Chapter One - Blockchain Technology Use Cases in Healthcare

Abstract Blockchain technology alleviates the reliance on a centralized authority to certify information integrity and ownership, as well as mediate transactions and exchange of digital assets, while enabling secure and pseudoanonymous transactions along with agreements directly between interacting parties. It possesses key properties, such as immutability, decentralization, and transparency, which potentially address pressing issues in healthcare, such as incomplete records at point of care and difficult access to patients’ own health information. An efficient and effective healthcare system requires interoperability, which allows software apps and technology platforms to communicate securely and seamlessly, exchange data, and use the exchanged data across health organizations and app vendors. Unfortunately, healthcare today suffers from siloed and fragmented data, delayed communications, and disparate workflow tools caused by the lack of interoperability. Blockchain offers the opportunity to enable access to longitudinal, complete, and tamper-aware medical records that are stored in fragmented systems in a secure and pseudoanonymous fashion. This chapter focuses on the applicability of Blockchain technology in healthcare by (1) identifying potential Blockchain use cases in healthcare, (2) providing a case study that implements Blockchain technology, and (3) evaluating design considerations when applying this technology in healthcare.

[1]  Marc Berg,et al.  Viewpoint Paper: Some Unintended Consequences of Information Technology in Health Care: The Nature of Patient Care Information System-related Errors , 2003, J. Am. Medical Informatics Assoc..

[2]  David W. Bates,et al.  Paperless healthcare: Progress and challenges of an IT-enabled healthcare system , 2010 .

[3]  Elizabeth Warren Strengthening Research through Data Sharing. , 2016, The New England journal of medicine.

[4]  George Hripcsak,et al.  Health data use, stewardship, and governance: ongoing gaps and challenges: a report from AMIA's 2012 Health Policy Meeting , 2014, J. Am. Medical Informatics Assoc..

[5]  John Fletcher,et al.  Sharing Clinical Trial Data: A Proposal from the International Committee of Medical Journal Editors , 2016, The National medical journal of India.

[6]  Jenny James,et al.  Dealing with drug-seeking behaviour. , 2016, Australian prescriber.

[7]  David T. Marc,et al.  Why Patient Matching Is a Challenge: Research on Master Patient Index (MPI) Data Discrepancies in Key Identifying Fields. , 2016, Perspectives in health information management.

[8]  Laxmaiah Manchikanti,et al.  Opioid epidemic in the United States. , 2012, Pain physician.

[9]  John E. Mattison,et al.  Review: The HL7 Clinical Document Architecture , 2001, J. Am. Medical Informatics Assoc..

[10]  J. Grossman,et al.  Building a Better Delivery System: A New Engineering/Health Care Partnership , 2005 .

[11]  D. Parkin,et al.  The evolution of the population-based cancer registry , 2006, Nature Reviews Cancer.

[12]  Patrick Blake,et al.  Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine , 2015, Journal of Clinical Bioinformatics.

[13]  Michael D. Reis,et al.  Types and origins of diagnostic errors in primary care settings. , 2013, JAMA internal medicine.

[14]  Design of blockchain-based apps using familiar software patterns with a healthcare focus , 2017 .

[15]  Douglas C. Schmidt,et al.  FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data , 2018, Computational and structural biotechnology journal.

[16]  V. Mbarika,et al.  What is telemedicine? A collection of 104 peer-reviewed perspectives and theoretical underpinnings. , 2007, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[17]  Kamran Sartipi,et al.  HL7 FHIR: An Agile and RESTful approach to healthcare information exchange , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[18]  Mary F. Wisniewski,et al.  Diagnostic error in medicine: analysis of 583 physician-reported errors. , 2009, Archives of internal medicine.

[19]  Atul J. Butte,et al.  Opening clinical trial data: are the voluntary data-sharing portals enough? , 2015, BMC Medicine.

[20]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[21]  José Luis Fernández Alemán,et al.  Security and privacy in electronic health records: A systematic literature review , 2013, J. Biomed. Informatics.

[22]  Jeanmarie Perrone,et al.  Addressing the Opioid Epidemic. , 2015, JAMA.

[23]  David W. Bates,et al.  White Paper: Personal Health Records: Definitions, Benefits, and Strategies for Overcoming Barriers to Adoption , 2006, J. Am. Medical Informatics Assoc..

[24]  Nick Black,et al.  Relationship between patient reported experience (PREMs) and patient reported outcomes (PROMs) in elective surgery , 2014, BMJ quality & safety.

[25]  D. Bates,et al.  Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. , 2003, Archives of internal medicine.

[26]  Charlotte A. Weaver,et al.  Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. , 2013, Journal of the American Medical Informatics Association : JAMIA.

[27]  Robert LaRose,et al.  The impact of rural broadband development: Lessons from a natural field experiment , 2010, Gov. Inf. Q..

[28]  G E Gross,et al.  The role of the tumor board in a community hospital , 1987, CA: a cancer journal for clinicians.