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

Abstract

Sarah Cook,1 David Osborn,2,3 Arti Maini,1 Ravi Parekh,1 Shamini Gnani,1 Thomas Beaney,1 Ana Luisa Neves,1 Sonia Saxena,1 Jennifer K Quint1 1School of Public Health, Imperial College London, London, UK; 2Division of Psychiatry, University College London, London, UK; 3Camden and Islington NHS Foundation Trust, London, UKCorrespondence: Sarah Cook, White City Campus, Imperial College London, 9th Floor Michael Uren Building, London, W12 0BZ, UK, Email [email protected]: 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, electronic health records, primary care, clinical practice research datalink

Keywords

• alcohol use disorder
• electronic health records
• primary care
• clinical practice research datalink