title: Data quality improvement in general practice.
abstract: BACKGROUND
  The importance of routine data generated by GPs has grown extensively in the last decade. These data have found many applications other than patient care. More attention has therefore been given to the issue of data quality. Several systematic reviews have detected ample space for improvement of data quality. A new review was conducted in order to find out which methods of improvement are effective.
  
  
  METHODS
  The Medline database was searched using an iteratively composed set of terms and MeSH (Medical Subject Headings) headings. Only papers that focused on explicit attempts at improving data quality of medical records in general practice were included.
  
  
  RESULTS
  Twelve studies met the inclusion criteria. No study used patient-based comparison of records with external sources as the method to assess data quality improvement. Ten studies used internal indicators or markers of data quality instead. Attempts at data quality improvement often involve some sort of individualized feedback, and nearly all attempts seem to have some positive effect. Only one of the included studies fulfilled the basic methodological requirements of an intervention study. The most recent studies used a simple before-after design.
  
  
  CONCLUSIONS
  No intervention to improve data quality has been put to a rigorous enough test. We still lack empirical knowledge as to how improvement can be brought about.
authors.affiliation: Division of Clinical Information and Public Health, Department of General Practice, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. h.j.brouwer@amc.uva.nl
authors.forename: H J
authors.initials: HJ
authors.lastname: Brouwer
authors.forename: P J E
authors.initials: PJ
authors.lastname: Bindels
authors.forename: H C
authors.initials: HC
authors.lastname: Weert
mesh_terms: D003625:Data Collection / Q000379:methods*; D005194:Family Practice / Q000458:organization & administration* / Q000706:statistics & numerical data; D005568:Forms and Records Control / Q000592:standards*; D006801:Humans; D008499:Medical Records / Q000592:standards*; D011786:Quality Control; D012107:Research Design / Q000592:standards*; D017749:Total Quality Management