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Kidney Health Evaluation

CBE ID
4315e
Endorsement Status
E&M Committee Rationale/Justification

Not Endorsed due to No Consensus

1.0 New or Maintenance
Previous Endorsement Cycle
Is Under Review
No
1.6 Measure Description

Percentage of patients aged 18-85 years with a diagnosis of diabetes who received a kidney health evaluation defined by an Estimated Glomerular Filtration Rate (eGFR) AND Urine Albumin-Creatinine Ratio (uACR) within the 12-month measurement period

Measure Specs
General Information
1.7 Measure Type
1.7 Composite Measure
No
1.3 Electronic Clinical Quality Measure (eCQM)
1.8 Level of Analysis
1.9 Care Setting
1.10 Measure Rationale

Chronic Kidney Disease (CKD) is a major driver of morbidity, mortality and high healthcare costs in the United States. Currently, 37 million American adults have CKD and millions of others are at increased risk (National Kidney Foundation [NKF], 2022), with an estimated population prevalence growing to nearly 17% among Americans aged 30 years and older by the year 2030 (Saran et al., 2019; Hoerger et al., 2015). Total Medicare spending in 2016 on both CKD and End-Stage Renal Disease (ESRD) was over $114 billion, comprising 23% of total Medicare fee-for-service spending overall with costs increasing exponentially with advancing CKD (Saran et al., 2019; Nichols et al., 2020). In the US from 2002-2016, the burden of CKD, defined as years of life lost, years living with disability, disability-adjusted life years, and deaths, outpaced changes in the burden of disease for other conditions (Bowe et al., 2018). Patients with CKD are readmitted to the hospital more frequently than those without diagnosed CKD (Saran et al., 2019). CKD is the 9th leading cause of death in the US and is the fastest growing non-communicable disease in terms of in burden largely due to death (Hoerger et al., 2015; Bowe et al., 2018). This public health issue is driven largely by the impact of diabetes—the most common comorbid risk factor for CKD (Saran et al., 2019; Bowe et al., 2018).  

 

The intent of this process measure is to improve rates of guideline-concordant kidney health evaluation in patients with diabetes to more consistently identify and potentially treat or delay progression of CKD in this high-risk population. Annual kidney health evaluation in patients with diabetes to determine risk of CKD using estimated glomerular filtration rate (eGFR) and urine albumin creatinine ratio (uACR) is recommended by clinical practice guidelines (American Diabetes Association, 2023; de Boer, 2022; NKF, 2007; NKF, 2012) and has been a focus of various local and national health care quality improvement initiatives, including Healthy People 2030 (Healthy People 2030, 2023). However, performance of these tests in patients with diabetes remains low, with rates that vary across Medicare (41.8%) and private insurers (49.0%) (Saran et al., 2019; Alfego et al., 2021; Stempneiwicz et al., 2021). Low rates of detection of CKD in a population of patients with diabetes have been demonstrated to be associated with low patient awareness of their own kidney health status (Szczech et al., 2014). Indeed, 90% of individuals with CKD are unaware of their condition due to under-recognition and under-diagnosis (Saran, et al., 2019; Centers for Disease Control and Prevention, 2023). Currently, an individual’s lifetime probability of developing CKD is relatively high, reaching 54% for someone currently aged 30-49 years (Hoerger et al., 2015). Regular kidney health evaluations, utilizing both eGFR and uACR, provide an opportunity to improve identification and potential reversal of worsening kidney function, particularly in high risk populations, such as those with diabetes.

 

This measure replaces and improves upon the previous Merit-Based Incentive Program (MIPS) medical attention for nephropathy measure. This measure is more specific as it requires utilizing the eGFR and uACR tests to assess a patient’s kidney health. 

