About this Research Topic
Recent years have seen a rapidly growing interest in blockchain technologies (DLT) among health and healthcare research and practice communities. These technologies are currently being explored in different parts of the world for a wide range of topics: securing patient and provider identities, securely storing health records and maintaining a single source of truth, managing pharmaceutical and medical device supply chains, medical fraud detection, medical data sharing among researchers, research data monetization, crisis mapping and recovery scenarios, using blockchain-enabled augmented reality, and even tackling environmental plastic pollution with blockchain rewards. Given the increasing availability of health data and the advancements in the Internet of Things, recent research has also incorporated artificial intelligence and edge computing into blockchain-based healthcare applications. Researchers have identified a large number of blockchain use cases in the healthcare sector, but there is a serious lack of reproducible architectures and prototypes that provide practical designs that can be further investigated.
Recent developments of blockchain and distributed ledger technologies have enabled much more sophisticated computing in a decentralized manner. Combined with other key inherent properties of blockchain technologies, immutability and transparency, blockchain-based architectures can potentially transform the healthcare industry in many revolutionary ways, particularly to solve the pressing interoperability challenges plaguing data sharing, medical supply chain management, patient identity matching, and many other healthcare services. Although there is significant demand of interoperable solutions, blockchain and related DLTs face their own limitations in data privacy, security, and scalability. The goal of this Research Topic is to invite research and presentations of blockchain-enabled or DLT-based architectures that will improve the healthcare practice, process, systems, and outcomes while overcoming such technical limitations.
Potential topics include, but are not limited to:
• Decentralized/DLT identity architectures
• Blockchain/DLT-based AI architectures
• Blockchain/DLT and big data designs
• Interoperable data sharing systems
• Medical supply chain management
• Architectures for stakeholders of the sector
• Personal health records
• Medical research platforms
• Blockchain/DLT and contact tracing
• Security architectures
• Formal approaches to evaluate blockchain designs
Recent developments of blockchain and distributed ledger technologies have enabled much more sophisticated computing in a decentralized manner. Combined with other key inherent properties of blockchain technologies, immutability and transparency, blockchain-based architectures can potentially transform the healthcare industry in many revolutionary ways, particularly to solve the pressing interoperability challenges plaguing data sharing, medical supply chain management, patient identity matching, and many other healthcare services. Although there is significant demand of interoperable solutions, blockchain and related DLTs face their own limitations in data privacy, security, and scalability. The goal of this Research Topic is to invite research and presentations of blockchain-enabled or DLT-based architectures that will improve the healthcare practice, process, systems, and outcomes while overcoming such technical limitations.
Potential topics include, but are not limited to:
• Decentralized/DLT identity architectures
• Blockchain/DLT-based AI architectures
• Blockchain/DLT and big data designs
• Interoperable data sharing systems
• Medical supply chain management
• Architectures for stakeholders of the sector
• Personal health records
• Medical research platforms
• Blockchain/DLT and contact tracing
• Security architectures
• Formal approaches to evaluate blockchain designs
Keywords: Healthcare, medicine, clinical trials, interoperability, blockchain technology, distributed ledger technology, artificial intelligence, big data
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
