Identifying levels of alcohol use disorder severity in electronic health records.

IF 3 3区医学 Q2 SUBSTANCE ABUSE

Substance Abuse Treatment, Prevention, and Policy Pub Date : 2025-09-08 DOI:10.1186/s13011-025-00670-w

Jakob Manthey, Carolin Kilian, Ludwig Kraus, Ingo Schäfer, Anna Schranz, Bernd Schulte

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Abstract

Background: Alcohol use disorder (AUD) is conceptualized as a dimensional phenomenon in the DSM-5, but electronic health records (EHRs) rely on binary AUD definitions according to the ICD-10. The present study classifies AUD severity levels using EHR data and tests whether increasing AUD severity levels are linked with increased comorbidity.

Methods: Billing data from two German statutory health insurance companies in Hamburg included n = 21,954 adults diagnosed with alcohol-specific conditions between 2017 and 2021. Based on ICD-10 alcohol-specific diagnoses, patients were classified into five AUD severity levels: 1 (F10.0, T51.0 or T51.9); 2 (F10.1); 3 (F10.2); 4 (F10.3/4); 5 (K70 + or one of the following diagnoses: K70.0-4, K70.9, K85.2, K85.20, K86.0, 10.5-9, E24.4, G31.2, G62.1, G72.1, I42.6, K29.2). Generalized estimating equation regression models for count data (Poisson distribution) were used to assess associations with the Elixhauser Comorbidity Score (ECS).

Results: Across the study period, the annual prevalence of any AUD diagnosis varied between 2.7% and 2.9%. A dose-response relationship was observed between AUD severity and ECS, indicating that individuals with higher AUD severity experience more comorbid conditions, particularly cardiovascular and liver diseases.

Conclusions: The proposal to define AUD severity levels based on ICD-10 diagnoses allows for a more nuanced analysis of AUD in EHR data.

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在电子健康记录中确定酒精使用障碍的严重程度。

背景：在DSM-5中，酒精使用障碍（AUD）被定义为一种维度现象，但根据ICD-10，电子健康记录（EHRs）依赖于二元AUD定义。本研究使用电子病历数据对澳元严重程度进行分类，并检验澳元严重程度的增加是否与合并症的增加有关。方法：来自汉堡两家德国法定健康保险公司的账单数据包括2017年至2021年间诊断为酒精特异性疾病的n = 21,954名成年人。根据ICD-10酒精特异性诊断，将患者分为5个AUD严重程度：1 (F10.0、T51.0或T51.9)；2 (F10.1);3 (F10.2);4 (F10.3/4);5 （K70 +或以下诊断之一：K70.0-4、K70.9、K85.2、K85.20、K86.0、10.5-9、E24.4、G31.2、G62.1、G72.1、I42.6、K29.2）。使用计数数据（泊松分布）的广义估计方程回归模型来评估与Elixhauser共病评分（ECS）的关联。结果：在整个研究期间，任何AUD诊断的年患病率在2.7%至2.9%之间变化。AUD严重程度与ECS之间存在剂量-反应关系，表明AUD严重程度较高的个体会出现更多合并症，特别是心血管和肝脏疾病。结论：基于ICD-10诊断定义AUD严重程度的建议允许对EHR数据中的AUD进行更细致的分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Substance Abuse Treatment, Prevention, and Policy Medicine-Health Policy

CiteScore

5.20

自引率

0.00%

发文量

审稿时长

19 weeks

期刊介绍： Substance Abuse Treatment, Prevention, and Policy is an open access, peer-reviewed journal that encompasses research concerning substance abuse, with a focus on policy issues. The journal aims to provide an environment for the exchange of ideas, new research, consensus papers, and critical reviews, to bridge the established fields that share a mutual goal of reducing the harms from substance use. These fields include: legislation pertaining to substance use; correctional supervision of people with substance use disorder; medical treatment and screening; mental health services; research; and evaluation of substance use disorder programs.