title: Collecting information on the quality of prescribing in primary care using semi-automatic data extraction from GPs' electronic medical records.
abstract: OBJECTIVE
  To evaluate a semi-automatic data extraction from the electronic medical record (EMR) of general practitioners (GPs) through a comparison with a paper sheets data collection simultaneously used in a primary care research project on the quality of prescribing for osteoarthritis in the elderly.
  
  
  METHODS
  One hundred and fifty-two GPs using five different EMR-software systems participated with the semi-automatic data extraction from the EMR and 233 GPs collected data with paper registration sheets.
  
  
  METHODS
  The proportion of patients with respectively a drug prescription, paracetamol, a non-steroidal anti-inflammatory drug (NSAID) and ibuprofen were compared between the semi-automatic extraction and the paper data collection and among the EMR-software systems.
  
  
  RESULTS
  Using the semi-automatic data extraction, a significantly lower proportion of patients on drugs was obtained compared to the paper data collection (adjusted OR: 0.31; 95% CI 0.25-0.39). However, the proportion of patients on a specific type of drug was comparable. Within the results from the semi-automatic extraction, the results were heterogeneous among the different EMR-software systems.
  
  
  CONCLUSIONS
  The semi-automatic data extraction with multiple EMR-software systems proposed in this study seems suitable for quality of prescribing assessment in primary care. However, it may be less reliable when only a single EMR-software is used.
authors.affiliation: Scientific Institute of Public Health, Unit of Epidemiology, J. Wytsmanstraat 14, 1050 Brussels, Belgium. h.vandenberghe@iph.fgov.be
authors.forename: H E E
authors.initials: HE
authors.lastname: Vandenberghe
authors.forename: V
authors.initials: V
authors.lastname: Van Casteren
authors.forename: P
authors.initials: P
authors.lastname: Jonckheer
authors.forename: H
authors.initials: H
authors.lastname: Bastiaens
authors.forename: J
authors.initials: J
authors.lastname: Van der Heyden
authors.forename: M-F
authors.initials: MF
authors.lastname: Lafontaine
authors.forename: E
authors.initials: E
authors.lastname: De Clercq
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000627:therapeutic use; D001530:Belgium; D003625:Data Collection / Q000379:methods; D011307:Drug Prescriptions; D005260:Female; D006801:Humans; D008297:Male; D008485:Medical Audit; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D010003:Osteoarthritis / Q000188:drug therapy; D010821:Physicians, Family; D010818:Practice Patterns, Physicians'; D011787:Quality of Health Care
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal