AI Native HIEs: Preparing for the Coming Wave of Predictive Care

By Leo Pak, CEO – Interstella

Artificial intelligence is no longer on the horizon. It is here, reshaping every corner of healthcare. The question is no longer if AI will influence care, but how infrastructure must evolve to support it.

For Health Information Exchanges, the implications are profound. The HIEs that will survive the coming wave will not be those that tack AI on as an afterthought. They will be those built as AI-native infrastructures from the ground up.

For two decades, HIEs were judged by the pipes they built and the data they moved. Connectivity was the milestone. But connectivity without intelligence is already obsolete. The future belongs to those who cannot only route data but refine it into fuel for AI-driven prediction, insight, and intervention.

From Pipelines to Refineries

The old model of interoperability was about transactions. A lab result moved from Hospital A to Clinic B. Mission accomplished.

But predictive care requires something far more sophisticated. It demands that the lab result, the prescription, the mental health screening, the housing instability note, and the genomic marker all be reconciled, standardized, and contextualized instantly.

That is the difference between a pipeline and a refinery. Pipelines move raw material. Refineries transform it into usable fuel.

An AI-native HIE does not simply transmit HL7 or CCD messages. It produces Intelligent Assets — data that is self-updating, context-rich, and immediately ready to drive predictive models, AI copilots, and real-time decision support.

Without this shift, the promise of AI collapses. Dirty, inconsistent, or lagging data poisons algorithms, undermines trust, and creates more risk than value. Dirty data is the real threat to AI. Refinement is the antidote.

The Power of Prediction

The coming wave of predictive care will depend on this foundation. Imagine:

• A patient flagged in real time as at risk for heart failure, not after an ER admission, but weeks before, based on subtle patterns across medications, vital signs, housing instability, and behavioral health cues.
  

• A school nurse alerted to rising asthma risk because environmental data and inhaler refills spike simultaneously.
  

• A community navigator notified before eviction triggers a behavioral health crisis.

This is predictive care in action. And it is only possible when HIE infrastructure stops thinking in transactions and starts thinking in intelligence.

Principles of an AI-Native HIE

The distinction is not just technical. It is philosophical. An AI-native HIE is built on three principles:

1. Real-time: Batch pipelines are relics. Predictive models cannot wait hours or days.
   

2. Refined: Quarantine, normalization, enrichment, and governance are not extras. They are prerequisites.
   

3. Whole-person: Clinical data alone is not enough. Behavioral health, social determinants, genomic signals, and environmental factors must all be integrated.
   

Together, these principles create the conditions for predictive care. Without them, AI is theater. With them, AI becomes a trusted partner in care delivery.

The Lynqsys Foundation

At Interstella, this is not theory. Our Lynqsys platform is purpose-built to transform messy, multi-source data into Intelligent Assets.

• Data Refinery as a Service (DRAAS): Lynqsys does not just move data. It refines it in real time, turning raw streams into AI-ready assets.
  

• Cloud-Native and AI-Native: Unlike legacy platforms migrated to the cloud, Lynqsys was born there. Its microservices architecture scales elastically and integrates seamlessly into AI pipelines.
  

• FHIR-First and TEFCA-Ready: Every record is normalized into modern standards while preserving compatibility with legacy HL7 and CCD data.
  

• Dynamic Intelligence: Intelligent ingest engines, anomaly detection, and auto-generated data quality scorecards ensure trust in every byte.
  

Lynqsys is not just a tool. It is an intelligent operating system for healthcare, designed by HIE veterans for HIE professionals.

Whole Person Intelligence in Action

Through our partnership with NinePatch, we have shown how Lynqsys extends beyond the clinical chart into behavioral, social, and genomic domains. Together, we deliver Whole Person Intelligence — the synthesis of physical, mental, environmental, and social data into actionable insights.

This is how AI-native infrastructure makes a difference on the ground: real-time alerts for housing instability, predictive flags for behavioral health crises, adaptive interventions for neurodivergent care. It is not abstract. It is lived context, activated.

From Compliance to Leadership

The AI-native HIE is not a distant vision. It is already being built. Interstella’s work with clients like SCHIO demonstrates how state and regional HIEs can leapfrog from compliance-driven utilities to predictive care leaders.

A decade ago, the milestone was connection. Today, it is prediction. The next wave of healthcare will be defined not by whether data moves, but by whether data anticipates.

Those who embrace this paradigm will not just weather the coming wave. They will lead it.

Learn more about how Interstella and our Lynqsys platform are building the AI-native HIE. Visit us at www.interstella.us or connect with us at Civitas 2025.