New CKD Tool Could Simplify Risk Assessment in Primary Care

An electronic health record (EHR)-integrated clinical decision support tool demonstrated 100% concordance with manually calculated chronic kidney disease (CKD) risk classifications, kidney failure risk estimates, and cardiovascular risk scores in a validation study presented at the American Society of Nephrology (ASN) Kidney Week 2026 Annual Meeting in Denver, Colorado.¹

The tool, called Treat CKD, was developed by researchers at the University of California, San Francisco (UCSF), to automate CKD identification, risk stratification, and guideline-based treatment recommendations at the point of care. In addition to demonstrating accuracy across 60 patient records, the tool received favorable feedback from 11 primary care clinicians, who described it as clinically relevant, easy to use, and well integrated into existing workflows.¹

The findings, presented October 22 during a session on cardiovascular-kidney-metabolic (CKM) health, suggest that EHR-based decision support may help address gaps in CKD recognition and management in primary care, although further research is needed to determine whether the tool improves clinical outcomes.¹

"Treat CKD accurately automates CKD identification and risk classification, estimates risk of cardiovascular events and progression to kidney failure, and provides guideline-concordant treatment recommendations for primary care, while being perceived by clinicians as easy to use, acceptable, and clinically appropriate for routine use in primary care, supporting its further evaluation as a scalable CKD detection and treatment strategy," corresponding author Ivan Villasenor, an MD candidate at UCSF School of Medicine, said in an ASN press release.²

How Does Treat CKD Support Clinical Decision-Making?

Treat CKD was developed to address underdiagnosis and undertreatment of CKD in primary care by consolidating risk assessments and treatment recommendations within the Epic EHR system.

Using existing patient data, the tool automatically identifies CKD and assigns risk classifications based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. It also incorporates 2 established risk prediction models: the Kidney Failure Risk Equation (KFRE), which estimates the likelihood of progression to kidney failure, and the American Heart Association's Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations, which estimate cardiovascular risk.¹

Based on these assessments, Treat CKD generates recommendations across several aspects of CKD care, including:

• Albuminuria testing: Recommendations to support CKD risk assessment and classification.
• Blood pressure management: Guideline-based treatment recommendations.
• Cholesterol-lowering therapy: Recommendations addressing cardiovascular risk.
• Cardio-kidney therapies: Treatment recommendations aligned with applicable clinical guidelines.
• Nephrology referral: Guidance to help identify patients who may require specialist evaluation.

By integrating these functions into a single clinical support tool, investigators aimed to reduce the need for primary care clinicians to independently calculate risk scores, review multiple guidelines, and determine appropriate management strategies during routine patient encounters.¹

Validation Shows Complete Concordance With Manual Assessments

To evaluate accuracy, investigators manually reviewed 60 patient records and compared Treat CKD's automated results with independently calculated risk assessments.

The tool demonstrated full concordance with manual KDIGO CKD risk classification, KFRE kidney failure estimates, and PREVENT cardiovascular risk estimates across the reviewed records.¹

Investigators also conducted key informant interviews with 11 primary care clinicians to assess usability, clinical relevance, and integration into routine workflows.

Clinicians described the tool as easy to navigate and valuable for consolidating CKD staging, kidney failure risk, cardiovascular risk, and treatment recommendations into a single interface. They also reported that Treat CKD reduced cognitive burden without adding substantial workflow demands.¹

However, participants identified opportunities for improvement, including greater flexibility in blood pressure targets and expanding the tool's functionality to patients with moderate-risk CKD.

Implications for Primary Care

The findings highlight the potential role of EHR-integrated decision support in addressing the complexity of CKD management, particularly as primary care clinicians increasingly manage overlapping kidney, cardiovascular, and metabolic risks.

Treat CKD's incorporation of KDIGO risk categories, KFRE estimates, and PREVENT equations could help clinicians evaluate kidney disease progression and cardiovascular risk within the same encounter, while providing recommendations for treatment and specialty referral.

Importantly, the study evaluated the tool's technical accuracy and clinician experience rather than its impact on CKD detection rates, prescribing practices, referral patterns, or patient outcomes. The investigators did not report whether implementation increased albuminuria testing, improved uptake of guideline-directed therapies, or reduced progression to kidney failure.

The findings are also limited by the relatively small validation sample of 60 patients and usability interviews involving 11 primary care clinicians within a single health system.

Nevertheless, investigators concluded that the tool's accuracy, usability, and integration into routine primary care workflows support further evaluation of Treat CKD as a potentially scalable approach to improving CKD recognition and risk-based treatment.¹

References

1. Villasenor I, Okpara K, Shirali S, et al. Treat CKD: An electronic health record (EHR)-integrated clinical decision support tool for risk-based CKD care in primary care. Abstract TH-OR044. Presented at: ASN Kidney Week 2026; October 22, 2026; Denver, CO.

2. American Society of Nephrology. Clinical support tool helps primary care health professionals detect and treat chronic kidney disease. News release. October 22, 2026. Accessed October 27, 2026. https://www.eurekalert.org/news-releases/1148353