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Multicenter Study
. 2008 Mar;58(548):192-6.
doi: 10.3399/bjgp08X277302.

Identifying undiagnosed diabetes: cross-sectional survey of 3.6 million patients' electronic records

Affiliations
Multicenter Study

Identifying undiagnosed diabetes: cross-sectional survey of 3.6 million patients' electronic records

Tim A Holt et al. Br J Gen Pract. 2008 Mar.

Abstract

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 >or=11.1 mmol/l or fasting blood glucose level >or=7.0 mmol/l (A); either a random or a fasting blood glucose level >or=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.

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Figures

Figure 1
Figure 1
Number and percentage of the study population in each diagnostic category.
Figure 2
Figure 2
Proportion of blood glucose measurements identified by strategies A and B according to time interval since the measurement.

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