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Published on: April 12, 2021
Development of a Primary Care Cardio-Kidney Risk Navigator for Clinical Decision Support
Tyler J Gluckman1, Kade Birkeland2, Ankeet Bhatt3
1Center for Cardiovascular Analytics, Research, and Data Science (CARDS), Providence Heart Institute, Providence Health System, Portland, OR 97225, USA.
Insights
A new algorithm integrates chronic kidney disease (CKD) screening into cardiovascular disease (CVD) risk management. This practical tool aids primary care in earlier identification and prevention for at-risk patients.
Area of Science:
- Nephrology
- Cardiology
- Primary Care Medicine
Background:
- Chronic kidney disease (CKD) and cardiovascular disease (CVD) share a significant, interconnected health burden, with each condition exacerbating the other.
- Despite available diagnostic tools and risk assessment methods, CKD screening is inconsistent, and kidney health is under-integrated into CVD risk stratification.
- Barriers at systemic, clinical, and patient levels hinder the adoption of guideline-recommended CKD screening.
Purpose of the Study:
- To develop a consensus-based, practical algorithm for integrating CKD screening into cardiovascular disease (CVD) risk management.
- To address inconsistencies in CKD screening and improve the integration of kidney measures into CVD risk assessment.
Main Methods:
- A structured Delphi process involving a multidisciplinary expert panel was employed to develop an evidence-informed screening algorithm.
- Iterative surveys, landscape assessments, and roundtable discussions were used to identify screening components, refine the algorithm, and assess clinical workflow feasibility.
- Consensus on the algorithm's structure, content, and applicability was achieved through structured group discussions and survey-based validation.
Main Results:
- The expert panel identified optimal triggers for CKD screening and key gaps in current clinical practices.
- The developed algorithm offers a streamlined, implementation-focused approach for consistent and earlier identification of patients at risk for CKD and CVD.
- Consensus was reached on the algorithm's structure, content, and its applicability across various clinical settings.
Conclusions:
- The Primary Care Cardio-Kidney Risk Navigator algorithm provides a practical framework for integrating CKD screening into CVD risk management within primary care.
- This tool operationalizes existing guidelines into a unified, workflow-oriented approach to support consistent implementation and earlier patient identification.
- The algorithm facilitates timely referral and prevention strategies for at-risk populations and is adaptable for EHR integration or use as a standalone decision support tool.
Abstract:
Background/Objectives: Chronic kidney disease (CKD) and cardiovascular disease (CVD) confer a substantial, interrelated health burden. CKD markedly increases cardiovascular risk and premature mortality, while CVD accelerates kidney disease progression. Despite the availability of simple diagnostic tests and validated CVD risk tools, CKD screening remains inconsistent, kidney measures are under-integrated into CVD risk stratification, and guideline-recommended screening is variably adopted due to system-, clinician-, and patient-level barriers. This initiative aimed to develop a consensus-based, practical algorithm to integrate CKD screening into CVD risk management. Methods: A structured Delphi process was used to develop an evidence-informed, consensus-based screening algorithm. In Phase 1, a multidisciplinary expert panel completed iterative surveys to identify and prioritize key screening components and achieve preliminary consensus. Participants received a landscape assessment summarizing current practices, evidence, and implementation gaps. A roundtable discussion reviewed clinical guidelines, published evidence, and survey findings, informing the development of an initial algorithm draft. In Phase 2, a follow-up roundtable refined the algorithm, assessed feasibility within real-world clinical workflows, and confirmed consensus on priority elements. Agreement was finalized through structured group discussion and survey-based validation. Results: Panel discussions identified optimal CKD screening triggers, key gaps in current practice, and opportunities to promote earlier identification of at-risk patients. Refinement during the second roundtable resulted in consensus on algorithm structure, content, and applicability across settings. The final algorithm reflects a streamlined, implementation-focused approach to support consistent and earlier identification of at-risk patients. Conclusions: The algorithm, labeled the Primary Care Cardio-Kidney Risk Navigator, provides a practical, flexible framework that integrates and operationalizes existing guideline recommendations into a unified, workflow-oriented approach for primary care that supports consistent real-world implementation. It supports earlier identification, referral, and prevention strategies for at-risk populations and can be implemented within electronic health records or as a standalone clinical decision support tool.
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