dc.contributor.author | Lid, Torgeir Gilje | en_US |
dc.contributor.author | Eide, Geir Egil | en_US |
dc.contributor.author | Dalen, Ingvild | en_US |
dc.contributor.author | Meland, Eivind | en_US |
dc.date.accessioned | 2016-12-30T14:05:36Z | |
dc.date.available | 2016-12-30T14:05:36Z | |
dc.date.issued | 2016 | |
dc.Published | Scandinavian Journal of Primary Health Care 2016, 34(3):215-223 | eng |
dc.identifier.issn | 1502-7724 | |
dc.identifier.uri | https://hdl.handle.net/1956/15322 | |
dc.description.abstract | Objective: To explore whether information regarding potentially alcohol-related health incidents recorded in electronic patient records might aid in earlier identification of alcohol use disorders. Design: We extracted potentially alcohol-related information in electronic patient records and tested if alcohol-related diagnoses, prescriptions of codeine, tramadol, ethylmorphine, and benzodiazepines; elevated levels of gamma-glutamyl-transferase (GGT), and mean cell volume (MCV); and new sick leave certificates predicted specific alcohol use disorder. Setting: Nine general practitioner surgeries with varying size and stability. Subjects: Totally 20,764 patients with active electronic patient record until data gathering and with a history of at least four years without a specific alcohol use disorder after turning 18 years of age. Methods: The Cox proportional hazard analysis with time-dependent covariates of potential accumulated risks over the previous four years. Main outcome measures: Time from inclusion until the first specific alcohol use disorder, defined by either an alcohol specific diagnostic code or a text fragment documenting an alcohol problem. Results: In the unadjusted and adjusted Cox-regression with time-dependent covariates all variables were highly significant with adjusted hazard ratios ranging from 1.25 to 3.50. Addictive drugs, sick leaves, GGT, MCV and International Classification for Primary Care version 2 (ICPC-2), and International Classification of Diseases version 10 (ICD-10) diagnoses were analyzed. Elevated GGT and MCV, ICD-10-diagnoses, and gender demonstrated the highest hazard ratios. Conclusions: Many frequent health problems are potential predictors of an increased risk or vulnerability for alcohol use disorders. However, due to the modest hazard ratios, we were unable to establish a clinically useful tool. | en_US |
dc.language.iso | eng | eng |
dc.publisher | Taylor & Francis | eng |
dc.rights | Attribution CC BY-NC | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | eng |
dc.subject | Alcohol-related disorders | eng |
dc.subject | computerized patient records | eng |
dc.subject | early diagnosis | eng |
dc.subject | General practice | eng |
dc.subject | Norway | eng |
dc.title | Can routine information from electronic patient records predict a future diagnosis of alcohol use disorder? | en_US |
dc.type | Peer reviewed | |
dc.type | Journal article | |
dc.date.updated | 2016-12-14T10:46:12Z | |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | Copyright 2016 The Author(s) | |
dc.identifier.doi | https://doi.org/10.1080/02813432.2016.1207138 | |
dc.identifier.cristin | 1392764 | |