Variation in tests for people with type 2 diabetes, hypertension, or chronic kidney disease in UK primary care

Objective: Clinical guidelines for people with diabetes recommend chronic kidney disease (CKD) testing at least annually using estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio (uACR). We aimed to understand CKD testing among people with type 2 diabetes in the United States. Research Design and Methods: Electronic health record data were analyzed from 513,165 adults with type 2 diabetes, receiving primary care from 24 health care organizations and 1,164 clinical practice sites. We assessed the percentage of patients with both ≥1 eGFR and ≥1 uACR, <a></a><a>and each test</a> individually, in the 1, 2, and 3 years ending September 2019, by health care organization and clinical practice site. Elevated albuminuria was defined by uACR ≥30 mg/g. Results: The 1-year median testing rate across organizations was 51.6% for both uACR and eGFR, 89.5% for eGFR, and 52.9% for uACR. uACR testing varied (10th–90th percentile) from 44.7% to 63.3% across organizations and from 13.3% to 75.4% across sites. Over 3 years, the median testing rate for uACR across organizations was 73.7%. Overall, the prevalence of detected elevated albuminuria was 15%. The average prevalence of detected elevated albuminuria increased linearly with uACR testing rates at sites, with estimated prevalence of 6%, 15%, and 30%, at uACR testing rates of 20%, 50%, and 100%. Conclusions: While eGFR testing rates are uniformly high among people with type 2 diabetes, testing rates for uACR are suboptimal and highly variable across and within the organizations examined. Guideline-recommended uACR testing should increase detection of CKD.

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Chronic Kidney Disease Testing Among Primary Care Patients With Type 2 Diabetes Across 24 U.S. Health Care Organizations

10.2337/figshare.14669748 ◽

2021 ◽

Author(s):

Nikita Stempniewicz ◽

Joseph A. Vassalotti ◽

John K. Cuddeback ◽

Elizabeth Ciemins ◽

Amy Storfer-Isser ◽

...

Keyword(s):

Type 2 Diabetes ◽

Primary Care ◽

Health Care ◽

Chronic Kidney Disease ◽

Clinical Practice ◽

Kidney Disease ◽

Health Care Organizations ◽

The United States ◽

Testing Rate

Objective: Clinical guidelines for people with diabetes recommend chronic kidney disease (CKD) testing at least annually using estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio (uACR). We aimed to understand CKD testing among people with type 2 diabetes in the United States. Research Design and Methods: Electronic health record data were analyzed from 513,165 adults with type 2 diabetes, receiving primary care from 24 health care organizations and 1,164 clinical practice sites. We assessed the percentage of patients with both ≥1 eGFR and ≥1 uACR, <a></a><a>and each test</a> individually, in the 1, 2, and 3 years ending September 2019, by health care organization and clinical practice site. Elevated albuminuria was defined by uACR ≥30 mg/g. Results: The 1-year median testing rate across organizations was 51.6% for both uACR and eGFR, 89.5% for eGFR, and 52.9% for uACR. uACR testing varied (10th–90th percentile) from 44.7% to 63.3% across organizations and from 13.3% to 75.4% across sites. Over 3 years, the median testing rate for uACR across organizations was 73.7%. Overall, the prevalence of detected elevated albuminuria was 15%. The average prevalence of detected elevated albuminuria increased linearly with uACR testing rates at sites, with estimated prevalence of 6%, 15%, and 30%, at uACR testing rates of 20%, 50%, and 100%. Conclusions: While eGFR testing rates are uniformly high among people with type 2 diabetes, testing rates for uACR are suboptimal and highly variable across and within the organizations examined. Guideline-recommended uACR testing should increase detection of CKD.

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Prediction of type 2 diabetes risk in people with non-diabetic hyperglycaemia: model derivation and validation using UK primary care data

BMJ Open ◽

10.1136/bmjopen-2020-037937 ◽

2020 ◽

Vol 10 (10) ◽

pp. e037937

Author(s):

Briana Coles ◽

Kamlesh Khunti ◽

Sarah Booth ◽

Francesco Zaccardi ◽

Melanie J Davies ◽

...

Keyword(s):

Type 2 Diabetes ◽

Primary Care ◽

Prognostic Models ◽

Predictor Variables ◽

Validation Dataset ◽

Practice Research ◽

Clinical Practice Research Datalink ◽

Primary Care Data

ObjectiveUsing primary care data, develop and validate sex-specific prognostic models that estimate the 10-year risk of people with non-diabetic hyperglycaemia developing type 2 diabetes.DesignRetrospective cohort study.SettingPrimary care.Participants154 705 adult patients with non-diabetic hyperglycaemia.Primary outcomeDevelopment of type 2 diabetes.MethodsThis study used data routinely collected in UK primary care from general practices contributing to the Clinical Practice Research Datalink. Patients were split into development (n=109 077) and validation datasets (n=45 628). Potential predictor variables, including demographic and lifestyle factors, medical and family history, prescribed medications and clinical measures, were included in survival models following the imputation of missing data. Measures of calibration at 10 years and discrimination were determined using the validation dataset.ResultsIn the development dataset, 9332 patients developed type 2 diabetes during 293 238 person-years of follow-up (31.8 (95% CI 31.2 to 32.5) per 1000 person-years). In the validation dataset, 3783 patients developed type 2 diabetes during 115 113 person-years of follow-up (32.9 (95% CI 31.8 to 33.9) per 1000 person-years). The final prognostic models comprised 14 and 16 predictor variables for males and females, respectively. Both models had good calibration and high levels of discrimination. The performance statistics for the male model were: Harrell’s C statistic of 0.700 in the development and 0.701 in the validation dataset, with a calibration slope of 0.974 (95% CI 0.905 to 1.042) in the validation dataset. For the female model, Harrell’s C statistics were 0.720 and 0.718, respectively, while the calibration slope was 0.994 (95% CI 0.931 to 1.057) in the validation dataset.ConclusionThese models could be used in primary care to identify those with non-diabetic hyperglycaemia most at risk of developing type 2 diabetes for targeted referral to the National Health Service Diabetes Prevention Programme.

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