A Two-Echelon Responsive Health Analytic Model for Triggering Care Plan Revision in Geriatric Care Management

A Two-Echelon Responsive Health Analytic Model for Triggering Care Plan Revision in Geriatric Care Management

Valerie Tang, H. Y. Lam, C. H. Wu, G. T. S. Ho
Copyright: © 2022 |Pages: 29
DOI: 10.4018/JOEUC.289224
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Abstract

Due to the increasing ageing population, how can caregivers effectively provide long-term care services to meet the older adults’ needs with finite resources is emerging. In addressing this issue, nursing homes are striving to adopt smart health with the internet of things and artificial intelligence to improve the efficiency and sustainability of healthcare. This study proposed a two-echelon responsive health analytic model (EHAM) to deliver appropriate healthcare services in nursing homes under the Internet of Medical Things environment. A novel care plan revision index is developed using a dual fuzzy logic approach for multidimensional health assessments, followed by care plan modification using case-based reasoning. The findings reveal that EHAM can generate patient-centred long-term care solutions of high quality to maximise the satisfaction of nursing home residents and their families. Ultimately, sustainable healthcare services can be within the communities.
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1. Introduction

In an attempt to address the challenge of how to handle the growing global ageing population best, the adoption of effective geriatric care management (GCM) is now being emphasised in nursing homes for delivering the best quality of care (QoC) to older individuals who show difficulties in daily living or who have chronic diseases (Thambusamy & Palvia, 2020; Schubert et al., 2016). However, resource shortages have been proven to affect the service quality in nursing homes (Leung et al., 2020; Berridge et al., 2018; Bratt & Gautun, 2018). As such, nursing homes continue to search for better use of limited healthcare resources. The resources include in terms of capital and staffing, and facilities. So that customised care plans for serving older individuals can be established. In the meantime, how can caregivers generate effective care plans under the constraints of limited resources and a limited time frame has become a key consideration for nursing homes to explore. To address this issue to alleviate pressures on caregivers, the adoption of smart health and the integration of ubiquitous computing and ambient intelligence has drawn significant attention in the healthcare context for analysing health information, assisting in clinical decision-making and selecting the most appropriate healthcare services (Hong et al., 2021; Khanra et al., 2020; Pramanik et al., 2017; Sicari et al., 2017). The opportunities available in this area have triggered a wide response in both research and the community that focuses on continuously advancing and implementing health technologies using information technology and responsive artificial intelligence to increase their economic, social, and sustainable impacts in the field of GCM.

According to Franceschi et al. (2018), ageing increases vulnerability to age-associated diseases, which causes vision change, hearing, muscular control, bone strength, immunity and nerve function, called ageing pathology. In socially responsible nursing homes, care planning is a critical activity in providing long-term care services to the elderly residents for maintaining their health. As shown in Figure 1, a care plan refers to the elderly needs and corresponding actions to address them through care planning. It provides both standardised and individualised interventions and needs to continuously monitor and review at a specific period as changes in the elderly conditions occur (Mariani et al., 2017). However, a comprehensive care plan review process is currently executed at fixed time intervals to assess older individuals' overall health performance. Since they have different levels of health deterioration, this fixed time-interval approach may not be suitable for application to every older patient in a nursing home to satisfy their individual needs, particularly in cases of acute illness. Notably, serious health effects may emerge if inappropriate healthcare services are delivered. Therefore, modifying the care plan at dynamic time intervals according to changes in the health state should be considered in nursing homes for providing timely and accurate healthcare services.

Figure 1.

Typical GCM operations in nursing homes

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