ArticleJournal of the American Medical Informatics Association : JAMIA2011
A secure protocol for protecting the identity of providers when disclosing data for disease surveillance.
Article in Journal of the American Medical Informatics Association : JAMIA, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Combining Geospatial Analysis with Dementia Risk Utilising General Practice Data: A Systematic Review.The journal of prevention of Alzheimer's disease · 2018Pooled it
- Privacy technology to support data sharing for comparative effectiveness research: a systematic review.Medical care · 2013Pooled it
- The Role of Trust as a Driver of Private-Provider Participation in Disease Surveillance: Cross-Sectional Survey From Nigeria.JMIR public health and surveillance · 2024Article
- New Approach to Privacy-Preserving Clinical Decision Support Systems for HIV Treatment.Journal of medical systems · 2022Article
- Privacy-preserving dataset combination and Lasso regression for healthcare predictions.BMC medical informatics and decision making · 2021Article
- EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Private Hospital Workflow Optimization via Secure k-Means Clustering.Journal of medical systems · 2019Article
- Fair compute loads enabled by blockchain: sharing models by alternating client and server roles.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation.JMIR medical informatics · 2018Article
- Geospatial cryptography: enabling researchers to access private, spatially referenced, human subjects data for cancer control and prevention.Journal of geographical systems · 2017Article
- Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation.BMC medical informatics and decision making · 2017Article
- Secure surveillance of antimicrobial resistant organism colonization or infection in Ontario long term care homes.PloS one · 2014Article
- Sharing data for the public good and protecting individual privacy: informatics solutions to combine different goals.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- Clinical research informatics: a conceptual perspective.Journal of the American Medical Informatics Association : JAMIA · 2012Article
- Preserving Institutional Privacy in Distributed binary Logistic Regression.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2012Article
- Article
- Physician privacy concerns when disclosing patient data for public health purposes during a pandemic influenza outbreak.BMC public health · 2011Article
- Grid Binary LOgistic REgression (GLORE): building shared models without sharing data.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundProviders have been reluctant to disclose patient data for public-health purposes. Even if patient privacy is ensured, the desire to protect provider confidentiality has been an important driver of this reluctance.
methodsSix requirements for a surveillance protocol were defined that satisfy the confidentiality needs of providers and ensure utility to public health. The authors developed a secure multi-party computation protocol using the Paillier cryptosystem to allow the disclosure of stratified case counts and denominators to meet these requirements. The authors evaluated the protocol in a simulated environment on its computation performance and ability to detect disease outbreak clusters.
resultsTheoretical and empirical assessments demonstrate that all requirements are met by the protocol. A system implementing the protocol scales linearly in terms of computation time as the number of providers is increased. The absolute time to perform the computations was 12.5 s for data from 3000 practices. This is acceptable performance, given that the reporting would normally be done at 24 h intervals. The accuracy of detection disease outbreak cluster was unchanged compared with a non-secure distributed surveillance protocol, with an F-score higher than 0.92 for outbreaks involving 500 or more cases.
conclusionThe protocol and associated software provide a practical method for providers to disclose patient data for sentinel, syndromic or other indicator-based surveillance while protecting patient privacy and the identity of individual providers.
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Registered trials
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.