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Background: While alcohol cessation improves mortality in alcoholic liver disease (ALD), many patients struggle to achieve abstinence. Our aim was to characterize ALD patients' preferences, misconceptions, and barriers to alcohol use treatment options., Methods: This mixed-methods study included outpatients with a history of alcohol-related cirrhosis or alcoholic hepatitis recruited from a hepatology clinic for a survey or an in-depth semi-structured interview. We purposefully sampled men and women, compensated and decompensated patients to ensure adequate representation of gender and severity of liver disease for the qualitative interviews., Results: 123 patients completed surveys among which 50% reported having at least one drink within the past year while only 20 patients were in any form of current alcohol treatment. Of the 23 patients reporting drinking within 3 months, only 3 were in AUD treatment currently. 17% had at least one misconception about alcohol use or treatment. An additional 22 ALD patients (10 women, 12 men) completed phone interviews of which two-third self-reported alcohol abstinence. All 22 interview participants had awareness of some form of alcohol treatment, but 13 felt that they did not need treatment with several characterizing it as ineffective or a "waste of time." Misconceptions included inaccurate perceptions of relapse medication side effects, beliefs that the presence of advanced liver disease symptoms means it is too late to treat alcohol use, and a lack of understanding about the chronicity of alcohol use disorders. The most common barriers to treatment included unwillingness to be in treatment, financial/insurance and transportation barriers., Conclusions: Alcohol use treatment was underutilized in many ALD patients, despite active drinking in many. Tailored education and preference sensitive treatment engagement may overcome barriers to alcohol use treatment and promote abstinence., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Preoperative risky alcohol use is one of the most common surgical risk factors. Accurate and early identification of risky alcohol use could enhance surgical safety. Artificial Intelligence‐based approaches, such as natural language processing (NLP), provide an innovative method to identify alcohol‐related risks from patients' electronic health records (EHR) before surgery. Methods: Clinical notes (n = 53,629) from pre‐operative patients in a tertiary care facility were analyzed for evidence of risky alcohol use and alcohol use disorder. One hundred of these records were reviewed by experts and labeled for comparison. A rule‐based NLP model was built, and we assessed the clinical notes for the entire population. Additionally, we assessed each record for the presence or absence of alcohol‐related International Classification of Diseases (ICD) diagnosis codes as an additional comparator. Results: NLP correctly identified 87% of the human‐labeled patients classified with risky alcohol use. In contrast, diagnosis codes alone correctly identified only 29% of these patients. In terms of specificity, NLP correctly identified 84% of the non‐risky cohort, while diagnosis codes correctly identified 90% of this cohort. In the analysis of the full dataset, the NLP‐based approach identified three times more patients with risky alcohol use than ICD codes. Conclusions: NLP, an artificial intelligence‐based approach, efficiently and accurately identifies alcohol‐related risk in patients' EHRs. This approach could supplement other alcohol screening tools to identify patients in need of intervention, treatment, and/or postoperative withdrawal prophylaxis. Alcohol‐related ICD diagnosis had limited utility relative to NLP, which extracts richer information within clinical notes to classify patients. [ABSTRACT FROM AUTHOR]