{"title":"Exploring internet of healthcare things for establishing an integrated care link system in the healthcare industry","authors":"H. Wan, Ks Chin","doi":"10.1177/18479790211019526","DOIUrl":null,"url":null,"abstract":"With the ageing population all over the world, long-term care services, such as nursing care, are essential to provide care and treatments to elderly patients in the community. During the nursing care services, elderly patients who live in the nursing homes require to be treated and consulted in a number of healthcare organisations, for example hospitals, mental health centres and rehabilitation centres. Currently, the data management for the elderly is relatively centralised to establish their own electronic medical records and protected health information without decision support functionalities. The community and healthcare industry are eager to develop a safe and comprehensive system to provide adequate healthcare services and monitoring to the elderly. In this study, an internet of healthcare things (IoHT)-based care link system (IoHT-CLS) is proposed, which provides a structured framework on integrating IoHT and artificial intelligence (AI) to generate a one-stop solution for managing elderly’s healthcare facilities. The elderly can be effectively linked into the integrated IoHT system by using various sensing and data collection technologies. The collected data are further processed by means of the adaptive neuro-fuzzy inference system and case-based reasoning to provide the functionalities of risk management and customised elderly service programmes for the elderly care institutions. Consequently, this study contributes to the healthcare management through the enhancement of service quality in the community.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"2 1","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering Business Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/18479790211019526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 11
Abstract
With the ageing population all over the world, long-term care services, such as nursing care, are essential to provide care and treatments to elderly patients in the community. During the nursing care services, elderly patients who live in the nursing homes require to be treated and consulted in a number of healthcare organisations, for example hospitals, mental health centres and rehabilitation centres. Currently, the data management for the elderly is relatively centralised to establish their own electronic medical records and protected health information without decision support functionalities. The community and healthcare industry are eager to develop a safe and comprehensive system to provide adequate healthcare services and monitoring to the elderly. In this study, an internet of healthcare things (IoHT)-based care link system (IoHT-CLS) is proposed, which provides a structured framework on integrating IoHT and artificial intelligence (AI) to generate a one-stop solution for managing elderly’s healthcare facilities. The elderly can be effectively linked into the integrated IoHT system by using various sensing and data collection technologies. The collected data are further processed by means of the adaptive neuro-fuzzy inference system and case-based reasoning to provide the functionalities of risk management and customised elderly service programmes for the elderly care institutions. Consequently, this study contributes to the healthcare management through the enhancement of service quality in the community.
期刊介绍:
The International Journal of Engineering Business Management (IJEBM) is an international, peer-reviewed, open access scientific journal that aims to promote an integrated and multidisciplinary approach to engineering, business and management. The journal focuses on issues related to the design, development and implementation of new methodologies and technologies that contribute to strategic and operational improvements of organizations within the contemporary global business environment. IJEBM encourages a systematic and holistic view in order to ensure an integrated and economically, socially and environmentally friendly approach to management of new technologies in business. It aims to be a world-class research platform for academics, managers, and professionals to publish scholarly research in the global arena. All submitted articles considered suitable for the International Journal of Engineering Business Management are subjected to rigorous peer review to ensure the highest levels of quality. The review process is carried out as quickly as possible to minimize any delays in the online publication of articles. Topics of interest include, but are not limited to: -Competitive product design and innovation -Operations and manufacturing strategy -Knowledge management and knowledge innovation -Information and decision support systems -Radio Frequency Identification -Wireless Sensor Networks -Industrial engineering for business improvement -Logistics engineering and transportation -Modeling and simulation of industrial and business systems -Quality management and Six Sigma -Automation of industrial processes and systems -Manufacturing performance and productivity measurement -Supply Chain Management and the virtual enterprise network -Environmental, legal and social aspects -Technology Capital and Financial Modelling -Engineering Economics and Investment Theory -Behavioural, Social and Political factors in Engineering