UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER

Author:

Denaxas Spiros12345,Gonzalez-Izquierdo Arturo124,Direk Kenan124,Fitzpatrick Natalie K12,Fatemifar Ghazaleh12,Banerjee Amitava125,Dobson Richard J B12645,Howe Laurence J7,Kuan Valerie27,Lumbers R Tom125,Pasea Laura12,Patel Riyaz S75,Shah Anoop D125,Hingorani Aroon D27,Sudlow Cathie89,Hemingway Harry1245

Affiliation:

1. Institute of Health Informatics, University College London, London,United Kingdom

2. Health Data Research UK, London, United Kingdom

3. The Alan Turing Institute, London, United Kingdom

4. The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, United Kingdom

5. British Heart Foundation Research Accelerator, University College London, London, United Kingdom

6. Department of Biostatistics and Health Informatics, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom

7. Institute of Cardiovascular Science, University College London, London, United Kingdom

8. Centre for Medical Informatics, Usher Institute of Population Health Science and Informatics, University of Edinburgh, Edinburgh, United Kingdom

9. Health Data Research UK, Scotland, United Kingdom

Abstract

AbstractObjectiveElectronic 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.

Funder

European Union's Horizon

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference96 articles.

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