HealthyBlock: Blockchain-Based IT Architecture for Electronic Medical Records Resilient to Connectivity Failures

Abstract

The current information systems for the registration and control of electronic medical records (EMR) present a series of problems in terms of the fragmentation, security, and privacy of medical information, since each health institution, laboratory, doctor, etc. has its own database and manages its own information, without the intervention of patients. This situation does not favor effective treatment and prevention of diseases for the population, due to potential information loss, misinformation, or data leaks related to a patient, which in turn may imply a direct risk for the individual and high public health costs for governments. One of the proposed solutions to this problem has been the creation of electronic medical record (EMR) systems using blockchain networks; however, most of them do not take into account the occurrence of connectivity failures, such as those found in various developing countries, which can lead to failures in the integrity of the system data. To address these problems, HealthyBlock is presented in this paper as an architecture based on blockchain networks, which proposes a unified electronic medical record system that considers different clinical providers, with resilience in data integrity during connectivity failure and with usability, security, and privacy characteristics. On the basis of the HealthyBlock architecture, a prototype was implemented for the care of patients in a network of hospitals. The results of the evaluation showed high efficiency in keeping the EMRs of patients unified, updated, and secure, regardless of the network clinical provider they consult.

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

“…By using this method, privacy violations can be reduced in a fine grained manner. The other notable solutions that have demonstrated effectiveness in terms of privacy preservation are, adaptive differential privacy algorithm [66], differential privacy approach [67], HealthyBlock-based approach for privacy preservation [68], federated learning [69], and privacy-preserving (PP) distributed learning techniques [70]. All these solutions have demonstrated effectiveness for preserving people's privacy when data are collected at the time of diagnosis/treatment.…”

Blockchain technology in healthcare: A systematic review

“…Our research also indicates those users’ reservations about the safe and ethical utilization of data could be a major barrier to blockchain adoption in healthcare systems. The existing issues are primarily associated with blockchain technology’s technological limitations, such as the protection of individual nodes [ 53 ], the degree of safety permitted through cryptographic elements implemented with the system [ 70 ], besides the preservation of confidential data whereas requesters complete their computations [ 100 ]. However, certain research has drawn attention to more socially relevant issues regarding sharing of public data [ 73 ] and users’ confidence in governments [ 49 , 74 ].…”

“…The introduction of blockchain technology programs into healthcare environments has piqued the interest of some academics [ 45 ]. Such integrations can pave the way for the development of intelligent healthcare systems [ 100 ]. For example [ 47 ], argues that blockchain adoption will aid in the development of a more efficient e-health ecosystem.…”

Blockchain-Based Electronic Health Records Management: A Comprehensive Review and Future Research Direction

“…vMR (Virtual Medical Record) found in [67] is a simplified, standardised EHR data model designed to support interfacing to clinical decision support system. Among the rest of the papers, authors in [68] described about the standard of ISO 18308: 2011, HL7 and HIPAA, but did not implement those principles. Finally, researchers in [69] followed the openEHR standard.…”

“…, 2016 [11], [49], [51], [55], [73], [90], [93], [100], [101], [125], [138], [140]. Researchers used PoA in 8 papers [50], [64], [66], [68], [82], [106], [108], [114], whereas PBFT was suggested in 7 research papers [60], [63], [71], [87], [98], [104], [132]. DPoS, BFT, and improved DPoS were less popular, the number was three [12], [13], [136], two [80], [122], and two [107], [130] accordingly.…”