title: Wide variation in the number of different drugs prescribed by general practitioners. A prescription database study.
abstract: OBJECTIVE
  To investigate the number of different drugs prescribed per dispensing unit and to analyse the influence of practice characteristics on this number.
  
  
  METHODS
  Register analysis based on the Odense Pharmacoepidemiological Database (OPED).
  
  
  METHODS
  General practices in the County of Funen, Demnark.
  
  
  METHODS
  173 general practices (99 single-handed and 74 group practices).
  
  
  METHODS
  Number of different drugs prescribed per dispensing unit.
  
  
  RESULTS
  The number of different drugs prescribed per dispensing unit varied nearly fourfold (range 102-381) and four practice characteristics were able to predict 74% of this variation. Practices with several doctors, a high number of patients listed per doctor, a high percentage of elderly individuals, and a heavy workload showed the highest number of different drugs prescribed.
  
  
  CONCLUSIONS
  As the quality of drug prescribing is associated with the use of a limited number of drugs, it is suggested that GPs should agree on a formulary containing the most essential drugs in primary health care.
authors.affiliation: Research Unit of General Practice, University of Southern Denmark, Odense.
authors.forename: L
authors.initials: L
authors.lastname: Bjerrum
authors.forename: U
authors.initials: U
authors.lastname: Bergman
mesh_terms: D000367:Age Factors; D000368:Aged; D016208:Databases, Factual; D003718:Denmark; D004346:Drug Information Services; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D004363:Drug Utilization / Q000706:statistics & numerical data*; D005194:Family Practice / Q000706:statistics & numerical data*; D005260:Female; D006123:Group Practice / Q000706:statistics & numerical data; D006302:Health Services Research; D006801:Humans; D008297:Male; D008875:Middle Aged; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D012042:Registries; D012044:Regression Analysis; D016526:Workload