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Research Article

Can routine information from electronic patient records predict a future diagnosis of alcohol use disorder?

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Pages 215-223 | Received 09 Sep 2015, Accepted 27 Mar 2016, Published online: 12 Jul 2016

Figures & data

Table 1. Descriptive statistics for n = 20,764 patients from nine general practice surgeries in the Stavanger area in Norway accrued from March to August of 2011.

Table 2. Results from Cox regression of alcohol use disorder with time-dependent covariates for 20,764 patients from nine general practice surgeries in the Stavanger area in Norway accrued from March to August of 2011.

Figure 1. Receiver operator characteristics (ROC) curve for prognostic index (gender, elevated lab tests, class B-drugs, new sick leaves, and alcohol-related ICPC-2 and ICD-10 diagnoses), for n = 16,814 patients from the Stavanger area in Norway, for comprehensive alcohol use disorder. Abbreviations: ICD-10: International Classification of Diseases, version 10; ICPC-2: International Classification of Primary Care, version 2.

Figure 1. Receiver operator characteristics (ROC) curve for prognostic index (gender, elevated lab tests, class B-drugs, new sick leaves, and alcohol-related ICPC-2 and ICD-10 diagnoses), for n = 16,814 patients from the Stavanger area in Norway, for comprehensive alcohol use disorder. Abbreviations: ICD-10: International Classification of Diseases, version 10; ICPC-2: International Classification of Primary Care, version 2.