Aim To examine two methods of extracting risks for undetected type 2 diabetes (T2D): derived from electronic medical record (EMR) and family medicine (FM) assessment during pre-consultation phase. All risks were structured in three lists of patients’ data using Wonca International Classification Committee (WICC). Missing data were detected in each list. Methods A prospective study included a group of 1883 patients (aged 45-70) identified with risks. Risks were assessed based on EMR for continuity variables and FM’s assessment for episodes of disease and personal related information. Patients were categorized with final diagnostic test in normoglycaemia, impaired fasting glycaemia and undetected T2D. Results Total prevalence of diabetes was 10.9% (new 1.4%), of which 59.3% were females; mean age was 57.4. The EMR risks were hypertension in 1274 patients (yes 67.6%, no 27.9%, missing 4.4%), hypolipemic treatment in 690 (yes 36.6%, no 30.9%, miss 32.5%). In the episodes of disease: gestational diabetes mellitus in 31 women (yes 2.8%, missing 97.2%). Personal information: family history of diabetes in 649 (yes 34.5%, no 12.4%, missing 53.1%), overweight in 1412 (yes 75.0%, no 8.4%, missing 16.6%), giving birth to babies >4000g in 11 women (yes 0.9%, missing 99.1%). Overweight alone was the best predictor for undiagnosed type 2 diabetes, OR: 2.11 (CI: 1.41-3.15) (p<.001). Conclusion Two methods of extraction could not detect data for episodes of the disease. In the list of personal information, FMs could not assess overweight for one in six patients and family history for every other patient. The study can stimulate improving coded and structured data in EMR.