Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study
 
research article

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

Scheibner, James
•
Ienca, Marcello  
•
Vayena, Effy
December 1, 2022
Bmc Medical Ethics

Background: Increasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorphic encryption allows computations to be performed on data without this data ever being decrypted. Therefore, homomorphic encryption represents a potential solution for conducting feasibility studies on cohorts of sensitive patient data stored in distributed locations. Distributed ledger technology provides a permanent record on all transfers and processing of patient data, allowing data custodians to audit access. A significant portion of the current literature has examined how these technologies might comply with data protection and research ethics frameworks. In the Swiss context, these instruments include the Federal Act on Data Protection and the Human Research Act. There are also institutional frameworks that govern the processing of health related and genetic data at different universities and hospitals. Given Switzerland's geographical proximity to European Union (EU) member states, the General Data Protection Regulation (GDPR) may impose additional obligations. Methods: To conduct this assessment, we carried out a series of qualitative interviews with key stakeholders at Swiss hospitals and research institutions. These included legal and clinical data management staff, as well as clinical and research ethics experts. These interviews were carried out with two series of vignettes that focused on data discovery using homomorphic encryption and data erasure from a distributed ledger platform. Results: For our first set of vignettes, interviewees were prepared to allow data discovery requests if patients had provided general consent or ethics committee approval, depending on the types of data made available. Our interviewees highlighted the importance of protecting against the risk of reidentification given different types of data. For our second set, there was disagreement amongst interviewees on whether they would delete patient data locally, or delete data linked to a ledger with cryptographic hashes. Our interviewees were also willing to delete data locally or on the ledger, subject to local legislation. Conclusion: Our findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies.

  • Details
  • Metrics
Type
research article
DOI
10.1186/s12910-022-00852-2
Web of Science ID

WOS:000892998800001

Author(s)
Scheibner, James
Ienca, Marcello  
Vayena, Effy
Date Issued

2022-12-01

Publisher

BMC

Published in
Bmc Medical Ethics
Volume

23

Issue

1

Start page

121

Subjects

Ethics

•

Medical Ethics

•

Social Sciences, Biomedical

•

Social Sciences - Other Topics

•

Biomedical Social Sciences

•

data protection

•

privacy preserving technologies

•

qualitative research

•

vignettes

•

interviews

•

distributed ledger technology

•

homomorphic encryption

•

data protection regulation

•

genetic data

•

blockchain

•

gdpr

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
SHS-ENS  
Available on Infoscience
December 19, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/193340
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés