The Standard

Summary

HL7 International embraces artificial intelligence as a powerful enabling technology for health data interoperability. Rather than restricting AI use of our standards, we are actively engineering our processes and content to be AI-ready. We believe that AI systems capable of understanding FHIR® and other HL7 standards ultimately serve our mission to improve health and well-being through better data exchange.

Our Perspective: Open Standards = Open Possibilities

HL7 International's mission is to create and promote the adoption of innovative interoperability standards that improve health and well-being while fostering a diverse and inclusive global community. We pursue this so that people everywhere can live in optimal health. Because open standards enable new digital freedoms, we want our standards to be as widely used and as deeply understood as possible. By humans and machines alike. Standards demonstrate the network effect — they become more valuable the more widely they are adopted.

Some standards development organizations (SDOs) restrict or prohibit the use of their intellectual property in AI training and inference. HL7 International takes a different approach. We view AI systems as legitimate and valuable consumers of our standards — partners in the global project of interoperability rather than threats to our business model.

Our licensing choices reflect this view. HL7 publishes our FHIR platform standard and related specifications under the Creative Commons Zero (CC0) public domain dedication, the most permissive licensing approach available. CC0 reflects a deliberate strategic commitment: by removing all licensing barriers, we maximize adoption potential and minimize friction for all implementers, including AI developers and the AI systems they build.

FHIR in the Wild: Standards-Aware AI Systems

HL7's flagship FHIR standard is unique not only as a modern API standard for healthcare, with innovations in open standards development, but also in its structure and publication format. FHIR reflects a fundamentally developer-native approach, setting it apart from most other health IT standards. Rather than static, paywalled PDFs, FHIR is published as a fully navigable website where every resource, data type, and operation has its own structured page — paired with computable, machine-readable definitions in JSON and XML that allow tools to programmatically interrogate the standard itself. Further, the platform specification and derivative implementation guides, along with their computable parts, are distributed as versioned NPM packages via a public registry, enabling reproducible builds and automated dependency resolution familiar to any software developer.

Additionally, we have embraced the expectation of co-developing and testing an open-source (typically licensed under Apache 2.0) reference implementation software alongside the standard. This ensures that the published standard is actually implementable, and gives implementers working software to learn from, test their code against, or even incorporate into their products.

Because FHIR is freely available, extensively documented online, and has corresponding open source reference software code bases on public platforms like Github, FHIR is already embedded in the training corpora of the world's leading large language models. Developers today can ask an AI assistant to generate a FHIR patient resource, write a FHIR search query, or explain the semantics of a SMART on FHIR authorization flow — and receive accurate, useful answers. This is a natural consequence of our open-first standards strategy at work.

In short, we see the standard not as a document to be read, but as an open platform to be built upon.

Today we honor the life and legacy of Clement J. McDonald, MD, who passed away on May 21, 2026.

Known worldwide as the one and only "Clem", he was a luminary in the field of biomedical informatics. Clem was a titan, world renowned for his innovations in electronic medical records, clinical decision support, multi-institution health data exchange, and especially in the global standards that enable computers to share and understand health data.

As a co-founder and life-long member of HL7 International, Clem's vision for interoperability enabled by consensus standards is encoded in our DNA.

A Pioneering Career

Clem grew up on Chicago's West Side, graduated from Notre Dame in three years, and attended the University of Illinois College of Medicine. He completed his internal medicine residency at Cook County Hospital and the University of Wisconsin, after which he joined Indiana University and the Regenstrief Institute in 1972. There he built one of the world's first electronic medical record systems and published the first randomized controlled trials demonstrating that computerized clinical decision support could improve care.

He rose through the academic ranks at the Indiana University School of Medicine to become Distinguished Professor of Medicine and the Sam Regenstrief Professor of Medical Informatics, and served as Director of the Regenstrief Institute from 1990 to 2006. He also developed the Indiana Network for Patient Care, a groundbreaking statewide health information exchange. Throughout this time, he also practiced primary care internal medicine in a safety-net clinic for more than 25 years (that ran on the EMR he created).

In 2004, Clem joined the U.S. National Library of Medicine where he first served as Director of the Lister Hill National Center for Biomedical Communications and Scientific Director of its intramural research program, and later serving as Chief Health Data Standards Officer — a position he held until his passing.

Co-authored by Kevin Day, Consent Implementation Guide Co-Lead, FAST FHIR Accelerator

MEET MARIA

Maria is 62 and just home from the hospital after a procedure that requires careful follow-up. Her care team has discharged her with medications, recovery instructions, and a treatment plan her health plan put in place to manage cost. Her husband took time off work to help her recover at home—administering medications, watching for warning signs, coordinating with the visiting home health nurse, and calling the health plan when questions came up about coverage and the treatment plan.

There is one complication. Decades ago, before Maria met her husband, she received sensitive care she has chosen not to share with him; care that is in her medical record and always will be. So when the hospital asked Maria at discharge whether she wanted to grant her husband access to her clinical information, she faced a binary choice: all or nothing. There was no option to share the medications and care plan he needed while keeping the rest of her history private. The system doesn't support that nuance, so Maria selected nothing.

