Short snapper – closing cardiomatabolic care gaps with AI and team-based care

Many patients with chronic cardiometabolic conditions remain below recommended treatment targets despite established clinical guidelines. This session presents a practical care model that combines AI-supported patient identification, automated intake, ambient documentation and team-based care to help primary care practices proactively identify and manage care gaps. Through real-world implementation examples, attendees will learn how digital tools, physician extenders and coordinated referral pathways can support more consistent guideline-based care, improve practice efficiency and expand access for patients with chronic disease. 

Learning Objectives

By the end of this session, participants will be able to:

• Describe how AI-driven EMR screening tools can identify patients with unmet cardiometabolic care gaps without requiring full EMR interoperability and prioritize them for outreach and intervention.
• Explain how a structured four-step physician extender model, supported by LLM-based guideline recommendations and ambient AI documentation, increases physician capacity while maintaining care quality and closing chronic disease care gaps.
• Identify practical strategies for integrating eConsult and specialist referral pathways into a primary care chronic disease workflow to support coordinated, guideline-directed therapy for complex patients.

Speaker:

• Janish Raja, MD, Vice President Operations, Inflective AI

Presenter Bios:

Janish Raja

Janish Raja is Vice President of Operations at Inflective AI, where he leads the implementation of programs that use digital tools and team-based care to address gaps in chronic disease management. Drawing on his medical education and frontline experience in healthcare operations, he brings a clinically informed perspective to improving access to care and translating clinical priorities into practical workflows. His current work includes developing and advancing Inflective’s care-gap closure programs in Ontario, with an initial focus on dyslipidemia clinics. This approach connects proactive patient identification, coordinated assessment and follow-up to support guideline-based care.

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