title: Assessment of the possibility to classify patients according to cholesterol guideline screening criteria using routinely recorded electronic patient record data.
abstract: BACKGROUND
  Computerised decision support systems (CDSS) can be categorised as either being inquisitive or non-inquisitive. The non-inquisitive system uses routinely entered electronic patient data, to generate patient specific feedback based on guidelines. The Dutch College of General Practitioners' (DCGP) cholesterol guideline classifies patients into risk groups, eligible for screening. The availability of sufficient routinely recorded electronic patient data to classify patients according to the DCGP cholesterol guideline is unknown.
  
  
  OBJECTIVE
  To assess whether it is possible to classify patients according to the screening criteria of the DCGP cholesterol guideline, using data routinely recorded by general practitioners.
  
  
  METHODS
  We analysed the DCGP cholesterol guideline to identify selection criteria for screening. These selection criteria were subsequently used to create a cohort of patient records eligible for screening in the Integrated Primary Care Information (IPCI) Database. We calculated incidence and prevalence of risk factors and selected patient records for active management according to the identified screening selection criteria.
  
  
  RESULTS
  145866 valid patient records were selected for classification. In the retrieved records 9741 (13.6%) males and 5756 (7.8%) females were identified for active management according to the selection criteria of the DCGP cholesterol guideline.
  
  
  CONCLUSIONS
  The classification of patients into risk groups, eligible for screening, according to the criteria of the DCGP cholesterol guideline using routinely recorded electronic patient data is feasible. Care should be taken when using only diagnostic codes, as it gives higher than expected incidence and prevalence of risk factors. Based on these findings we are currently building Cholgate, a non-inquisitive decision support system for cholesterol management.
authors.affiliation: Institute of Medical Informatics, Erasmus Medical Center, PO Box 1738, 3000 DR Rotterdam, The Netherlands.
authors.forename: J T
authors.initials: JT
authors.lastname: Van Wyk
authors.forename: M A M
authors.initials: MA
authors.lastname: Van Wijk
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D020000:Decision Support Systems, Clinical / Q000706:statistics & numerical data; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D006937:Hypercholesterolemia / Q000628:therapy*; D016247:Information Storage and Retrieval / Q000379:methods; D008297:Male; D008403:Mass Screening / Q000145:classification / Q000379:methods*; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*; D008875:Middle Aged; D009426:Netherlands; D010361:Patients / Q000145:classification*; D017410:Practice Guidelines as Topic; D018570:Risk Assessment / Q000379:methods