Literature DB >> 32540775

Decentralised provenance for healthcare data.

Andrea Margheri1, Massimiliano Masi2, Abdallah Miladi3, Vladimiro Sassone4, Jason Rosenzweig5.   

Abstract

OBJECTIVE: The creation and exchange of patients' Electronic Healthcare Records have developed significantly in the last decade. Patients' records are however distributed in data silos across multiple healthcare facilities, posing technical and clinical challenges that may endanger patients' safety. Current healthcare sharing systems ensure interoperability of patients' records across facilities, but they have limits in presenting doctors with the clinical context of the data in the records. We design and implement a platform for managing provenance tracking of Electronic Healthcare Records based on blockchain technology, compliant with the latest healthcare standards and following the patient-informed consent preferences.
METHODS: The platform leverages two pillars: the use of international standards such as Integrating the Healthcare Enterprise (IHE), Health Level Seven International (HL7) and Fast Healthcare Interoperability Resources (FHIR) to achieve interoperability, and the use of a provenance creation process that by-design, avoids personal data storage within the blockchain. The platform consists of: (1) a smart contract implemented within the Hyperledger Fabric blockchain that manages provenance according to the W3C PROV for medical document in standardised formats (e.g. a CDA document, a FHIR resource, a DICOM study, etc.); (2) a Java Proxy that intercepts all the document submissions and retrievals for which provenance shall be evaluated; (3) a service used to retrieve the PROV document.
RESULTS: We integrated our decentralised platform with the SpiritEHR engine, an enterprise-grade healthcare system, and we stored and retrieved the available documents in the Mandel's sample CDA repository,1 which contained no protected health information. Using a cloud-based blockchain solution, we observed that the overhead added to the typical processing time of reading and writing medical data is in the order of milliseconds. Moreover, the integration of the Proxy at the level of exchanged messages in EHR systems allows transparent usage of provenance data in multiple health computing domains such as decision making, data reconciliation, and patient consent auditing.
CONCLUSIONS: By using international healthcare standards and a cloud-based blockchain deployment, we delivered a solution that can manage provenance of patients' records via transparent integration within the routine operations on healthcare data.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Blockchain; Data provenance; FHIR; Healthcare; Interoperability

Year:  2020        PMID: 32540775     DOI: 10.1016/j.ijmedinf.2020.104197

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  5 in total

Review 1.  HL7 FHIR-based tools and initiatives to support clinical research: a scoping review.

Authors:  Stephany N Duda; Nan Kennedy; Douglas Conway; Alex C Cheng; Viet Nguyen; Teresa Zayas-Cabán; Paul A Harris
Journal:  J Am Med Inform Assoc       Date:  2022-08-16       Impact factor: 7.942

2.  HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study.

Authors:  Ayan Chatterjee; Nibedita Pahari; Andreas Prinz
Journal:  Sensors (Basel)       Date:  2022-05-15       Impact factor: 3.847

3.  Healthchain: A novel framework on privacy preservation of electronic health records using blockchain technology.

Authors:  Shekha Chenthara; Khandakar Ahmed; Hua Wang; Frank Whittaker; Zhenxiang Chen
Journal:  PLoS One       Date:  2020-12-09       Impact factor: 3.240

4.  Approaches and Criteria for Provenance in Biomedical Data Sets and Workflows: Protocol for a Scoping Review.

Authors:  Kerstin Gierend; Frank Krüger; Dagmar Waltemath; Maximilian Fünfgeld; Thomas Ganslandt; Atinkut Alamirrew Zeleke
Journal:  JMIR Res Protoc       Date:  2021-11-22

5.  Lightweight Distributed Provenance Model for Complex Real-world Environments.

Authors:  Rudolf Wittner; Cecilia Mascia; Matej Gallo; Francesca Frexia; Heimo Müller; Markus Plass; Jörg Geiger; Petr Holub
Journal:  Sci Data       Date:  2022-08-17       Impact factor: 8.501

  5 in total

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