ArticleJournal of the American Medical Informatics Association : JAMIA2019
UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers, 1 of them a synthesis that pooled it.
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Who cites it
123 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review to Summarize and Critically Appraise Existing Phenotype Libraries Using Electronic Health Records.Pharmacoepidemiology and drug safety · 2026Pooled it
- Emulating a target trial in case-control designs: an application to statins and colorectal cancer.International journal of epidemiology · 2020Trial
- Harmonizing UK primary care prescription records for research: a case study in the UK biobank.JAMIA open · 2026Article
- Association between dietary inflammatory index, empirical dietary inflammatory patterns and the risk of Long COVID: a prospective cohort study.BMC public health · 2026Article
- Natural language processing of biomedical text to map and prioritize protein-disease associations in HFpEF.Computers in biology and medicine · 2026Article
- Accelerating real-world prediction and research in Alzheimer's: The M3AD study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- PhenoFit: a framework for determining computable phenotyping algorithm fitness for purpose and reuse.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Replication of COPD susceptibility loci in a large Chinese elderly population using a validated, multi-setting EHR phenotype.BMC pulmonary medicine · 2026Article
- Extending BEHRT to UK Biobank: assessing transformer model performance in clinical prediction.Frontiers in digital health · 2026Article
- Organ-specific proteomic aging clocks predict disease and longevity across diverse populations.Nature aging · 2026Article
- Machine learning-based predictions of healthcare contacts following emergency hospitalisation using electronic health records.NPJ digital medicine · 2025Article
- Evaluating transportability of in vitro cellular models to in vivo human phenotypes using gene perturbation data.Nature communications · 2025Article
- Long-term accrual of conditions following myocardial infarction: a study of disease trajectories in the Wales Multimorbidity e-Cohort.BMC medicine · 2025Article
- Estimating 10-Year Cardiovascular Disease Risk in Primary Prevention Using UK Electronic Health Records and a Hybrid Multitask BERT Model: Retrospective Cohort Study.JMIR medical informatics · 2025Article
- Phenotyping Neurodisability in Hospital Records in England: A National Birth Cohort Using Linked Administrative Data.Paediatric and perinatal epidemiology · 2025Article
- Atrial fibrillation development in the heart failure population from nationwide British linked electronic health records.ESC heart failure · 2025Article
- Missed opportunities to manage complex comorbidity of heart failure, type 2 diabetes mellitus and chronic kidney disease: a retrospective cohort study.Heart (British Cardiac Society) · 2025Article
- A computational framework for defining and validating reproducible phenotyping algorithms of 313 diseases in the UK Biobank.Scientific reports · 2025Article
- Robustly measuring multimorbidity using disparate linked datasets.Communications medicine · 2025Article
- Review
63 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
objectiveElectronic health records (EHRs) are a rich source of information on human diseases, but the information is variably structured, fragmented, curated using different coding systems, and collected for purposes other than medical research. We describe an approach for developing, validating, and sharing reproducible phenotypes from national structured EHR in the United Kingdom with applications for translational research. MATERIALS AND
methodsWe implemented a rule-based phenotyping framework, with up to 6 approaches of validation. We applied our framework to a sample of 15 million individuals in a national EHR data source (population-based primary care, all ages) linked to hospitalization and death records in England. Data comprised continuous measurements (for example, blood pressure; medication information; coded diagnoses, symptoms, procedures, and referrals), recorded using 5 controlled clinical terminologies: (1) read (primary care, subset of SNOMED-CT [Systematized Nomenclature of Medicine Clinical Terms]), (2) International Classification of Diseases-Ninth Revision and Tenth Revision (secondary care diagnoses and cause of mortality), (3) Office of Population Censuses and Surveys Classification of Surgical Operations and Procedures, Fourth Revision (hospital surgical procedures), and (4) DM+D prescription codes.
resultsUsing the CALIBER phenotyping framework, we created algorithms for 51 diseases, syndromes, biomarkers, and lifestyle risk factors and provide up to 6 validation approaches. The EHR phenotypes are curated in the open-access CALIBER Portal (https://www.caliberresearch.org/portal) and have been used by 40 national and international research groups in 60 peer-reviewed publications.
conclusionsWe describe a UK EHR phenomics approach within the CALIBER EHR data platform with initial evidence of validity and use, as an important step toward international use of UK EHR data for health research.
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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.