 

References:

 

Alfego, D., Ennis, J., Gillespie, B., Lewis, M.J., Montgomery, E., Ferrè, S., … Letovsky, S. (2021). Chronic kidney disease testing among at-risk adults in the U.S. remains low: Real-world evidence from a National Laboratory database. Diabetes Care, 44(9), 2025-2032.https://doi.org/10.2337/dc21-0723

 

American Diabetes Association Professional Practice Committee. (2023). Chronic kidney disease and risk management: Standards of medical care in diabetes—2023.Diabetes Care, 46(Supplement_1), S191-S202. https://doi.org/10.2337/dc23-S011

 

Bowe, B., Xie, Y., Li, T., Mokdad, A. H., Xian, H., Yan, Y.,... Al-Aly, Z. (2018). Changes in the US burden of chronic kidney disease from 2002 to 2016. JAMA Network Open, 1(7).

 

Centers for Disease Control and Prevention. Chronic Kidney Disease in the United States. (2023). Retrieved from: https://www.cdc.gov/kidneydisease/publications-resources/ckd-national-facts.html

 

de Boer, I.H., Khunti, K., Sadusky, T., Tuttle, K.R., Neumiller, J.J., Rhee, Bakris, G. (2022). Diabetes management in chronic kidney disease: a consensus report by the American Diabetes Association (ADA) and Kidney Disease: Improving Global Outcomes (KDIGO). Kidney International, 102(5):974-989. doi: 10.1016/j.kint.2022.08.012

 

Healthy People 2030. Retrieved from: https://health.gov/healthypeople/objectives-and-data/browse-objectives/chronic-kidney-disease

 

Hoerger, T. J., Simpson, S. A., Yarnoff, B. O., Pavkov, M. E., Burrows, N. R., Saydah, S. H., . . . Zhuo, X. (2015). The future burden of CKD in the United States: A simulation model for the CDC CKD Initiative. American Journal of Kidney Diseases, 65(3), 403-411. doi:10.1053/j.ajkd.2014.09.023 

 

National Kidney Foundation. (2007). KDOQI Clinical practice guidelines and clinical practice recommendations for diabetes and chronic kidney disease. Retrieved from: https://www.kidney.org/sites/default/files/docs/diabetes_ajkd_febsuppl_07.pdf

 

National Kidney Foundation. (2012). KDOQI Clinical practice guideline for diabetes and CKD: 2012 Update. Retrieved from: http://www.kidney.org/sites/default/files/docs/diabetes-ckd-update-2012.pdf

 

National Kidney Foundation. (2022). About chronic kidney disease. Retrieved from: https://www.kidney.org/atoz/content/about-chronic-kidney-disease

 

Nichols, G.A., Ustyugova, A., Déruaz-Luyet, A., O’Keeffe-Rosetti, M., & Brodovicz, K.G. (2020). Health care costs by type of expenditure across eGFR stages among patients with and without diabetes, cardiovascular disease, and heart failure. Journal of the American Society of Nephrology, 31(7), 1594-1601. DOI: https://doi.org/10.1681/asn.2019121308

 

Saran R. B., Abbott K. C., Agodoa, L.Y.C., Bragg-Gresham, J., Balkrishnan, R., Shahinian, V. (2019). US renal data system 2018 annual data report: Epidemiology of kidney disease in the United States. American Journal of Kidney Diseases, 73(3). DOI: https://doi.org/10.1053/j.ajkd.2019.01.001

 

Stempneiwicz, N., Vassalotti, J.A., Cuddeback, J.K., Ciemins, E., Storfer-Isser, A., Sang, Y., … Coresh, J. (2021). Chronic kidney disease testing among primary care patients with type 2 diabetes across 24 U.S. health care organizations. Diabetes Care, 44(9), 2000-2009. DOI: https://doi.org/10.2337/dc20-2715

 

Szczech, L. A., Stewart, R. C., Su, H., Deloskey, R. J., Astor, B. C., Fox, C. H., . . . Vassalotti, J. A. (2014). Primary care detection of chronic kidney disease in adults with type-2 diabetes: The ADD-CKD study (Awareness, detection and drug therapy in type 2 diabetes and chronic kidney disease). PLoS ONE, 9(11). DOI: https://doi.org/10.1371/journal.pone.0110535 

1.20 Types of Data Sources
1.25 Data Source Details

Practices collect EHR data using certified electronic health record technology (CEHRT). The MAT output, which includes the human readable and XML artifacts of the clinical quality language (CQL) for the measure are contained in the eCQM specifications attached. No additional tools are used for data collection for eCQMs.