PT - JOURNAL ARTICLE AU - Tim A Holt AU - David Stables AU - Julia Hippisley-Cox AU - Shaun O'Hanlon AU - Azeem Majeed TI - Identifying undiagnosed diabetes: cross-sectional survey of 3.6 million patients' electronic records AID - 10.3399/bjgp08X277302 DP - 2008 Mar 01 TA - British Journal of General Practice PG - 192--196 VI - 58 IP - 548 4099 - http://bjgp.org/content/58/548/192.short 4100 - http://bjgp.org/content/58/548/192.full SO - Br J Gen Pract2008 Mar 01; 58 AB - Background Around 1% of the UK population has diabetes that is either undiagnosed or unrecorded on practice disease registers.Aim To estimate the number of people in UK primary care databases with biochemical evidence of undiagnosed diabetes. To develop simple practice-based search techniques to support early recognition of diabetes.Design of study Cross-sectional survey of 3 630 296 electronic records.Setting Four hundred and eighty UK practices contributing to the QRESEARCH database.Method Electronic searches to identify people with no diabetes diagnosis in one of two categories (A and B), using the most recently recorded blood glucose measurement: random blood glucose level ≥11.1 mmol/l or fasting blood glucose level ≥7.0 mmol/l (A); either a random or a fasting blood glucose level ≥7.0 mmol/l (B). An additional outcome measure was the proportion of the population with at least one blood glucose measurement in the record.Results The number (percentage) identified in category A was 3758 (0.10% of the total population); the number in category B was 32 785 (0.90%). Projected to a practice of 7000 patients, around eight patients have biochemical evidence of undiagnosed diabetes, and 68 have results suggesting the need for further follow-up. One-third of people aged over 40 years without diabetes have a blood glucose measurement in the past 2 years in their record.Conclusion People with possible undiagnosed diabetes are readily identifiable in UK primary care databases through electronic searches using blood glucose data. People with borderline levels, who may benefit from interventions to reduce their risk of progression to diabetes, can also be identified using practice-based software.