Recording of Alcohol Use Disorder in Electronic Health Records: Developing a Recommended Codelist for Research

Clin Epidemiol. 2024 Oct 4:16:673-681. doi: 10.2147/CLEP.S477778. eCollection 2024.

Abstract

Purpose: Electronic health records (EHR) are valuable resources for health research; however, their use is challenging. A validated alcohol use disorder (AUD) codelist for UK primary care is needed to improve population-based research in this patient group. We aimed to develop an AUD codelist for use in the Clinical Practice Research Datalink (CPRD) Aurum database, a UK EHR primary-care database.

Methods: The CPRD code browser was searched using keywords related to alcohol use using a previously developed search strategy. The resulting codes were categorised as AUD if they were: a) diagnostic of AUD, b) indicated alcohol withdrawal, or c) indicated chronic alcohol-related harm (physical or mental). Codes related to alcohol use but not used to define AUD were also classified into relevant categories (alcohol status, acute harm, and alcohol screening). All codes were categorised independently by at least two reviewers (one person reviewed all codes and five reviewers (all practising GPs) each reviewed a subset of codes (100-200 codes each). Disagreements in categorisation were discussed by at least three coders and a consensus was reached. The reliability of categorisation was assessed using kappa statistics.

Results: In total, 556 potential codes related to alcohol use were identified. The Kappa for reliability between coders was moderate for both AUD (0.72) and across all categories (0.62), with substantial variability between coders (AUD: 0.33-0.97; all categories 0.36-0.74). In the final codelist, 138 codes were included as indicating AUD: 38 codes identified which indicated diagnosis of AUD, 14 indicating withdrawal plus 85 codes indicating chronic alcohol-related harm (41 physical health and 44 mental health).

Conclusion: Many codes are used in primary care to record alcohol use and associated harms, and there is substantial variability in how clinicians categorise them. While future work formally validating the codelist against gold standard clinical reviews and qualitative work with General Practitioners is needed for a deeper understanding of coding processes, we have documented here the process used for the development of an AUD codelist within primary care which can be used as a reference for future research.

Keywords: alcohol use disorder; clinical practice research datalink; electronic health records; primary care.

Grants and funding

SC was funded by an NIHR Three Research Schools Mental Health Fellowship for this work. This Fellowship (MH055) was funded as part of the Three NIHR Research Schools Mental Health Programme. SS is funded by the National Institute for Health and Care Research (NIHR) Senior Investigator Award, NIHR School for Public Health Research (SPHR) (grant number: NIHR 204000), NIHR Northwest London Applied Research Collaboration, and Imperial NIHR Biomedical Research Centre. The NIHR SPHR is a partnership between the Universities of Bristol, Cambridge, and Sheffield; Imperial; University College London; the London School of Hygiene and Tropical Medicine; LiLaC — a collaboration between the Universities of Liverpool and Lancaster; and Fuse — the Centre for Translational Research in Public Health, a collaboration between Newcastle, Durham, Northumbria, Sunderland, and Teesside Universities. TB is supported by a grant from the Wellcome Trust. SG is funded by the NIHR School for Public Health Research and NIHR Northwest London Applied Research Collaboration. ALN is funded by the NIHR Northwest London Applied Research Collaborationand NIHR Northwest London Patient Safety Research Collaboration. Infrastructure for this research was supported by the NIHR Imperial Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.