Background UK primary care records are computerised and these records are used for both research and quality improvement. However, there is disparity in the prevalence of diabetes found in epidemiological studies compared with that reported through the UK's national quality improvement scheme. Objective To investigate how non-diagnostic computer data could be used to identify, confirm or refute prevalent cases of people with diabetes. Method We carried out a literature review to identify the most accurate non-diagnostic markers. For each type of diabetes we focused on four broad areas; demographic details, biochemical markers, clinical features and therapeutic strategies. Sample markers were tested by calculating their positive predictive value (PPV) and sensitivity (Sn) and their ability to differentiate between types of diabetes. Results Biochemical markers were useful in identifying cases of diabetes but not in differentiating between types of diabetes as the same plasma glucose criterion is used to diagnose Type 1, Type 2, and 'other' types of diabetes; the lack of a 'fasting' qualifier blunts the use of this marker.Auto-immune markers were the most accurate in identifying Type 1 diabetes but are not recorded frequently in primary care.
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