Abstract
Electronic Health Records (EHR) have a distributed nature and can be managed by distinct affinity domains. Sharing patient health information across distinct organisations helps to deliver a well-informed diagnosis, improving the quality of healthcare service. The federation of those information systems can take the form of a distributed database where data are partitioned and possibly replicated across distinct computational systems. However, the benefits of having a distributed system, such as consistency, availability, and data protection, are mostly absent. This article proposes a distributed database consensus protocol designed to improve the performance of EHR insertion operations, a particularly critical issue in medical imaging cases due to the data volume. It explores the personal and non-transferable nature of EHR and the proposed methodology reduces the data contention through data isolation, improving the overall retrieval performance and detection of misbehaving parties. Furthermore, the proposal follows the recent European General Data Protection Regulation (GDPR), which states that appropriate mechanisms should be used in order to protect data against accidental loss, destruction, or damage, using appropriate technical or organisational measures.
Highlights
T HE proliferation of medical imaging acquisition equipment and the introduction of new modalities with high temporal and space resolution has resulted in a data explosion crisis in healthcare institutions [1], [2]
Computer-Aided Diagnosis (CAD) systems and annotation platforms [7]–[9] could benefit greatly from shareable Electronic Health Records (EHR), and relieve the burden on physicians already in short supply [10], especially in mass screening programs where disease coverage is low. For such a scenario to emerge, 1GDPR: https://gdpr-info.eu it is necessary to provide a good foundation for EHR to be available in many different organisations, in a GDPRcompliant manner [11]
Some optimisations can be made to existing Byzantine Fault Tolerant (BFT) protocols in the context of EHR and in particular medical imaging records
Summary
T HE proliferation of medical imaging acquisition equipment and the introduction of new modalities with high temporal and space resolution has resulted in a data explosion crisis in healthcare institutions [1], [2] This presents a challenge for storage [3], data flow, security [4], interoperability [5] and document sharing. Computer-Aided Diagnosis (CAD) systems and annotation platforms [7]–[9] could benefit greatly from shareable EHR, and relieve the burden on physicians already in short supply [10], especially in mass screening programs where disease coverage is low For such a scenario to emerge, 1GDPR: https://gdpr-info.eu it is necessary to provide a good foundation for EHR to be available in many different organisations, in a GDPRcompliant manner [11]. In the validation section we have set feasibility tests that show the results for inserts/updates and retrieval operations, as well as a Tendermint comparison of transactions throughput and latency
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