Background Type 2 diabetes (T2D) is a leading cause of both chronic kidney disease (CKD) and onward progression to end stage renal disease. Timely diagnosis coding of CKD in patients with T2D could lead to improvements in quality of care and patient outcomes.

Aim To assess the consistency between estimated glomerular filtration rate (eGFR) based evidence of CKD and CKD diagnosis coding in UK primary care.

Design and Setting A retrospective analysis of electronic health record data in a cohort of people with type 2 diabetes from 60 primary care centres within England between 2012 and 2022.

Method We estimated the incidence rate of CKD per 100 person-years using eGFR-based CKD and diagnosis codes. Logistic regression was applied to establish which attributes were associated with diagnosis coding. Time from eGFR-based CKD to entry of a diagnosis code was summarised using the median and interquartile range.

Results The overall incidence of CKD was 2.32 (95% CI: 2.24, 2.41) and significantly different between eGFR-based criteria and diagnosis codes: 1.98 (95% CI: 1.90, 2.05) vs 1.06 (95% CI: 1.00, 1.11) respectively; p<0.001. Only 46% of CKD incidences identified using eGFR-based criteria had a corresponding diagnosis code. Younger patients, patients with a higher severity CKD stage, and patients with an observed urine-albumin-to-creatinine ratio were more likely to have a diagnosis code.

Conclusion Diagnosis coding of patients with eGFR-based evidence of CKD in UK primary care is poor within patients with type 2 diabetes, despite CKD being a well-known complication of diabetes.

How this fits in Type 2 diabetes is a recognised cause of chronic kidney disease (CKD), and early identification and management of CKD can reduce the risk of progression and related complications. Diagnosis coding of CKD is associated with better patient outcomes, yet we have observed that less than half of patients with type 2 diabetes who meet eGFR-based criteria for stage 3-5 CKD have a CKD diagnosis code in their primary care record. There is a need to understand why CKD diagnosis coding practices are subpar in primary care and this research acts as a call-to-action to improve.

The authors have declared no competing interest.

This study was funded by Gendius Ltd.

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