Detection and management of alcohol use disorders in German primary care influenced by non-clinical factors

Alcohol Alcohol. Jul-Aug 2007;42(4):308-16. doi: 10.1093/alcalc/agm013. Epub 2007 May 17.


Aims: The primary objective was to assess the proportion of detected and correctly referred patients in German primary care. The secondary objective was to identify patient and practitioner characteristics that predict detection and correct referral.

Methods: In this clustered cross-sectional survey in German primary care, 3003 patients were consecutively invited to participate, and were asked to fill in a standardized health questionnaire. They were then screened for problematic alcohol consumption using the Alcohol Use Disorders Identification Test. The physicians recorded their assessment of the presence of any alcohol use disorder and documented the treatment course of all identified patients for 3 months.

Results: Correctly identified problem drinkers were 38.6% in a per-protocol analysis and 33.6% using a worst-case scenario. Referral behaviour of physicians was in conformity with current practice guidelines in 64.6% of the documented cases and 27.0% in a worst-case scenario. Several patient (e.g. sex, age) and practitioner characteristics (e.g. age), which influence the diagnosis and referral of patients, could be identified.

Conclusions: There is a clear need to increase the special diagnostic and therapeutic skills of general practitioners so that they may be able to indicate and perform secondary prevention. Further research should focus on the likely effects of the implementation of these diagnostic and management tools.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Alcoholism / diagnosis*
  • Alcoholism / epidemiology
  • Alcoholism / therapy*
  • Analysis of Variance
  • Female
  • Germany / epidemiology
  • Guidelines as Topic
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Primary Health Care / statistics & numerical data*
  • Quality Control
  • Referral and Consultation
  • Socioeconomic Factors