Blockchain Reinventing the Healthcare Industry: Use Cases and Applications

Blockchain Reinventing the Healthcare Industry: Use Cases and Applications

Vijayaraghavan Varadharajan, Divik Bansal, Sanal J. Nair, Rian Leevinson J
DOI: 10.4018/978-1-7998-6650-3.ch013
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Abstract

The fragmented and disorganized nature of data in healthcare poses a variety of challenges to scientific research and medical applications. This mainly stems from the lack of traceability of transactions, complex disconnected networks, and lack of data interoperability. This complexity leads to difficulties in conducting research and clinical trials, and to the problem of counterfeit drugs in the market. This triggers lack of availability and accessibility of data for researchers and medical experts. Blockchain technology offers comprehensive solutions to these problems, and hence it has been of enormous interest in the healthcare sector. Blockchain technology with its innate transparency, traceability, data security, and distributed nature can help to overcome the data related problems in healthcare. This chapter provides an overview of the use of blockchain in the healthcare industry and explores various use-cases and applications. This chapter also discusses case-studies and various challenges faced while adapting blockchain in the healthcare industry.
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Introduction

Blockchain technology is a decentralized and distributed data sharing platform without the need of a central authority. Transactions in blockchain are innately secure, tamperproof and trustworthy due to cryptographic algorithms and proof of work feature of consensus algorithms. In recent years, use of blockchain and digital ledger technologies have gained traction and entered different domains, largely due to the popularity of cryptocurrencies. After gaining popularity as a distributed ledger technology used for the implementation of the bitcoin cryptocurrency, blockchain has gained popularity in non-financial domains and hence is now considered as a general-purpose technology (Jovanovic et al, 2005).

The healthcare sector has excellent potential for the implementation of blockchain-enabled technologies and a variety of use-cases have been developed with the help of blockchain. Studies have shown a wide range of possibilities with the use of blockchain in healthcare. The main areas of application include Electronic Health Records (EHR), personal patient data, medical records storage systems, clinical trial support systems, data management for connected devices, administrative systems, and supply chain in the pharmaceutical industry.

The blockchain is predominantly used for improving complex, multiparty transactions, access control, data integrity and provenance which are some of the major challenges in the healthcare industry today. Blockchain enables the secure transfer of information amongst researchers, healthcare professionals and patients. It can be used to build integrated health management systems across different institutions, healthcare systems and clinics. It also enables efficient electronic health records and personal health record managements, which are an essential part of modern healthcare industry. Moreover, this also facilitates seamless data accessibility for biomedical and bioinformatics researchers, paving way for better scientific collaborations and research. Provenance is one of the key advantages of blockchain and it plays an impeccable part in the pharmaceutical supply chain, especially to prevent counterfeit drugs and adulterations in medicine.

These are extremely important application areas that could be revolutionized by blockchain. Moreover, the use of blockchain can also improve interoperability while preserving the confidentiality and security of data. It conforms to strict regulations in terms of the handling and storage of sensitive data and it contains inherent integrity.

The evolution of technology has brought fundamental changes in the design of healthcare systems. The drawbacks of conventional healthcare systems will be overcome by the next generation healthcare systems, that would be intelligent, better connected, collaborative, secure by design, and will focus on inclusive user experience. Artificial intelligence can munch on petabytes of data from distributed systems and generate meaningful insights about the libraries of chemical compounds, natural products, extracts, and active agents throughout the drug discovery. A wearable wristwatch or a personal health assistant on mobile devices could identify conditions of medical emergencies like heart failure, diabetes, asthma attacks, etc. and alert the physician. Similarly, Augmented Reality is helping to model the novel discoveries and make them accessible for academia. The convergence of digital technologies such as Machine learning, IoT, Blockchain, and Augmented Reality will bring an unprecedented level of collaboration, trigger innovation in medical research, and facilitate newer concepts like precision medicine, population health, and help to create decision support systems for physicians. Blockchain enables trust, data integrity, data security, verifiability and better control over sensitive information moving between many devices, organizations, platforms and algorithms.

With humans being accustomed to a more sedentary lifestyle and a rapid increase in the aging population, there has been a considerable increase in the cost of healthcare and a growing risk of chronic diseases. Perhaps a more meaningful and long-term benefit lies in precision genome medicine. Currently, genome sequencing is finding its use in cancer research, characterizing genetic disease, and in predicting an individual's probable response to treatment. Advancement in the genome research together with technologies such as machine learning and blockchain would help to create a global genome knowledge repository or decision support database (Mattick et al., 2014). The global decision support systems could drastically improve the diagnosis and therapy for chronic diseases, personalized drug prescription, and pre-empting an epidemic based on the larger population data.

Key Terms in this Chapter

NIDA: National Institute of Drug Abuse is the United States of America’s federal agency supporting scientific research on drug use.

Smart Contract: A smart contract is a computer protocol intended to digitally facilitate, verify, or enforce the negotiation or performance of a contract. Smart contracts allow the performance of credible transactions without third parties. These transactions are trackable and irreversible.

HL7: Health Level Seven or HL7 refers to a set of international standards for transfer of clinical and administrative data between software applications used by various healthcare providers.

Distributed Ledger Technology (DLT): A distributed ledger is a consensus of replicated, shared, and synchronized digital data geographically spread across countries, organizations, or institutions. There is no central administrator or centralized data storage.

Opioids: These are substances that have effects similar those of morphine. Medically they are primarily used for pain relief, including anesthesia. Opioids include oxycodone, hydrocodone, morphine, etc.

NHS: The National Health Service (NHS) is the umbrella term for the publicly-funded healthcare systems of the United Kingdom comprising of NHS Scotland, NHS Whales and Health and Social Care in Northern Ireland.

WHO: The World Health Organization (WHO) is a specialized agency of the United Nations responsible for international public health. The WHO's broad mandate includes advocating for universal healthcare, monitoring public health risks, coordinating responses to health emergencies, and promoting human health and wellbeing.

CDS: CDS stands for clinical decision support systems that are health information technology systems designed to provide physicians and other health professionals with clinical decision support i.e. assistance with clinical decision-making task.

Serialized Drug: Serialization of drugs is the process of assigning unique numbers to each unit of prescription product, which contains information about the product's origin, batch number and expiration date.

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