Rethinking ROI in healthcare navigation: How AI Is making the invisible visible

By Shannon Skaggs, Chief AI Officer, Quantum Health

For years, self-insured employers have relied on traditional ROI metrics to evaluate the success of their benefits programs. But as costs continue to rise and scrutiny intensifies, that’s no longer enough. Employers and their consultants are asking a more complex question: What specific actions are driving value -- and how do we prove it?

At Quantum Health, we’ve been navigating this challenge head-on by transforming how we connect our engagements with members and providers to measurable outcomes.

How AI in healthcare navigation turns action into impact

We’ve always had methodologies to estimate savings and trend improvements but those alone couldn't always satisfy curiosity from employers. They wanted proof, down to the member level, of what we were doing, when we were doing it, and what impact it had.

That led us to develop a new approach, powered by AI and our 26 years of member journeys, interactions and data. More than just uncovering past value events, our dynamic AI engine continuously optimizes member and provider journeys in real time to deliver better clinical, financial and experiential outcomes. One that doesn’t just summarize interactions or offer insights but one that can act: surfacing, validating, and quantifying moments of value within the member journey.

This use of AI takes purposeful action toward a defined goal. For us, that goal is better outcomes: identifying when our team made a meaningful difference in a member’s care journey and quantifying that difference in clinical, financial and experiential terms.

Secure and ethical AI in healthcare: A human-first model

Unlike open AI models, our system is built as a closed-loop platform. It operates within a secure, HIPAA-compliant environment and uses tightly controlled inputs, reducing the risk of data breaches or AI “hallucinations.” All models are continually monitored and refined by a cross-functional team, including clinicians, actuaries, and care leaders, to ensure ethical use and real-world accuracy.

And while we’re using AI to scale insights and augment decision-making, it’s never a replacement for people. Our model is human-first by design, enhancing the work of our care coordinators and giving them sharper tools to guide members through complex healthcare decisions.

Making value tangible

Take, for example, a member who visited her OB-GYN for a routine exam. What should have been a preventive visit became more complicated when she was diagnosed with fibroids, requiring further testing and ultimately surgery. Her journey included misprocessed claims, network navigation and provider selection.

At each stage, our care team stepped in, finding high-value providers, resolving billing issues, and guiding benefit usage. Our platform captured and evaluated each interaction, assigning dollar values to the member and employer savings. In one instance alone, redirecting her MRI from a hospital to a freestanding imaging center saved the member $300 and the employer $150.

This is just one of thousands of examples of how we've intervened in a member’s journey.

Importantly, these moments of value have been triggered by our Warriors and supported by our technology for years—this AI-driven capability is simply a new way to package and share those proven interventions with clients, consultants, and to empower our teams with real-time feedback for continuous improvement. By aggregating these individual moments, we’re able to show not just that we delivered savings, but how we did it. And by mining more than 26 years of de-identified interaction transcripts and provider interactions, our model can now surface and quantify these events in near real time, turning one-off anecdotes into a pattern of measurable value.

The framework

To bring clarity to this data-rich environment, we’ve categorized our actions into four main categories:

1. Navigation and steerage: Guiding members to the right level of care, in-network providers or centers of excellence.
2. Solutioning: Helping members overcome barriers like transportation, billing confusion or care access.
3. Care coordination and clinical support: Ensuring members receive appropriate follow-up care and support.
4. Decision support: Influencing critical decisions early in a member’s journey to avoid unnecessary cost or complexity.

These aren’t abstract concepts. They’re traceable, documentable, and thanks to AI processing, now quantifiable.

We still stand behind our third-party validated actuarial study, which provides a top-down view of the financial impact our navigation model delivers across our entire book of business. What’s new is this AI-powered capability that takes a bottom-up approach — not only tracing where value was created, but actively steering interventions and recommending optimal next steps to improve outcomes across clinical, financial, and experiential dimensions. It traces value at the member level, showing exactly where and how individual interactions make a difference. Together, these two perspectives offer a more complete and credible ROI story, one that combines broad financial validation with real, day-to-day impact.

As we continue to refine this model with human oversight and client feedback, the impact becomes clearer: smarter insights, faster iterations, and greater visibility. It’s not just about proving ROI. It’s about redefining it.