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The world is facing multiple healthcare challenges because of the emergence of the COVID-19 (coronavirus) pandemic. The pandemic has exposed the limitations of handling public healthcare emergencies using existing digital healthcare technologies. Thus, the COVID-19 situation has forced research institutes and countries to rethink healthcare delivery solutions to ensure continuity of services while people stay at home and practice social distancing. Recently, several researchers have focused on disruptive technologies, such as blockchain and artificial intelligence (AI), to improve the digital healthcare workflow during COVID-19. Blockchain could combat pandemics by enabling decentralized healthcare data sharing, protecting users’ privacy, providing data empowerment, and ensuring reliable data management during outbreak tracking. In addition, AI provides intelligent computer-aided solutions by analyzing a patient’s medical images and symptoms caused by coronavirus for efficient treatments, future outbreak prediction, and drug manufacturing. Integrating both blockchain and AI could transform the existing healthcare ecosystem by democratizing and optimizing clinical workflows. In this article, we begin with an overview of digital healthcare services and problems that have arisen during the COVID-19 pandemic. Next, we conceptually propose a decentralized, patient-centric healthcare framework based on blockchain and AI to mitigate COVID-19 challenges. Then, we explore the significant applications of integrated blockchain and AI technologies to augment existing public healthcare strategies for tackling COVID-19. Finally, we highlight the challenges and implications for future research within a patient-centric paradigm.
The novel coronavirus disease (COVID-19) has spread to almost every country since the outbreak in December 2019 from Wuhan, China. The severity of this epidemic became extensive within a month of the virus’s widescale spread. Thus, a Public Health Emergency of International Concern (PHEIC) was declared by the World Health Organization (WHO) [1]. The outbreak forced several nations to close their borders, maintain lockdowns, and practice social distancing to limit the spread of COVID-19. These led to massive interruptions in the economy of many sectors, such as industry, insurance, agriculture, supply chains, transport, and tourism [2]. The pandemic has had an unexpected impact at the global level, not just on an economic scale, but also pushing healthcare systems around the world to their limits, such as through a lack of personal protective equipment (PPE) for healthcare workers and by causing difficulties in diagnosing and monitoring large populations [3]. In general, the healthcare system has operated in a closed ecosystem of siloed institutions, where healthcare professionals (i.e., doctors, radiologists, clinicians, and researchers) have served as the primary stakeholders of medical information. The flow of information has gone in one direction, i.e., healthcare expert to patient. However, in the era of digitized patient health records, data are growing and flowing across a closed healthcare system faster than ever before. The one-to-one flow of information is giving way to a multiplicity of information, sharing relationships with many-to-many, one-to-many, and many-to-one [4]. In such cases, most coronavirus information collected from the public, hospitals, and clinical laboratories may not be faithful, since the data are not gathered according to set guidelines [5] and are not monitored or stored appropriately because of the vastness of digitized patient health records. The existing healthcare technology requires trustable data, which is crucial to providing the correct widespread information about the novel coronavirus. Furthermore, the virus test procedure using medical tools for detecting coronavirus infections often takes several days to complete because of the inaccuracy and manual processing of large volumes of data. Finally, tracking or surveilling infected patients or their contacts raises several privacy issues [6]. These insufficiencies exposed by COVID-19 have prompted healthcare organizations to transform the existing digital healthcare system to combat pandemic situations. Overall, the digital healthcare ecosystem needs to facilitate clinical trials, frontline care, data surveillance, medical billing, telemedicine, drug delivery, treatment facilities, and strategy discovery. In addition, it is essential to design a more patient-centric and democratized digital healthcare ecosystem for combating COVID-19 and future pandemics by using digital platforms.
Recently, several researchers have focused on utilizing disruptive technologies, such as blockchain and artificial intelligence (AI), to provide solutions for these ongoing COVID-19 crises [7, 8]. Blockchain is a peer-to-peer (P2P) distributed and shared ledger, where transactions are digitally recorded into blocks. The nodes (miners) of the blockchain network are responsible for linking the blocks to each other in chronological order. Blockchain nodes contain a copy of the stored information and keep their network active [9]. Thus, blockchain provides the entire history or provenance of data. It is possible to store sample test results, patient records, discharge summaries, and vaccination statuses in a blockchain digital ledger. These will support clinical laboratories, patients, hospitals, and government-funded healthcare organizations in a decentralized way to manage healthcare information using self-executing contracts called “smart contracts” [8]. Smart contracts are computer programs that execute the predefined terms of an agreement between participants when certain conditions are met within the blockchain network [10]. Furthermore, smart contracts based on blockchain technology could automate auditing processes, medical supply chain management, outbreak tracking, and remote patient monitoring [10]. On the other hand, AI technologies, such as machine learning and deep learning, have been used as powerful tools for enhancing COVID-19 detection, diagnosis, and vaccination/drug discovery, and for performing extensive data analysis [11]. In addition, the federated learning paradigm [12, 13] has gained traction for healthcare applications to solve the data privacy and governance problems by training AI models collaboratively without sharing the raw datasets. Thus, AI could process an enormous amount of data in less time and at a fraction of the cost by performing tasks that are difficult to achieve manually. Meanwhile, the blockchain could promote secure data access and interoperability while protecting the privacy and security of health data [14]. Integrated blockchain and AI technology could reshape the healthcare ecosystem by advancing the patient-centric approach [15, 16, 17]. A patient-centric approach could provide a viable solution to cope with the coronavirus epidemic for disseminating treatment and managing pandemic situations.
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Although researchers have reviewed blockchain and AI to combat COVID-19 [18], these reviews mainly focused on the role of blockchain, such as the development of data storage, managing big data, and security issues for COVID-19 patients [14]. Other reviews focused on analytics and decision tools for healthcare professionals to combat COVID-19 using AI technologies [11]. However, these reviews lacked a concrete and comprehensive study on integrating blockchain and AI for COVID-19 responses based on a patient-centric approach in the healthcare ecosystem, a limitation that was the primary driver for conducting our research. This paper aimed to provide and explore insight into combined blockchain and AI technology to mitigate the COVID-19 pandemic’s challenges by transforming the traditional healthcare ecosystem. Then, we discuss the services and practical applications of using these innovative technologies to facilitate COVID-19 healthcare strategies. The contributions of this article are as follows:
This work is organized as follows: Section 2 includes related research work and recent trends in healthcare systems that utilize blockchain and AI technologies. Section 3 provides an overview of digital healthcare services and describes the background of blockchain and AI technologies. In Section 4, we exploit a blockchain- and AI-based conceptual framework for delivering patient-centric healthcare services to combat COVID-19. Section 5 explores the potential applications of the decentralized, patient-centric framework to facilitate pandemic healthcare strategies. In Section 6, we discuss the relevant open issues, possible solutions, and further research directions. Finally, we conclude the paper in Section 7.
In this section, state-of-the-art research related to healthcare systems based on blockchain and AI is presented. The key risks and issues in a traditional healthcare system include a single point of failure, data alterations, high chances of malicious cyberattacks, centralized authority, high data management cost, and databases that are not transparent. To address these issues, researchers have proposed numerous blockchain-based solutions. The authors of [19] addressed the security and privacy concerns by using a blockchain-based server–client architecture network to store the hashed patients’ data. However, these server–client architectures are prone to a single-point failure. Thus, a blockchain-based distributed mechanism for data accessibility between patients and doctors
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