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

Abstract

Clinical guidelines for people with diabetes recommend chronic kidney disease (CKD) testing at least annually using estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (uACR). We aimed to understand CKD testing among people with type 2 diabetes in the U.S. RESEARCH DESIGN AND METHODSElectronic 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 one or more eGFRs and one or more uACRs and each test individually in the 1, 2, and 3 years ending September 2019 by health care organization and clinical practice site. Elevated albuminuria was defined as uACR $30 mg/g. RESULTSThe 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%, respectively. CONCLUSIONSWhile 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.In the U.S., one in nine adults have type 2 diabetes (1,2), and one-third of those also have chronic kidney disease (CKD), defined as decreased glomerular filtration rate (GFR) or elevated albuminuria (3-5). Most people with CKD are unaware of their condition (6,7), and, to improve identification, clinical guidelines recommend testing high-risk patients with estimated GFR (eGFR) from serum creatinine and urinary albumin-to-creatinine ratio (uACR) (8-10).

Albuminuria Testing in Hypertension and Diabetes: An Individual-Participant Data Meta-Analysis in a Global Consortium

“…25 We were 20) 38127 ( 15) 14689 ( 6) 2279 (1) 28 ( 5) 87 ( 15) 18742 (7) only able to examine Black-White racial differences in the associations between SBP and albuminuria in a subset of cohorts. Lastly, recent study showed that ACR testing rates varied across not only health care organizations but also practice sites in diabetes, 26 but we could not examine variation in ACR testing rates across provider types.…”

Integrating CKD Into US Primary Care: Bridging the Knowledge and Implementation Gaps

“…Routine primary care case finding for CKD with eGFR and uACR should focus on risk conditions, particularly; diabetes, hypertension, cardiovascular disease, and a family history of kidney disease, as recommended by clinical practice guidelines from the American Diabetes Association, 12 Kidney Disease: Improving Global Outcomes, 4 Kidney Disease Outcomes Quality Initiative, 5 and other organizations, in contrast to mass or general population screening. 13 , 14 In recent years in the United States, annual uACR testing is approximately 40% for diabetes and less than 10% for hypertension in national data sets from Medicare, 2 commercial insurance, 2 health systems, 15 and clinical laboratories, 16 supporting the need for interventions to improve targeted albuminuria testing. There are some challenges for clinicians to order uACR because laboratories do not universally offer the test and reporting formats vary, introducing inconsistencies and complexity in the interpretation of the results.…”

Facilitating a Patient-Centered Transition From Kidney Disease to Kidney Failure: Can Digital Tools Help?

“…2 Although allowing for a longer lookback period to ascertain laboratory results may increase the proportion of patients having complete data for risk prediction, the usefulness of predictions becomes more uncertain as it is based on increasingly remote data. 11 , 12 Although very few registry participants (29/1032; 2.8%) in this study had a missing risk score, the utility of prediction algorithms such as the Kidney Failure Risk Equation may be reduced if transported to less-resourced, nonintegrated health systems with less data availability. In these more fragmented care delivery settings, which often provide care for racially, ethnically, and linguistically diverse populations of low socioeconomic status, it will be crucial to verify that missingness does not systematically withhold care from high-risk patient populations who may be less likely to be tested due to suboptimal access to care.…”