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UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER.
Denaxas, Spiros; Gonzalez-Izquierdo, Arturo; Direk, Kenan; Fitzpatrick, Natalie K; Fatemifar, Ghazaleh; Banerjee, Amitava; Dobson, Richard J B; Howe, Laurence J; Kuan, Valerie; Lumbers, R Tom; Pasea, Laura; Patel, Riyaz S; Shah, Anoop D; Hingorani, Aroon D; Sudlow, Cathie; Hemingway, Harry.
Afiliación
  • Denaxas S; Institute of Health Informatics, University College London, London,United Kingdom.
  • Gonzalez-Izquierdo A; Health Data Research UK, London, United Kingdom.
  • Direk K; The Alan Turing Institute, London, United Kingdom.
  • Fitzpatrick NK; The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, United Kingdom.
  • Fatemifar G; British Heart Foundation Research Accelerator, University College London, London, United Kingdom.
  • Banerjee A; Institute of Health Informatics, University College London, London,United Kingdom.
  • Dobson RJB; Health Data Research UK, London, United Kingdom.
  • Howe LJ; The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, United Kingdom.
  • Kuan V; Institute of Health Informatics, University College London, London,United Kingdom.
  • Lumbers RT; Health Data Research UK, London, United Kingdom.
  • Pasea L; The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, United Kingdom.
  • Patel RS; Institute of Health Informatics, University College London, London,United Kingdom.
  • Shah AD; Health Data Research UK, London, United Kingdom.
  • Hingorani AD; Institute of Health Informatics, University College London, London,United Kingdom.
  • Sudlow C; Health Data Research UK, London, United Kingdom.
  • Hemingway H; Institute of Health Informatics, University College London, London,United Kingdom.
J Am Med Inform Assoc ; 26(12): 1545-1559, 2019 12 01.
Article en En | MEDLINE | ID: mdl-31329239
ABSTRACT

OBJECTIVE:

Electronic 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

METHODS:

We 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.

RESULTS:

Using 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.

CONCLUSIONS:

We 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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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Algoritmos / Almacenamiento y Recuperación de la Información / Registros Electrónicos de Salud Tipo de estudio: Diagnostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Algoritmos / Almacenamiento y Recuperación de la Información / Registros Electrónicos de Salud Tipo de estudio: Diagnostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido