Recording of alcohol use disorder in electronic health records: developing a recommended codelist for research
File(s)
Author(s)
Type
Journal Article
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.
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.
Date Issued
2024-10-04
Date Acceptance
2024-09-16
Citation
Clinical Epidemiology, 2024, 16
ISSN
1179-1349
Publisher
Dove Medical Press
Journal / Book Title
Clinical Epidemiology
Volume
16
Copyright Statement
© 2024 Cook et al. This work is published by Dove Medical Press Limited, and licensed under a Creative Commons Attribution License. The full terms of the License are
available at http://creativecommons.org/licenses/by/4.0/. The license permits unrestricted use, distribution, and reproduction in any medium, provided the original author
and source are credited.
available at http://creativecommons.org/licenses/by/4.0/. The license permits unrestricted use, distribution, and reproduction in any medium, provided the original author
and source are credited.
License URL
Identifier
https://www.dovepress.com/recording-of-alcohol-use-disorder-in-electronic-health-records-develop-peer-reviewed-fulltext-article-CLEP
Publication Status
Published
Date Publish Online
2024-10-04