Evidence map›Paper›PMID 36451210›Full record

ArticleBMC medical ethics2022

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

James Scheibner, Marcello Ienca, Effy Vayena

Abstract read
In one paragraph

Article in BMC medical ethics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Attitudes towards data access and sharing health data for research: a case study of Australian data custodian perspectives.Health information management : journal of the Health Information Management Association of Australia · 2026
    Article
  2. Review
  3. Body Surface Potential Mapping: A Perspective on High-Density Cutaneous Electrophysiology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

James ScheibnerHealth Ethics and Policy Laboratory, Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zurich, Switzerland.
Marcello IencaHealth Ethics and Policy Laboratory, Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zurich, Switzerland.
Effy VayenaHealth Ethics and Policy Laboratory, Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zurich, Switzerland. effy.vayena@hest.ethz.ch.

Funding

Personalized Health and Related Technologies Program 2017-201
6 · The paper itself

Abstract

backgroundIncreasingly, 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.

methodsTo 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.

resultsFor 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.

conclusionOur findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies.

Indexed as

PrivacyTechnologyDissent and DisputesEthics, ResearchHumansQualitative ResearchData protectionDistributed ledger technologyHomomorphic encryptionInterviewsPrivacy preserving technologiesQualitative researchVignettes

Identifiers

PMID36451210
PMCPMC9713155

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.