Feature Fridays: Turning Condition Chaos into Clinical Clarity for Improved Care

Population health analytics shouldn’t feel like detective work.

But when your data lives in dozens of sources, formats, and coding systems, it does. That’s why so many organizations settle for claims-only analytics and fly blind on what’s really happening now.

This week’s Feature Friday: Zus Data Marts.

No detective work. No pipelines. Just clean, always-fresh clinical data—ready for action in your favorite tools.

What this feature does:

Zus Data Marts take the complexity out of clinical data and make it analytics-ready from day one.

Evergreen Nephrology saw the impact right away:

“Historical A1C results are crucial to our patient care and business model. Zus has already identified 2–3x more A1C results compared to our previous platform.” — Director of Advanced Analytics

Here’s what it looks like in action:

✅ Aggregates all data into one place: EHR data from dozens of sources, plus pharmacy fills, lab results, and ADT events—all unified so you’re not logging into multiple portals or chasing down records.

✅ Always up to date, automatically: The data refreshes every 24 hours. Automatically. No requests, no manual triggers. When a patient gets a new diagnosis, refill, or lab result, your population view updates without anyone lifting a finger.

✅ Transforms messy FHIR into SQL-friendly tables: FHIR is great for interoperability—but painful for analytics. We flatten nested resources into a clean schema so your team can query with standard SQL, not decipher API payloads.

✅ Works where you work: Use Zus Data Marts directly in Snowflake, Databricks, and (soon) BigQuery. Or pipe the data into your own warehouse or analytics model (think Tuva).

Imagine you’re managing a population of 50,000 patients in value-based contracts. You need to identify which patients have diabetes, are overdue for an A1C test, and recently had an ER visit.

Without Zus Data Marts:

You wait weeks for claims data to confirm an ER visit.
You manually query multiple EHR extracts to find the latest A1C values.
Your analysts spend hours untangling ICD-10 and SNOMED codes.

With Zus Data Marts:

All that data—EHR + pharmacy + lab + ADT—is aggregated in one place, normalized, and analytics-ready.
You run a single query in Snowflake: find diabetic patients, last A1C date > 6 months, recent ADT alert = yes.
You have a targeted outreach list in minutes, not weeks.

That’s the difference between reactive care and proactive care.

Why you should care:

Because timing and accuracy drive outcomes and revenue. Relying on claims alone keeps you stuck in the past. By the time a claim tells you a patient went to the ER, your window to intervene is long gone. Zus changes that with near real-time clinical data, giving you next-day visibility into what’s happening now, not weeks later.

And because Data Marts are built on top of the Zus Common Patient Record, you’re analyzing the richest, most comprehensive dataset available—not a patchwork of claims and stale extracts.

But solving this challenge isn’t just about access to more timely data. It’s about making the process manageable. Building and maintaining pipelines to make clinical data usable isn’t just a technical headache. It’s expensive and time consuming. Many healthcare organizations spend months and hundreds of thousands of dollars on custom ETL, only to end up with a process that constantly needs fixing. With Zus Data Marts, that complexity disappears. It’s fully managed, always up to date, and ready for analysis out of the box.

And when you’re operating in value-based care, timely, accurate, comprehensive patient data is the foundation for success. Risk stratification, quality measure reporting, spotting utilization trends early… these all depend on a complete, current view of your population. Zus makes this possible, without adding headcount, infrastructure, or delays.