast the likelihood of readmission and give healthcare professionals useful information to stop such occurrences (Zeinalnezhad & Shishehchi, 2023). The delivery of geriatric healthcare can be more economical and patient-focused by proactively addressing these concerns.

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