Screening for Alcohol Use Disorder Among Hospitalised Patients: Learning from a Retrospective Cohort Study in Secondary Care

Background: Excessive alcohol consumption is among the leading causes of hospitalisation in high-income countries and contributes to over 200 medical conditions. We aimed to determine the prevalence and characteristics of alcohol use disorder (AUD), describe the distribution of AUD in ICD-10 discharge diagnosis groups and ascertain any relationship between them in secondary care. Methods: The study group was a retrospective cohort of adult patients admitted to Nottingham University Hospital (NUH) between 4 April 2009 and 31 March 2020. Uni- and multivariable analysis was performed to determine the relationship between AUD and covariable high-risk characteristics and describe the distribution of AUD in ICD-10 discharge diagnosis groups defined by an alcohol-attributable fraction. Results: A total of 44,804 patients (66,440 admissions) were included, with a mean age of 63.1 years (SD ± 19.9); of these, 48.0% (n = 20,863) were male and 71.2% were (n = 30,994) white. AUDIT-C was completed in 97.1% (n = 43,514) of patients, and identified 16.5% (n = 7164) as having AUD, while 2.1% (n = 900) were found to be alcohol-dependent. In patients with AUD, 4.0% (n = 283) had an ICD-10 diagnosis that was alcohol-specific and 17.5% (n = 1255) were diagnosed with alcohol-related disorders; the remainder were not diagnosed with either disorder. Two-thirds (64.7%) of the patients with AUD had associated mental and behavioural disorders. Multivariable logistic regression analysis revealed that patients aged 60-69 had the highest risk of AUD (OR 4.19, 95% CI 3.53-4.99). Being single (OR 1.18, 95% CI 1.11-1.26) and a history of emergency admission (OR 1.21, 95% CI 1.14-1.29) were associated with increased odds of AUD. Conversely, females compared to males (OR 0.34, 95% CI 0.35-0.39), individuals from minority ethnic backgrounds compared to white Caucasians (OR 0.39, 95% CI 0.35-0.45), and those from more deprived areas (IMD quintile 1: OR 0.79, 95% CI 0.74-0.86) had lower odds of AUD. Conclusions: One in six admitted patients had AUD, with a higher risk in males, ages 60-69, and emergency admissions. Mental disorders are highly prevalent among hospitalised patients with AUD. The performance of the AUDIT-C score varied among hospitalised patients based on their ICD-10 diagnosis, which should be considered when implementing universal alcohol screening in these settings.