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Cited by 828Blockchain Technology Applications and SecurityElectronic Health Records SystemsBlockchain Technology in Education and Learning

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Blockchain Technology for Healthcare: Facilitating the Transition to Patient-Driven Interoperability

Open access
Gordon, William J., Catalini, Christian·2018·Computational and Structural Biotechnology Journal
DOI 10.1016/j.csbj.2018.06.003PMC PMC6068317
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Abstract

Interoperability in healthcare has traditionally been focused around data exchange between business entities, for example, different hospital systems. However, there has been a recent push towards patient-driven interoperability, in which health data exchange is patient-mediated and patient-driven. Patient-centered interoperability, however, brings with it new challenges and requirements around security and privacy, technology, incentives, and governance that must be addressed for this type of data sharing to succeed at scale. In this paper, we look at how blockchain technology might facilitate this transition through five mechanisms: (1) digital access rules, (2) data aggregation, (3) data liquidity, (4) patient identity, and (5) data immutability. We then look at barriers to blockchain-enabled patient-driven interoperability, specifically clinical data transaction volume, privacy and security, patient engagement, and incentives. We conclude by noting that while patient-driving interoperability is an exciting trend in healthcare, given these challenges, it remains to be seen whether blockchain can facilitate the transition from institution-centric to patient-centric data sharing.

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Crossref · 10.1016/j.csbj.2018.06.003

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Fig. 1 (A) Example of institution-driven interoperability for clinical EHR data. Bi-directional clinical data exchange occurs (i) through an intermediary like a Regional Health Information Organization (RHIO) or (ii) directly between health care organizations with specific business agreements. In both cases, data interfaces are entity-to-entity, not entity-to-patient. In this example, since organization #2 and #3 do not have a specific relationship, there is no bi-directional data flow; providers from organization #2 can request data from organization #3 via one-off requests (like a fax). If a patient receives care at all three organizations, their health data will be scattered across all three EHRs. (B) Example of patient-driven interoperability. Data sharing centers on the patient; in this example, using patient-facing APIs, a patient can directly retrieve their clinical EHR data from organization #1 and organization #3. Once retrieved, the patient can share with other organizations directly. Data flow can be bidirectional. RHIOs and entity-to-entity relationships may still exist as parallel functions. (C) Blockchain-enabled patient-driven interoperability. In this example, the patient can still retrieve data directly from organization #2; however, through blockchain-enabled smart contracts, the patient can authorize sharing of clinical EHR data between organization #2 and organization #3, which do not have a formal business relationship. The blockchain layer stores these authorization rules, along with patient public keys (to ensure entity resolution), as well as data access audit logs. Each organization will manage linking a patient's public key to their own internal enterprise master patient index system independently, and patients can update the smart contract-driven authorization rules as appropriate (for example, adding a new institution if they are seeing a new provider).
Fig. 1 (A) Example of institution-driven interoperability for clinical EHR data. Bi-directional clinical data exchange occurs (i) through an intermediary like a Regional Health Information Organization (RHIO) or (ii) directly between health care organizations with specific business agreements. In both cases, data interfaces are entity-to-entity, not entity-to-patient. In this example, since organization #2 and #3 do not have a specific relationship, there is no bi-directional data flow; providers from organization #2 can request data from organization #3 via one-off requests (like a fax). If a patient receives care at all three organizations, their health data will be scattered across all three EHRs. (B) Example of patient-driven interoperability. Data sharing centers on the patient; in this example, using patient-facing APIs, a patient can directly retrieve their clinical EHR data from organization #1 and organization #3. Once retrieved, the patient can share with other organizations directly. Data flow can be bidirectional. RHIOs and entity-to-entity relationships may still exist as parallel functions. (C) Blockchain-enabled patient-driven interoperability. In this example, the patient can still retrieve data directly from organization #2; however, through blockchain-enabled smart contracts, the patient can authorize sharing of clinical EHR data between organization #2 and organization #3, which do not have a formal business relationship. The blockchain layer stores these authorization rules, along with patient public keys (to ensure entity resolution), as well as data access audit logs. Each organization will manage linking a patient's public key to their own internal enterprise master patient index system independently, and patients can update the smart contract-driven authorization rules as appropriate (for example, adding a new institution if they are seeing a new provider).CC BY · PubMed Central

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Cites

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Research works printed but not linked: 9

  1. Health Affairs Health Policy Brief : Interoperability. : 2014.
  2. Office of the National Coordinator for Health Information Technology : Connecting health and care for the nation: A shared nationwide interoperability roadmap. : 2015.
  3. Julia Adler-Milstein. Moving past the EHR interoperability blame game. N Engl J Catal n.d. https://catalyst.nejm.org/ehr-interoperability-blame-game/ (accessed March 28 2018).
  4. Gordon W.J. Wright A. and Landman A.: Blockchain Technology in Health Care: Decoding the hype. NEJM Catal 2017; . https://catalyst.nejm.org/decoding-blockchain-technology-health/.
  5. Bipartisan Policy Center Health Information : Technology initiative. In: Clinician perspectives on electronic health information sharing for transitions of care. : 2012.
  6. Access of individuals to protected health information (45 CFR § 164.524). : 2014.
  7. Centers for Medicare & Medicaid Services (CMS) and HHS : Medicare and medicaid programs; electronic health record incentive program—Stage 3 and modifications to meaningful use in 2015 through 2017. : 2015.
  8. Ivan Drew: Moving toward a blockchain-based method for the secure storage of patient records, NIST/ONC. : 2016.
  9. Gordon W.J. and Landman A.: Secure, decentralized, interoperable medication reconciliation using the Blockchain. : NIST/ONC 2016.

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Metadata

Authors
Gordon, W. J., & Catalini, C.
Affiliations
  • Brigham and Women's Hospital (US)
  • National Bureau of Economic Research (US)
Corresponding author
Gordon, William J.
ORCID
Venue
Computational and Structural Biotechnology Journal
Publisher
American Association for the Advancement of Science (AAAS)
Published
2018-01
Volume
16
Pages
224-230
ISSN
2001-0370 (ISSN-L)
DOI
10.1016/j.csbj.2018.06.003
PMC
PMC6068317
OpenAlex
W2810476200
Cited by
828
References
34
Citations by year
2026: 52 · 2025: 80 · 2024: 94 · 2023: 126 · 2022: 151 · 2021: 135 · 2020: 112 · 2019: 78
FWCI
15.04
Type
journal article
Language
en
Open access
Licence
Locations
  • Computational and Structural Biotechnology Journal (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
Keywords
blockchain, health data sharing, data privacy, data security, patient identity, data immutability, data aggregation, patient engagement, incentives, governance, barriers to adoption

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