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Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Chronic kidney disease in type 2 diabetes in UK primary care: Testing frequency, coding accuracy and clinical inertia
A Zafar1,2,3, C Scarlata1,3, N Jaleel4
1NIHR Leicestershire and Northamptonshire Commercial Research Delivery Centre, Leicester, UK.
Aims/Hypothesis:
To identify gaps and inconsistencies in the coding and testing of chronic kidney disease (CKD) among people with type 2 diabetes mellitus in UK primary care by evaluating clinical inertia in those with reduced estimated glomerular filtration rate (eGFR) and/or elevated urine albumin-creatinine ratio (uACR) levels.
Methods:
We conducted a retrospective cross-sectional analysis using SystmOne and the PARM Diabetes tool. A cohort from two primary care settings was screened to identify type 2 diabetes mellitus patients with eGFR <60 mL/min/1.73 m2 on two occasions. A retrospective analysis evaluated CKD coding accuracy per NICE guidelines, identifying gaps in coding and testing.
Results:
Significant variation was observed in CKD monitoring and diagnosis between the two settings. Overall, 77.3% had eGFR testing, and 37.6% had uACR testing within the past 12 months, with significantly higher testing rates in primary care setting one (urban) compared to primary care setting two (rural). Only 35% of patients received both tests within the past 12 months, with the lowest uptake among patients under 60 years (28%) and those with advanced CKD stages. Among patients with ≥2 eGFR readings <60 mL/min/1.73 m2, 61% remained uncoded for CKD if they had exactly two readings, compared to 15% uncoded among those with more than two. Coding rates increased with age but did not differ significantly between settings.
Conclusions:
The study emphasises the need for increased uACR testing and CKD coding in type 2 diabetes mellitus patients to ensure accurate monitoring and management. Fluctuating eGFR/ACR levels and process issues may contribute to clinical inertia. These findings specifically highlight gaps in CKD monitoring and diagnosis, particularly in younger patients and rural settings. We recommend healthcare professionals review coding practices and follow CKD guidelines to improve patient outcomes.
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