Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare

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Abstract

Chronic diseases are a growing concern worldwide, with nearly 25% of adults suffering from one or more chronic health conditions, thus placing a heavy burden on individuals, families, and healthcare systems. With the advent of the “Smart Healthcare” era, a series of cutting-edge technologies has brought new experiences to the management of chronic diseases. Among them, smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state. However, how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management, in terms of quality of life, patient outcomes, and privacy protection, is an urgent issue that needs to be addressed. Artificial intelligence (AI) can provide intelligent suggestions by analyzing a patient’s physiological data from wearable devices for the diagnosis and treatment of diseases. In addition, blockchain can improve healthcare services by authorizing decentralized data sharing, protecting the privacy of users, providing data empowerment, and ensuring the reliability of data management. Integrating AI, blockchain, and wearable technology could optimize the existing chronic disease management models, with a shift from a hospital-centered model to a patient-centered one. In this paper, we conceptually demonstrate a patient-centric technical framework based on AI, blockchain, and wearable technology and further explore the application of these integrated technologies in chronic disease management. Finally, the shortcomings of this new paradigm and future research directions are also discussed.

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Impact of mHealth Chronic Disease Management on Treatment Adherence and Patient Outcomes: A Systematic Review

Saee Hamine, Emily Gerth-Guyette, Dunia Faulx … (2015)

Background Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management. Objective We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management (“mAdherence”), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers. Methods We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users. Results In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%). Conclusions There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.

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Prevention of chronic disease in the 21st century: elimination of the leading preventable causes of premature death and disability in the USA

Ursula E Bauer, Peter A Briss, Richard A Goodman … (2014)

With non-communicable conditions accounting for nearly two-thirds of deaths worldwide, the emergence of chronic diseases as the predominant challenge to global health is undisputed. In the USA, chronic diseases are the main causes of poor health, disability, and death, and account for most of health-care expenditures. The chronic disease burden in the USA largely results from a short list of risk factors--including tobacco use, poor diet and physical inactivity (both strongly associated with obesity), excessive alcohol consumption, uncontrolled high blood pressure, and hyperlipidaemia--that can be effectively addressed for individuals and populations. Increases in the burden of chronic diseases are attributable to incidence and prevalence of leading chronic conditions and risk factors (which occur individually and in combination), and population demographics, including ageing and health disparities. To effectively and equitably address the chronic disease burden, public health and health-care systems need to deploy integrated approaches that bundle strategies and interventions, address many risk factors and conditions simultaneously, create population-wide changes, help the population subgroups most affected, and rely on implementation by many sectors, including public-private partnerships and involvement from all stakeholders. To help to meet the chronic disease burden, the US Centers for Disease Control and Prevention (CDC) uses four cross-cutting strategies: (1) epidemiology and surveillance to monitor trends and inform programmes; (2) environmental approaches that promote health and support healthy behaviours; (3) health system interventions to improve the effective use of clinical and other preventive services; and (4) community resources linked to clinical services that sustain improved management of chronic conditions. Establishment of community conditions to support healthy behaviours and promote effective management of chronic conditions will deliver healthier students to schools, healthier workers to employers and businesses, and a healthier population to the health-care system. Collectively, these four strategies will prevent the occurrence of chronic diseases, foster early detection and slow disease progression in people with chronic conditions, reduce complications, support an improved quality of life, and reduce demand on the health-care system. Of crucial importance, with strengthened collaboration between the public health and health-care sectors, the health-care system better uses prevention and early detection services, and population health is improved and sustained by solidifying collaborations between communities and health-care providers. This collaborative approach will improve health equity by building communities that promote health rather than disease, have more accessible and direct care, and focus the health-care system on improving population health. Copyright © 2014 Elsevier Ltd. All rights reserved.

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A Decentralized Privacy-Preserving Healthcare Blockchain for IoT

Ashutosh Dhar Dwivedi, Gautam Srivastava, Shalini Dhar … (2019)

Medical care has become one of the most indispensable parts of human lives, leading to a dramatic increase in medical big data. To streamline the diagnosis and treatment process, healthcare professionals are now adopting Internet of Things (IoT)-based wearable technology. Recent years have witnessed billions of sensors, devices, and vehicles being connected through the Internet. One such technology—remote patient monitoring—is common nowadays for the treatment and care of patients. However, these technologies also pose grave privacy risks and security concerns about the data transfer and the logging of data transactions. These security and privacy problems of medical data could result from a delay in treatment progress, even endangering the patient’s life. We propose the use of a blockchain to provide secure management and analysis of healthcare big data. However, blockchains are computationally expensive, demand high bandwidth and extra computational power, and are therefore not completely suitable for most resource-constrained IoT devices meant for smart cities. In this work, we try to resolve the above-mentioned issues of using blockchain with IoT devices. We propose a novel framework of modified blockchain models suitable for IoT devices that rely on their distributed nature and other additional privacy and security properties of the network. These additional privacy and security properties in our model are based on advanced cryptographic primitives. The solutions given here make IoT application data and transactions more secure and anonymous over a blockchain-based network.

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Author and article information

Contributors

Yi Xie: 455085617@qq.com

Lin Lu: lledu2014@163.com

Zhe Dong: 13601706191@139.com

Journal

Journal ID (nlm-ta): Curr Med Sci

Journal ID (iso-abbrev): Curr Med Sci

Title: Current Medical Science

Publisher: Huazhong University of Science and Technology (Wuhan )

ISSN (Print): 2096-5230

ISSN (Electronic): 2523-899X

Publication date (Electronic): 24 December 2021

Pages: 1-11

Affiliations

[1 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, Department of Orthopedic Surgery, Union Hospital, Tongji Medical College, , Huazhong University of Science and Technology, ; Wuhan, 430022 China

[2 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, Laboratory of Intelligent Medicine, Union Hospital, Tongji Medical College, , Huazhong University of Science and Technology, ; Wuhan, 430022 China

[3 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, School of Electronic Information and Communications, , Huazhong University of Science and Technology, ; Wuhan, 430074 China

[4 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, Wuhan Fourth Hospital, Tongji Medical College, , Huazhong University of Science and Technology, ; Wuhan, 430032 China

[5 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, School of Cyber Science and Engineering, , Huazhong University of Science and Technology, ; Wuhan, 430074 China

Article

Publisher ID: 2485

DOI: 10.1007/s11596-021-2485-0

PMC ID: 8702375

PubMed ID: 34950987

SO-VID: f4dfc5fd-1167-4434-8c39-017933b9e305

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This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare

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Artificial Intelligence in Medicine

Most cited references 59

Impact of mHealth Chronic Disease Management on Treatment Adherence and Patient Outcomes: A Systematic Review

Prevention of chronic disease in the 21st century: elimination of the leading preventable causes of premature death and disability in the USA

A Decentralized Privacy-Preserving Healthcare Blockchain for IoT

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