Chapter 1 The impact of blockchain technology on the healthcare system
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J. Raj Kumar
Abstract
Blockchain is a relatively new technology that can be used to manage electronic data. This technology has the potential to support transparency and accountability. A distributed public ledger of transactions is known as a blockchain. Each participant in a computer network can view an identical copy of the distributed public ledger. Blockchain technology is most useful for use cases that involve transactions that leave only a minimal digital footprint, where transparency and immutability are advantageous. The verification of patient identities, the management of medical and pharmaceutical supply chains, and the administration of dynamic patient consent as well as data sharing and access permissions are all potential applications for blockchain technology in the healthcare industry. An identity management system to support contact tracing in South Korea and a system to support sharing data and software code for research purposes are two examples of the new tools that are emerging to combat the COVID-19 pandemic. Both of these tools are enabled by blockchain technology. In addition, blockchain technology has been implemented or proposed for use in the management of supply chains for pharmaceuticals, medical supplies, and even an upcoming vaccine. There is a great deal of excitement regarding the application of blockchain technology in the medical field, but its value may be exaggerated. The majority of the currently available research on the application of blockchain technology in the healthcare industry presents theoretical frameworks, architectures, or models with very few specific technical details. In most cases, there is neither a prototype nor a pilot implementation from which to gain insight. It is unusual for blockchain technology to be implemented in healthcare on a national scale. Blockchain should be implemented in areas of a health information system, where it will have the greatest impact in conjunction with other technologies, in order to meet the information requirements and policy objectives that have been established. It is important to note that blockchain is not well-suited to the storage of high volumes of data due to the computational and capacity constraints imposed by replicating the blockchain across every participant in the network (node). It would be inefficient and expensive to store large records on the blockchain, such as complete electronic medical records or records of genetic data. Examples of such records include full medical records. It is also difficult to query data contained within a blockchain, which restricts the use of data in clinical settings, statistical analyses, and research. Additionally, storing personal health data “on chain,” which makes the data, by definition, visible to other users of the network, constitutes an invasion of a person’s right to privacy. The EU General Data Protection Regulation grants individuals certain rights, one of which is the right to erasure, but these rights are in conflict with the immutability of blocks within a chain. Blockchain applications should be evaluated in accordance with the Organisation for Economic Cooperation and Development Council on Health Data Governance Recommendation and focus on four key aspects: fitness for use, alignment with laws and regulations, incremental adoption to allow time for evaluation, and a training and communication plan to take advantage of blockchain’s strengths and avoid its pitfalls.
Abstract
Blockchain is a relatively new technology that can be used to manage electronic data. This technology has the potential to support transparency and accountability. A distributed public ledger of transactions is known as a blockchain. Each participant in a computer network can view an identical copy of the distributed public ledger. Blockchain technology is most useful for use cases that involve transactions that leave only a minimal digital footprint, where transparency and immutability are advantageous. The verification of patient identities, the management of medical and pharmaceutical supply chains, and the administration of dynamic patient consent as well as data sharing and access permissions are all potential applications for blockchain technology in the healthcare industry. An identity management system to support contact tracing in South Korea and a system to support sharing data and software code for research purposes are two examples of the new tools that are emerging to combat the COVID-19 pandemic. Both of these tools are enabled by blockchain technology. In addition, blockchain technology has been implemented or proposed for use in the management of supply chains for pharmaceuticals, medical supplies, and even an upcoming vaccine. There is a great deal of excitement regarding the application of blockchain technology in the medical field, but its value may be exaggerated. The majority of the currently available research on the application of blockchain technology in the healthcare industry presents theoretical frameworks, architectures, or models with very few specific technical details. In most cases, there is neither a prototype nor a pilot implementation from which to gain insight. It is unusual for blockchain technology to be implemented in healthcare on a national scale. Blockchain should be implemented in areas of a health information system, where it will have the greatest impact in conjunction with other technologies, in order to meet the information requirements and policy objectives that have been established. It is important to note that blockchain is not well-suited to the storage of high volumes of data due to the computational and capacity constraints imposed by replicating the blockchain across every participant in the network (node). It would be inefficient and expensive to store large records on the blockchain, such as complete electronic medical records or records of genetic data. Examples of such records include full medical records. It is also difficult to query data contained within a blockchain, which restricts the use of data in clinical settings, statistical analyses, and research. Additionally, storing personal health data “on chain,” which makes the data, by definition, visible to other users of the network, constitutes an invasion of a person’s right to privacy. The EU General Data Protection Regulation grants individuals certain rights, one of which is the right to erasure, but these rights are in conflict with the immutability of blocks within a chain. Blockchain applications should be evaluated in accordance with the Organisation for Economic Cooperation and Development Council on Health Data Governance Recommendation and focus on four key aspects: fitness for use, alignment with laws and regulations, incremental adoption to allow time for evaluation, and a training and communication plan to take advantage of blockchain’s strengths and avoid its pitfalls.
Kapitel in diesem Buch
- Frontmatter I
- About the book V
- Preface VII
- Foreword IX
- Contents XI
- List of contributors XV
- Chapter 1 The impact of blockchain technology on the healthcare system 1
- Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
- Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
- Chapter 4 Role of artificial intelligence in disease diagnosis 89
- Chapter 5 Machine learning for twinning the human body 105
- Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
- Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
- Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
- Chapter 9 Nanorobots in healthcare 209
- Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
- Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
- Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
- Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
- Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
- Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
- Index 375
Kapitel in diesem Buch
- Frontmatter I
- About the book V
- Preface VII
- Foreword IX
- Contents XI
- List of contributors XV
- Chapter 1 The impact of blockchain technology on the healthcare system 1
- Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
- Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
- Chapter 4 Role of artificial intelligence in disease diagnosis 89
- Chapter 5 Machine learning for twinning the human body 105
- Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
- Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
- Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
- Chapter 9 Nanorobots in healthcare 209
- Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
- Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
- Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
- Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
- Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
- Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
- Index 375
