title: Medical speciality and pattern of medicines prescription.
abstract: OBJECTIVE
  To describe the prescribing patterns and their quality in relation to the prescriber's medical specialty in a defined population.
  
  
  METHODS
  The study was done on a random sample of all primary care medical prescriptions made through the social security system during 1 year in Andorra, a small European country. Number and type of prescribed medicines, prescribers' medical speciality and patients' age and gender were recorded. Medical specialties considered were General Practice, Paediatrics, Cardiology, Pneumology, Gynaecology, Ophthalmology and Other. A set of various quality indicators [World Health Organisation (WHO)/International Network for Rational Use of Drugs (INRUD) indicators and others] was used.
  
  
  RESULTS
  The number of medicines prescribed per encounter varied depending on the prescriber's medical specialty and patient's age. Cardiologists and pneumologists tended to prescribe more medicines than other medical specialties. Patients older than 65 years received more prescriptions than younger adults, mostly at the expense of cardiovascular drugs. The contribution of the various groups and subgroups of medicines and the scores of various prescribing indicators showed wide variability across the medical specialties.
  
  
  CONCLUSIONS
  Prescribing patterns and indicators of prescription quality show wide variability depending on the prescriber's medical specialty. This has important implications for priority setting in information, continuous education and research.
authors.affiliation: Fundació Institut Català de Farmacologia, WHO Collaborating Centre for Research and Training in Pharmacoepidemiology, Department of Pharmacology, Therapeutics and Toxicology, Universitat Autònoma de Barcelona, Barcelona, Spain.
authors.forename: A
authors.initials: A
authors.lastname: Vallano
authors.forename: E
authors.initials: E
authors.lastname: Montané
authors.forename: J M
authors.initials: JM
authors.lastname: Arnau
authors.forename: X
authors.initials: X
authors.lastname: Vidal
authors.forename: C
authors.initials: C
authors.lastname: Pallarés
authors.forename: M
authors.initials: M
authors.lastname: Coll
authors.forename: J R
authors.initials: JR
authors.lastname: Laporte
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000725:Andorra; D002648:Child; D002675:Child, Preschool; D004363:Drug Utilization / Q000706:statistics & numerical data*; D017723:Drug Utilization Review / Q000379:methods; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D008511:Medicine / Q000706:statistics & numerical data*; D008875:Middle Aged; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D013038:Specialization