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.

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