Institute of Health Informatics, University College London, London,United Kingdom.
Health Data Research UK, London, United Kingdom.
J Am Med Inform Assoc. 2019 Dec 1;26(12):1545-1559. doi: 10.1093/jamia/ocz105.
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.
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.
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.
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.
电子健康记录（EHR）是人类疾病信息的丰富来源，但信息结构多样、碎片化，使用不同的编码系统进行整理，并出于医疗研究以外的目的而收集。我们描述了一种从英国国家结构化 EHR 中开发、验证和共享可重复表型的方法，该方法可应用于转化研究。
我们实施了基于规则的表型框架，最多有 6 种验证方法。我们将我们的框架应用于英格兰住院和死亡记录链接的全国性电子健康记录数据源（基于人群的初级保健，所有年龄段）中的 1500 万个体样本。数据包括连续测量值（例如血压、药物信息、编码诊断、症状、程序和转诊），使用 5 种受控临床术语进行记录：（1）读取（初级保健，SNOMED-CT[系统医学术语临床术语]的子集），（2）国际疾病分类第九版和第十版（二级保健诊断和死亡率原因），（3）人口普查和调查办公室手术和程序分类第四版（医院手术程序），以及（4）DM+D 处方代码。
使用 CALIBER 表型框架，我们为 51 种疾病、综合征、生物标志物和生活方式风险因素创建了算法，并提供了多达 6 种验证方法。EHR 表型在开放访问的 CALIBER 门户（https://www.caliberresearch.org/portal）中进行管理，并已被 40 个国家和国际研究小组在 60 篇同行评议出版物中使用。
我们在 CALIBER EHR 数据平台内描述了一种英国 EHR 表型学方法，并初步证明了其有效性和使用，这是朝着国际使用英国 EHR 数据进行健康研究迈出的重要一步。
