Identifying undiagnosed diabetes: cross-sectional survey of 3.6 million patients' electronic records
Holt, Tim A., Stables, David, Hippisley-Cox, Julia, O'Hanlon, Shaun and Majeed, Azeem. (2008) Identifying undiagnosed diabetes: cross-sectional survey of 3.6 million patients' electronic records. British Journal of General Practice, Vol.58 (No.548). pp. 192-196. ISSN 0960-1643Full text not available from this repository.
Official URL: http://dx.doi.org/10.3399/bjgp08X277302
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.
|Item Type:||Journal Article|
|Divisions:||Faculty of Medicine > Warwick Medical School|
|Journal or Publication Title:||British Journal of General Practice|
|Publisher:||Royal College of General Practitioners|
|Number of Pages:||5|
|Page Range:||pp. 192-196|
|Access rights to Published version:||Restricted or Subscription Access|
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