Spotlight: Chase Fagen @ Acuity Health
A spotlight is a short-form interview with a leader in health tech. In this spotlight, you'll hear from Chase Fagen, co-founder and Head of AI Engineering at Acuity Health.
What does Acuity Health do?
Acuity Health helps healthcare enterprises build, deploy, continuously improve, and manage AI voice agents. We take a bespoke, forward-deployed approach, working closely with each organization to tailor AI agents to its workflows, culture, and policies.
Our platform brings telephony, call routing, and agent management together. Agents can transfer calls to the right staff member with context and create tasks and notes for follow-up, giving teams continuity across AI and human interactions. The Acuity Platform enables medical enterprises to continuously iterate on their agents, updating instructions, refining workflows, and using performance insights to guide improvements as their needs evolve.
We also help organizations prepare their teams for deployment through change management playbooks that define responsibilities, establish handoff procedures, and guide AI adoption.
How did you end up working in health tech?
My co-founder and I started as AI consultants for small businesses. We both have parents who are physicians, so our immediate network naturally connected us with people in healthcare.
The turning point came when a large ophthalmology practice approached us because it was dropping around 200 calls a day. We suggested building an AI voice agent to help handle that volume. Working on a concrete problem for that practice became our entry point into health tech and the starting point for Acuity Health.
How does your role intersect with revenue cycle management (RCM)?
Our agents often serve as a patient’s first point of contact with a practice, so our work intersects with RCM before the patient even arrives. Alongside helping patients get scheduled, agents can verify insurance through Stedi and explain available copay and benefit information. Patients want to understand what their care may cost, and those early conversations help set expectations.
I think about our role as helping practices get the beginning of the revenue cycle right: capturing accurate information, helping patients understand their coverage, and passing the right context to staff when questions need further attention.
What do you think RCM will look like two years from now?
I think RCM will become much more proactive and personalized over the next two years. When staff and resources are stretched thin, practices often have to react to problems as they arise and follow the same workflow for everyone. There’s limited capacity to adapt the process to each patient’s circumstances.
The promise of AI is giving practices that capacity. If a patient’s coverage changes, information is missing, or they have concerns about cost, AI agents can help identify what’s needed and coordinate the appropriate verification, outreach, or staff follow-up.
What excites me is the ability to dynamically tailor that process to each patient: their coverage, their questions, and where they are in their care journey. Every interaction can inform the next action, helping practices resolve issues earlier and give patients clearer expectations before they arrive.