ArticleJournal of the American Medical Informatics Association : JAMIA2020
Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm.
Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 5 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
54 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Learning competing risks across multiple hospitals: one-shot distributed algorithms.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- One-shot distributed algorithms for addressing heterogeneity in competing risks data across clinical sites.Journal of biomedical informatics · 2024Pooled it
- Distributed Cox proportional hazards regression using summary-level information.Biostatistics (Oxford, England) · 2023Pooled it
- Distributed Quasi-Poisson regression algorithm for modeling multi-site count outcomes in distributed data networks.Journal of biomedical informatics · 2022Pooled it
- ODACH: a one-shot distributed algorithm for Cox model with heterogeneous multi-center data.Scientific reports · 2022Pooled it
- Privacy-enhancing sequential learning under heterogeneous selection bias in multi-site electronic health records data.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- PDA (Privacy-Preserving Distributed Algorithms) in action: ten principles for high-quality multi-site clinical evidence generation.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Temporal Variability in Diagnosis Code Distributions Across Extraction Time Points in a Multicenter Integrated EHR Database: A Snapshot Comparison Study.Journal of medical systems · 2026Observational
- Unlocking multi-institutional insights into disease progression with PEAL as a lossless, one-shot federated learning solution.NPJ digital medicine · 2026Article
- VALORIS: One-shot and lossless vertical logistic regression for privacy-protecting multi-site health analytics.Scientific reports · 2026Article
- Enabling the analysis of patient-level data across jurisdictions for research use: a real-world exploration of a federated likelihood approach.International journal of population data science · 2026Article
- Federated analytics for non-communicable disease surveillance in the European health data space: a scoping review and conceptual framework.Frontiers in public health · 2026Article
- Consideration of Sociodemographics in Sepsis Risk Prediction: Implications and Next Steps.Critical care medicine · 2025Article
- COLA-GLM: collaborative one-shot and lossless algorithms of generalized linear models for decentralized observational healthcare data.NPJ digital medicine · 2025Article
- Robust Privacy-Preserving Models for Cluster-Level Confounding: Recognizing Disparities in Access to Transplantation.Statistics in biosciences · 2025Article
- Federated target trial emulation using distributed observational data for treatment effect estimation.NPJ digital medicine · 2025Article
- Federated Target Trial Emulation using Distributed Observational Data for Treatment Effect Estimation.medRxiv : the preprint server for health sciences · 2025Article
- Communication-efficient federated learning of temporal effects on opioid use disorder with data from distributed research networks.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Federated Adaptive Causal Estimation (FACE) of Target Treatment Effects.Journal of the American Statistical Association · 2025Article
- DisCJournal of machine learning research : JMLR · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
objectivesWe propose a one-shot, privacy-preserving distributed algorithm to perform logistic regression (ODAL) across multiple clinical sites. MATERIALS AND
methodsODAL effectively utilizes the information from the local site (where the patient-level data are accessible) and incorporates the first-order (ODAL1) and second-order (ODAL2) gradients of the likelihood function from other sites to construct an estimator without requiring iterative communication across sites or transferring patient-level data. We evaluated ODAL via extensive simulation studies and an application to a dataset from the University of Pennsylvania Health System. The estimation accuracy was evaluated by comparing it with the estimator based on the combined individual participant data or pooled data (ie, gold standard).
resultsOur simulation studies revealed that the relative estimation bias of ODAL1 compared with the pooled estimates was <3%, and the ratio of standard errors was <1.25 for all scenarios. ODAL2 achieved higher accuracy (with relative bias <0.1% and ratio of standard errors <1.05). In real data analysis, we investigated the associations of 100 medications with fetal loss during pregnancy. We found that ODAL1 provided estimates with relative bias <10% for 85% of medications, and ODAL2 has relative bias <10% for 99% of medications. For communication cost, ODAL1 requires transferring p numbers from each site to the local site and ODAL2 requires transferring (p×p+p) numbers from each site to the local site, where p is the number of parameters in the regression model.
conclusionsThis study demonstrates that ODAL is privacy-preserving and communication-efficient with small bias and high statistical efficiency.
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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.