Working Upstream in Healthcare: Turning Medication Intelligence into Preventive Action

For more than a decade, healthcare has focused on improving interoperability and health intelligence sharing. And there’s been real progress. Today, information moves across systems faster and at greater scale than ever before.

But access alone doesn’t necessarily translate to impact.

When data shows up too late, in the wrong place or without a clear next step, it doesn’t change outcomes—it just helps explain what happened. Too much of our system is still built to react, not prevent.

I like to think about this using a simple concept from the book Upstream. We’ve become very good at pulling people out of the proverbial river—with clinicians, pharmacists, care coordinators and health plans doing important work every day.

But we’re far less effective at walking upstream to understand why people are falling into the river in the first place.

What a Downstream System Looks Like 

To illustrate this point, let’s look at the story of Maria, a fictional (but all too real) patient.

Maria has diabetes with complications, hypertension and hyperlipidemia. She’s enrolled in a Medicare Advantage plan, which means her chronic care management is closely measured—and costs matter. In a typical outpatient year, Maria touches five quality measures. Then she’s hospitalized, and suddenly that single event triggers four more.

That’s one patient and nine quality measures. This is what a downstream system looks like in practice.

While Maria’s data exists across the healthcare ecosystem, it’s fragmented and scattered. Her care team, pharmacist and health plan are all doing the best they can with what’s in front of them, but the important signals and insights are lagging.

Everyone is acting rationally inside a system that’s designed to react, not prevent.

The result?

Maria misses a medication refill, her blood glucose becomes unstable and symptoms show up. Eventually, she lands in the emergency room. And it’s only after her hospitalization that the signals finally line up, and the picture of what went wrong becomes clear. But it’s too late to intervene.

Maria’s health event didn’t result from a lack of data. It happened because the information and insights that mattered showed up too late and in the wrong place.

Why Interoperability in Healthcare Needs a Reset

Interoperability 2.0 isn’t about moving more data. It’s about ensuring intelligence arrives when and where it can be acted upon and drive meaningful impact.

Effective interoperability hinges on three essentials:

• Timing: Insights arrive early enough to influence action
• Workflow: Information surfaces directly within the moments and systems where decisions are made
• Insight: Intelligence is delivered with clarity, and there’s a clear and meaningful next step

Without the right timing, workflow integration and clarity, data doesn’t help drive decisions—it sits there, creating care gaps.

Going Upstream Takes Us From Reactive to Preventive

Clinicians and care teams aren’t asking for more data. They’re asking for less friction, more clarity and insights they can trust and act on. And when medication insights are embedded directly into existing workflows, decisions happen faster, care stays on track and patients are less likely to fall through the cracks.

Interoperability 2.0 is the shift from documenting what happened to changing what happens next.

For health plans, this isn’t theoretical. It’s a practical way to improve outcomes, quality performance and experiences that make a real and measurable impact.

“Medication intelligence is one of the few signals that tells us what actually happened—not just what was intended.”