A primary-care tool for chronic kidney disease
Investigators have developed and validated an electronic health record–integrated clinical decision-support tool intended to help primary-care professionals identify and manage chronic kidney disease, or CKD. Called Treat CKD, the system brings together diagnosis, risk classification and treatment-oriented recommendations at the point of care.
The research was presented at ASN Kidney Week 2026. The work describes a tool designed for routine primary-care use, where clinicians may be managing many conditions at once and where a structured view of kidney and cardiovascular risk could help determine what follow-up is appropriate.
Rather than relying on a separate calculation process for each part of the assessment, Treat CKD draws on data already held in electronic health records. It is designed to identify CKD, classify risk, calculate kidney-failure risk, estimate cardiovascular risk and provide recommendations connected to those results.
Several risk frameworks in one workflow
The tool uses Kidney Disease: Improving Global Outcomes, or KDIGO, criteria to classify CKD risk. It also calculates kidney-failure risk using the Kidney Failure Risk Equation and estimates cardiovascular risk with the American Heart Association PREVENT equations.
Those calculations are paired with recommendations covering albuminuria testing, blood-pressure management, cholesterol-lowering therapy, cardio-kidney therapies and nephrology referral. The aim is not merely to flag a possible kidney condition, but to organize clinically relevant information and next-step guidance in one primary-care workflow.
Albuminuria testing is included because it is one of the areas the tool can recommend as part of kidney-risk assessment. The tool’s scope also extends beyond the risk of kidney failure by incorporating cardiovascular risk estimation, reflecting the range of issues clinicians may need to consider for patients with CKD.
Testing at the University of California, San Francisco
When Treat CKD was incorporated into the University of California, San Francisco system, participating primary-care health professionals characterized it as easy to use, clinically relevant and well integrated into existing workflows. According to the report, they did not describe the tool as adding a substantial workflow burden.
The investigators also reported that the tool accurately confirmed KDIGO-based CKD risk classification. Its calculated Kidney Failure Risk Equation and PREVENT scores were fully concordant with manually calculated scores in the validation described in the presentation.
That reported agreement is important for a decision-support product. A tool that automates risk assessment must preserve the underlying clinical logic of the established methods it applies. In this case, the investigators said the automated results matched the manual calculations for the kidney-failure and cardiovascular-risk measures they evaluated.
Decision support, not a replacement for clinical judgment
Treat CKD is designed to support clinicians at the point of care, not to replace professional judgment. Its recommendations are described as guideline-concordant and are intended to help primary-care teams recognize CKD, stratify risk and consider follow-up steps.
The reported evaluation focused on validation and user feedback within the UCSF setting. It does not establish that the tool will automatically produce the same experience or results in every health system. Electronic health record systems, clinical workflows and implementation practices can differ substantially between organizations.
The research also does not claim that the tool by itself improves patient outcomes. Its stated role is to automate identification and risk classification, produce kidney and cardiovascular risk estimates, and provide recommendations that can support care decisions. Further evaluation would be needed to assess broader deployment as well as effects on detection, treatment and outcomes.
Why integration matters
Clinical decision support is most useful when it fits into the work clinicians are already doing. The developers’ report that primary-care professionals found Treat CKD relevant, usable and well integrated is therefore a central part of the early evaluation.
The system combines several tasks that otherwise may require separate review: determining whether CKD is present, applying KDIGO risk categories, estimating risk of progression to kidney failure, estimating cardiovascular risk and reviewing possible care actions. Bringing those tasks together could make it easier to surface a structured kidney-risk assessment during a routine visit.
For now, Treat CKD represents an early, health-system-integrated approach rather than a broadly established standard of care. The study’s key finding is that the tool was able to automate the specific risk assessments tested while matching manual calculations for the reported equations and gaining favorable feedback from primary-care users. The next question is whether further evaluation will support its use as a scalable strategy for CKD detection and treatment in primary care.
This article is based on reporting by Medical Xpress. Read the original article.
Originally published on medicalxpress.com
