Evidence map›Paper›PMID 33629963›Full record

ArticleJournal of medical Internet research2021

Revolutionizing Medical Data Sharing Using Advanced Privacy-Enhancing Technologies: Technical, Legal, and Ethical Synthesis.

James Scheibner, Jean Louis Raisaro, Juan Ramón Troncoso-Pastoriza, Marcello Ienca, Jacques Fellay, Effy Vayena, Jean-Pierre Hubaux

Abstract readMulticenter Study
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 3 pooled it
–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

49 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

7 authors.

James ScheibnerHealth Ethics and Policy Laboratory, Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zürich, Switzerland.ORCID 0000-0003-3667-398X
Jean Louis RaisaroPrecision Medicine Unit, Lausanne University Hospital, Lausanne, Switzerland.ORCID 0000-0003-2052-6133
Juan Ramón Troncoso-PastorizaLaboratory for Data Security, School of Computer and Communication Sciences, École polytechnique fédérale de Lausanne, Lausanne, Switzerland.ORCID 0000-0001-8764-5570
Marcello IencaHealth Ethics and Policy Laboratory, Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zürich, Switzerland.ORCID 0000-0001-8835-5444
Jacques FellayPrecision Medicine Unit, Lausanne University Hospital, Lausanne, Switzerland.ORCID 0000-0002-8240-939X
Effy VayenaHealth Ethics and Policy Laboratory, Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zürich, Switzerland.ORCID 0000-0003-1303-5467
Jean-Pierre HubauxLaboratory for Data Security, School of Computer and Communication Sciences, École polytechnique fédérale de Lausanne, Lausanne, Switzerland.ORCID 0000-0003-1533-6132

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data utility. The shortcomings of traditional privacy-enhancing technologies mean that institutions rely upon bespoke data sharing contracts. The lengthy process and administration induced by these contracts increases the inefficiency of data sharing and may disincentivize important clinical treatment and medical research. This paper provides a synthesis between 2 novel advanced privacy-enhancing technologies-homomorphic encryption and secure multiparty computation (defined together as multiparty homomorphic encryption). These privacy-enhancing technologies provide a mathematical guarantee of privacy, with multiparty homomorphic encryption providing a performance advantage over separately using homomorphic encryption or secure multiparty computation. We argue multiparty homomorphic encryption fulfills legal requirements for medical data sharing under the European Union's General Data Protection Regulation which has set a global benchmark for data protection. Specifically, the data processed and shared using multiparty homomorphic encryption can be considered anonymized data. We explain how multiparty homomorphic encryption can reduce the reliance upon customized contractual measures between institutions. The proposed approach can accelerate the pace of medical research while offering additional incentives for health care and research institutes to employ common data interoperability standards.

Indexed as

Computer SecurityHumansInformation DisseminationPrivacyTechnologyanonymizationcentralized approachdata governancedata privacydata protectiondata sharingdecentralized approachencryptionethicsfederated approachGDPRGeneral Data Protection RegulationInteroperabilitypatient data privacyprivacypseudonymizationresearch

Identifiers

PMID33629963
PMCPMC7952236

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.