Open Heart (Jan 2024)

Review of codelists used to define hypertension in electronic health records and development of a codelist for research

  • Jennifer Kathleen Quint,
  • Christopher Denton,
  • Fasihul Khan,
  • Iain Stewart,
  • Gisli Jenkins,
  • Ali-Reza Mohammadi-Nejad,
  • Dorothee Auer,
  • Karen Piper Hanley,
  • Michael Nation,
  • Harley H Y Kwok,
  • Jane Paxton,
  • Elizabeth Robertson,
  • Anna Duckworth,
  • Chris Scotton,
  • Aloysious Aravinthan,
  • Hilary Longhurst,
  • Mujdat Zeybel,
  • Louise V Wain,
  • Philip W Stone,
  • Richard J Allen,
  • Maria Kaisar,
  • Lisa Chakrabarti,
  • Georgie May Massen,
  • Andrew Thorley,
  • Anthony Harbottle,
  • Armando Mendez Villalon,
  • Daniel Lea,
  • Ebrima Joof,
  • Eleanor Cox,
  • Elizabeth Eves,
  • Emma Blamont,
  • Gina Parcesepe,
  • Gordon W. Moran,
  • Guruprasad P. Aithal,
  • Kate Frost,
  • Leo Casmino,
  • Margot Roeth,
  • Martin Craig,
  • Mohammad Alireza Kisomi

DOI
https://doi.org/10.1136/openhrt-2024-002640
Journal volume & issue
Vol. 11, no. 1

Abstract

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Background and aims Hypertension is a leading risk factor for cardiovascular disease. Electronic health records (EHRs) are routinely collected throughout a person’s care, recording all aspects of health status, including current and past conditions, prescriptions and test results. EHRs can be used for epidemiological research. However, there are nuances in the way conditions are recorded using clinical coding; it is important to understand the methods which have been applied to define exposures, covariates and outcomes to enable interpretation of study findings. This study aimed to identify codelists used to define hypertension in studies that use EHRs and generate recommended codelists to support reproducibility and consistency.Eligibility criteria Studies included populations with hypertension defined within an EHR between January 2010 and August 2023 and were systematically identified using MEDLINE and Embase. A summary of the most frequently used sources and codes is described. Due to an absence of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) codelists in the literature, a recommended SNOMED CT codelist was developed to aid consistency and standardisation of hypertension research using EHRs.Findings 375 manuscripts met the study criteria and were eligible for inclusion, and 112 (29.9%) reported codelists. The International Classification of Diseases (ICD) was the most frequently used clinical terminology, 59 manuscripts provided ICD 9 codelists (53%) and 58 included ICD 10 codelists (52%). Informed by commonly used ICD and Read codes, usage recommendations were made. We derived SNOMED CT codelists informed by National Institute for Health and Care Excellence guidelines for hypertension management. It is recommended that these codelists be used to identify hypertension in EHRs using SNOMED CT codes.Conclusions Less than one-third of hypertension studies using EHRs included their codelists. Transparent methodology for codelist creation is essential for replication and will aid interpretation of study findings. We created SNOMED CT codelists to support and standardise hypertension definitions in EHR studies.