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Avid Wijaya, Diniyah Kholidah, Elystia Vidia Marselina

Medical Record and Health Information Department, Poltekkes Kemenkes Malang, Kota Malang, Jawa Timur, Indonesia

Correspondence: Avid Wijaya, Poltekkes Kemenkes Malang, Jl. Besar Ijen 77C, Malang, Indonesia, Email [email protected]

View the original paper by Dr Cook and colleagues

Dear editor

The article “Recording of Alcohol Use Disorder in Electronic Health Records: Developing a Recommended Codelist for Research” provides valuable insights into the challenges and solutions in identifying Alcohol Use Disorder (AUD) through electronic health records (EHRs).1 Its main merit lies in developing a standardized codelist to enhance research quality using the CPRD Aurum database. However, the study’s methodology, while transparent, has limitations. The reliance on moderate inter-coder agreement (Kappa = 0.72) highlights subjective interpretation in categorizing codes. The decision to prioritize specificity over sensitivity may lead to underestimating AUD cases, especially since the trade-off between the two is influenced by the prevalence of the condition being tested. The concept of balanced accuracy needs to consider that the relationship between sensitivity and specificity is dynamic and influenced by the underlying prevalence of the condition.2 The dynamic nature of EHR coding practices, influenced by evolving terminology and clinician preferences, poses another challenge. The proposed solution includes complementing quantitative validation with a qualitative study involving general practitioners to refine the coding framework and ensure its implementation across various clinical settings. While quantitative methodology is important for establishing reliability and validity, a mixed approach with qualitative analysis is necessary to understand the contextual factors affecting clinical practices and to enhance the validity of healthcare service instruments.3 Expanding efforts to integrate non-stigmatizing language in EHR coding will also improve the usability of the codelist while supporting future research into complex conditions like AUD.

Disclosure

The authors report no conflicts of interest in this communication.

References

1. Cook S, Osborn D, Maini A, et al. Recording of alcohol use disorder in electronic health records: developing a recommended codelist for research. Clin Epidemiol. 2024;16:673–681. doi:10.2147/CLEP.S477778

2. Guesné SJJ, Hanser T, Werner S, Boobier S, Scott S. Mind your prevalence! J Cheminform. 2024;16(1):43. doi:10.1186/s13321-024-00837-w

3. Garcia LG, Gil MFH, Valcárcel MDR, et al. Design of an instrument to measure midwives’ workloads based on nursing interventions classification. Texto & Contexto - Enfermagem. 2024;33:e20230120. doi:10.1590/1980-265X-TCE-2023-0120en

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