title: Evaluating the performance of the Framingham Diabetes Risk Scoring Model in Canadian electronic medical records.
abstract: OBJECTIVE
  The objective of this study was to evaluate the performance of the Framingham Diabetes Risk Scoring Model (FDRSM) in a Canadian population, using the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database.
  
  
  METHODS
  We analyzed the records of 571 631 patients, between the ages of 45 and 64, between 2002 and 2005, by extracting the most recent laboratory and examination results, including age, sex, body mass index, fasting blood glucose, high-density lipoprotein, triglycerides and blood pressure. We calculated the risk scores of these patients based on the FDRSM. We tracked these patients for 8 years to find out whether or not they were diagnosed with diabetes. We used the area under the receiver operating characteristics curve (AROC) to estimate the discrimination capability of the FDRSM on our study sample and compared it with the AROC reported in the original Framingham diabetes study.
  
  
  RESULTS
  The AROC for our main research sample of 1970 patients for whom all risk factors and follow-up data were available was 78.6% compared to the AROC of 85% reported in the FDRSM. We found that 70.1% of our main sample had risks lower than 3%; 16.3% had risks between 3% and 10%; and 13.6% had risks greater than 10% for diabetes over the following 8-year period.
  
  
  CONCLUSIONS
  The discrimination capability of the FDRSM Canadian electronic medical records is fair. However, building a more accurate model for predicting diabetes based on the characteristics of Canadian patients is highly recommended.
authors.affiliation: Ted Rogers School of Information Technology Management, Ryerson University, Toronto, Ontario, Canada. Electronic address: Morteza.mashayekhi@ryerson.ca.
authors.forename: Morteza
authors.initials: M
authors.lastname: Mashayekhi
authors.affiliation: Ted Rogers School of Information Technology Management, Ryerson University, Toronto, Ontario, Canada.
authors.forename: Franklyn
authors.initials: F
authors.lastname: Prescod
authors.affiliation: Ted Rogers School of Information Technology Management, Ryerson University, Toronto, Ontario, Canada.
authors.forename: Bharat
authors.initials: B
authors.lastname: Shah
authors.affiliation: Ted Rogers School of Information Technology Management, Ryerson University, Toronto, Ontario, Canada.
authors.forename: Linying
authors.initials: L
authors.lastname: Dong
authors.affiliation: InfoClin Inc, Toronto, Ontario, Canada; University of Victoria, School of Health Informatics, Victoria, British Columbia, Canada.
authors.forename: Karim
authors.initials: K
authors.lastname: Keshavjee
authors.affiliation: Ted Rogers School of Information Technology Management, Ryerson University, Toronto, Ontario, Canada.
authors.forename: Aziz
authors.initials: A
authors.lastname: Guergachi
mesh_terms: D000328:Adult; D000368:Aged; D002170:Canada / Q000453:epidemiology; D003920:Diabetes Mellitus / Q000175:diagnosis* / Q000453:epidemiology*; D057286:Electronic Health Records / Q000145:classification*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods*; D055815:Young Adult
keywords: Canadian population; Framingham offspring study; diabetes mellitus; diabète sucré; dossiers médicaux électroniques; electronic medical records; population canadienne; prediabetes; prédiabète; étude Framingham offspring study