ArticleJournal of the American Medical Informatics Association : JAMIA2016
PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability.
Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05277116 (The Electronic Medical Records and GEnomics), which is not on this map. Cited by 250 papers, 3 of them syntheses that pooled 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.
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.
The Electronic Medical Records and GEnomics (eMERGE) Network Genomic Risk Assessment
Who cites it
250 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A Systematic Review to Summarize and Critically Appraise Existing Phenotype Libraries Using Electronic Health Records.Pharmacoepidemiology and drug safety · 2026Pooled it
- Assessing the readiness of digital data infrastructure for opioid use disorder research.Addiction science & clinical practice · 2020Pooled it
- Association of Thyroid Function Genetic Predictors With Atrial Fibrillation: A Phenome-Wide Association Study and Inverse-Variance Weighted Average Meta-analysis.JAMA cardiology · 2019Pooled it
- An electronic health record (EHR) phenotype algorithm to identify patients with attention deficit hyperactivity disorders (ADHD) and psychiatric comorbidities.Journal of neurodevelopmental disorders · 2022Trial
- AI-based multimodal integration of genomics and electronic health records.Nature reviews. Genetics · 2026Review
- Electronic Health Record-Based Phenotyping for Obsessive-Compulsive Disorder: Algorithm Development and Multicenter Validation Study.JMIR mental health · 2026Article
- Longitudinal Digital Phenotyping of Traditional Chinese Medicine Constitution From Routine Health Examination Records: Retrospective Clinical Informatics Study.JMIR medical informatics · 2026Article
- Conditional Perplexity Scoring for Large Language Model-Generated Differential Diagnoses in Case Reports: Preliminary Computational Evaluation.JMIR formative research · 2026Article
- A comparison of Fast Healthcare Interoperability Resources and Observational Medical Mutcomes Partnership electronic health record data within the All of Us Research Program.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Computable phenotypes for research using real-world data: experiences from the NIH pragmatic trials collaboratory.JAMIA open · 2026Article
- Measuring the Impact of Data Quality and Computable Phenotypes on Potential Racial Disparities in Predicting Healthcare Utilization Among Type 2 Diabetes Populations.Journal of racial and ethnic health disparities · 2026Article
- Introducing the TOP framework: a novel phenotyping solution for collaborative phenotype algorithm development and application.Journal of biomedical semantics · 2026Article
- Natural language processing to enhance rheumatoid arthritis care in clinical studies: a scoping review of applications, data, approaches, challenges and future directions.Rheumatology international · 2026Article
- Development of phenotype algorithms for the detection of adverse events in electronic health record data: a multicentre study.BMJ open · 2026Article
- Assessing the quality of electronic health record data and the claims linked data for target trial emulation studies.JAMIA open · 2026Article
- Evaluating the feasibility of the CIPHER metadata framework towards building a conceptual phenotype standard.JAMIA open · 2026Article
- Cardiovascular-Kidney-Metabolic Syndrome: Development of anJMIR diabetes · 2026Article
- Evaluating Large Language Models for Translating Multimodal Phenotype Documentations into Executable EHR Phenotyping Algorithms.Research square · 2026Article
- Evaluating Large Language Models for Translating Multimodal Phenotype Documentations into Executable EHR Phenotyping Algorithms.medRxiv : the preprint server for health sciences · 2026Article
- Evaluation of the genome-informed risk assessment (GIRA) approach from eMERGE in an independent health system.medRxiv : the preprint server for health sciences · 2026Article
190 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
objectiveHealth care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby identifying valid cases and controls. These algorithms achieve the greatest utility when validated and shared by multiple health care systems.Materials and Methods We report the current status and impact of the Phenotype KnowledgeBase (PheKB, http://phekb.org), an online environment supporting the workflow of building, sharing, and validating electronic phenotype algorithms. We analyze the most frequent components used in algorithms and their performance at authoring institutions and secondary implementation sites.
resultsAs of June 2015, PheKB contained 30 finalized phenotype algorithms and 62 algorithms in development spanning a range of traits and diseases. Phenotypes have had over 3500 unique views in a 6-month period and have been reused by other institutions. International Classification of Disease codes were the most frequently used component, followed by medications and natural language processing. Among algorithms with published performance data, the median PPV was nearly identical when evaluated at the authoring institutions (n = 44; case 96.0%, control 100%) compared to implementation sites (n = 40; case 97.5%, control 100%). DISCUSSION: These results demonstrate that a broad range of algorithms to mine electronic health record data from different health systems can be developed with high PPV, and algorithms developed at one site are generally transportable to others.
conclusionBy providing a central repository, PheKB enables improved development, transportability, and validity of algorithms for research-grade phenotypes using health care generated data.
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What OpenQuestion holds
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.