Her husband helps her recover with whatever Maria can tell him in the moment—what each pill is for, when the next appointment is, and what the home health nurse said. When he calls the health plan to ask why one therapy was authorized but another was not, he is told he is not on the consent and the conversation cannot continue. The clinical care suffers. So does the emotional care. Two weeks in, he is frustrated, and Maria is exhausted from carrying both her recovery and the running translation of her own chart.

Maria’s story is not unusual. Across the country, patients, providers, payers, and the family members who do the actual work of recovery face a quiet crisis hiding inside healthcare’s interoperability progress: the problem of consent.

The Hidden Roadblock: When Consent Doesn’t Scale

Healthcare interoperability has made remarkable strides. Data can now move faster, further, and more securely than ever before. Yet one foundational challenge continues to limit what that progress can achieve: how patient consent is captured, communicated, and enforced across organizations.

Today, consent is fragmented. A patient authorizes data sharing at one organization, but that authorization rarely travels with the data. In the context of data privacy and consent, a “policy” is the set of provisions that govern a specific grantor–grantee relationship—what may be disclosed, to whom, for what purpose, for how long, and under what conditions. Those provisions also drive enforcement decisions when consents conflict, such as when an additive permission from one source overlaps with a restriction from another. The operational burden of capturing them varies widely depending on the setting. In clinical environments, consent is typically tied to an encounter or event, such as a 30-minute office visit or a three-week inpatient stay, and expires when that event ends. Health plans, by contrast, capture consent that remains valid until a specified expiration date or until the patient revokes it. The result is a tangled consent relationship tree, where each branch—provider, payer, app, caregiver, personal representative—holds a different fragment of the patient’s intent, with different lifespans, scopes, and enforcement rules. Because no two systems interpret these provisions the same way, organizations fall back on manual review to reconcile conflicts, slowing workflows to a crawl at the exact moments when trust matters most. Compliance burden rises. Patients are left in the dark about how their information is used. And interoperability stalls precisely where it should accelerate.

This is the problem the HL7® FHIR® at Scale Taskforce (FAST) set out to solve.

May Community Roundtable on May 27 Offers More Insight into Proposed Rule and Payer Data Exchange

As the industry prepares for the next wave of healthcare interoperability, the HL7 Da Vinci Project is dedicated to providing the community with the insights and tools necessary for success. With newly proposed regulatory frameworks, the stakes for technical and operational alignment have never been higher. Join us for the May Community Roundtable on Wednesday, May 27, 2026, from 4 – 5:30 p.m. ET to prepare for what’s next.

What You’ll Learn

While our April session established the foundational context for the new federal rule (CMS-0062-P), the May session builds on the momentum by moving from initial impressions to active implementation strategies. We will provide a focused update of the community’s considerations regarding the 2026 Interoperability Standards and Prior Authorization for Drugs proposed rule, specifically focusing on the Payer Data Exchange (PDex), PDex Plan Net, and Member Attribution (ATR) List Implementation Guides (IGs) called out in the rule.

Real-World Perspectives & Demonstrations

Following the policy discussion, you will hear directly from implementers successfully deploying these standards in real-world payer environments:

• Onyx: Discover how their implementations focus on moving data out of silos into standardized formats, providing endpoints for payers to make data available via HL7 FHIR IGs.
• Availity: Watch a live demo of core PDex workflows, including member matching and data retrieval, and learn how a centralized network can reduce onboarding friction while preserving payer autonomy and PDex semantics.

Our presenters will share critical insights on scalability and how these implementations support broader policy goals around data access, care coordination, and patient empowerment.

Upcoming Da Vinci Community Roundtable on April 29 at 4:00 pm ET

The momentum for healthcare interoperability continues to accelerate. Following the CMS-0057-F final rule, the Centers for Medicare & Medicaid Services (CMS) and the Office of the National Coordinator for Health Information Technology (ONC) have introduced its next major regulatory step: the 2026 Interoperability Standards and Prior Authorization for Drugs Proposed Rule (CMS-0062-P).

Join the HL7 Da Vinci Project for the April Community Roundtable happening on Wednesday, April 29, 2026 at 4 p.m. ET as we break down this new proposal and discuss its implications for HL7 Fast Healthcare Interoperability Resources® (FHIR®) implementation and the industry at large. The new proposed rule relies heavily on the work of the HL7 Da Vinci Project community and could bring significant changes for industry, including adding Da Vinci implementation guides to Health Insurance Portability and Accountability Act of 1996 (HIPAA) requirements.

Featured Speakers

• Denise St. Clair: HL7 Da Vinci Project PMO; Vice President, Health Policy & Interoperability, Global Alliant, Inc.
• Alix Goss: Program Manager, HL7 Da Vinci Project; Senior Consultant, Point-of-Care Partners
• Moderator: Casey Thompson: HL7 Da Vinci Project Program Coordinator; Consultant, Point-of-Care Partners

If you’ve spent any time in healthcare over the past year, you’ve probably felt it: the energy, the urgency, the curiosity around AI. Everywhere you look, teams are experimenting with new models, exploring new use cases and imagining what care could look like if we finally had the right data in the right place at the right time.

But there’s also a shared realization emerging across the industry that AI can’t transform healthcare unless the data behind it is trustworthy, connected and interoperable.

That’s why HL7 International launched the 2026 HL7 AI Challenge, now officially open for submissions through June 30, 2026.

Why an HL7 AI Challenge?

Last year’s inaugural Challenge showed us something powerful: when innovators build on HL7 standards, they can move faster, scale more easily and create solutions that actually work in the messy, real‑world environments where healthcare happens.

Healthcare organizations around the world are experimenting with AI, but many face the same barriers: fragmented data, inconsistent formats, and limited ability to integrate AI outputs into clinical systems. HL7’s standards are designed to address these challenges, making them a natural foundation for safe and effective AI adoption.

The HL7 AI Challenge aims to:

• Encourage innovation grounded in open, widely adopted standards
• Demonstrate how structured, interoperable data improves AI performance
• Highlight real‑world solutions that can scale across organizations and borders

Healthcare interoperability has reached an inflection point.

In 2026, success is no longer defined by the presence of APIs but by the ability tooperate securely, consistently, and at scale across networks, organizations, and increasingly, across borders.

This shift reframes interoperability as something far more consequential:
a shared trust problem spanning cybersecurity, financial sustainability, and patient safety.

At the center of this transformation is FAST Security, emerging not simply as a technical specification, but as thefoundational trust layer for a global healthcare ecosystem.

Interoperability Is Now a Cybersecurity Surface

As healthcare exchange accelerates—payer-to-payer data sharing, automated prior authorization, and network-based access—organizations are no longer just exposing APIs.

They are expanding an identity and authorization attack surface.

Each new connection introduces:

• Additional credentials to manage
• Increasingly complex authorization logic
• More exceptions and edge cases
• Greater exposure to misconfiguration and attack

This is not a scaling API problem; it is a scaling trust problem.

FAST Security directly addresses this by standardizing how trust is established, enforced, and audited across organizational boundaries.

FAST Security as the Foundation of Trust Architecture

FAST Security is not designed to operate in isolation.

It provides the core trust workflows—authentication, authorization, and onboarding—that enable the broader FAST ecosystem:

• FAST Identity → Who is trusted
• FAST Security → How trust is enforced
• FAST Consent → What is permitted
• FAST Directory → Where trust is discovered

Together, these form a layered, reusable trust architecture aligned with modern interoperability demands.

This architecture allows trust to move from fragmented, one-off integrations to repeatable, scalable infrastructure.

New implementation community builds on global collaboration to improve
real-time device data exchange for AI-enabled care

Imagine a patient in an intensive care unit, monitored by a dozen devices generating streams of critical data every second.  From operating rooms and ICUs to ambulatory clinics and patient homes, clinicians and care teams rely on a growing ecosystem of medical and personal health devices. Now imagine that data is siloed, unable to flow into the EHR and unreachable by the analytics platform that might detect a dangerous trend before a clinician does.

This fragmentation is a well-known challenge in healthcare IT. On March 5, 2026, HL7 International took a major step toward solving it with the launch of the Caliper FHIR® Accelerator, a new implementation community dedicated to improving how data from medical and personal health devices is exchanged, integrated and used across healthcare systems. 

Why Caliper, and Why Now?

Caliper builds on HL7’s 2025 work with founding members to define a collaborative community focused on device interoperability. The need is clear: healthcare organizations are generating more high‑frequency device data than ever, but too often this information cannot flow cleanly into EHRs, analytics platforms or AI‑driven applications.

By leveraging HL7 FHIR alongside established device communication frameworks, Caliper aims to create a scalable, standards‑based foundation for real‑time device data integration. The goal is simple but transformative: ensure that data from critical care equipment and patient‑facing technologies can be shared consistently, reliably and safely.

“Healthcare systems are entering a new phase where access to high-quality, real-time data is essential to safely deploying advanced analytics and AI,” said Rachel Dunscombe, CEO of HL7 International. “The Caliper Accelerator represents an important step forward in ensuring that device-generated data, whether from critical care equipment or patient-facing technologies, can be shared and used consistently across care environments worldwide. This kind of foundational interoperability is critical to improving both clinical outcomes and operational resilience.”

Upcoming Da Vinci Community Roundtable on February 25 at 4:00 pm ET

As the federal government signals stronger enforcement and clearer expectations for healthcare pricing transparency, the ability for patients to make informed decisions has become a cornerstone of modern care efforts. The HL7® Da Vinci Project Community Roundtable, taking place on February 25, 2026, from 4 – 5:30 p.m. ET, will bring together the pioneers who are turning these regulatory expectations into reality.

The January roundtable set the stage for 2026 by focusing on overall use case progress and adoption readiness. This February session, “Navigating Patient Cost Transparency Using HL7 FHIR: Insights from Industry Leaders,” zooms in on Patient Cost Transparency (PCT), moving from the "why" of transparency to the "how" of implementation. Attendees will hear directly from early adopters about how they are navigating the complexities of Good Faith Estimates (GFE) and building the infrastructure for a more patient-centric ecosystem.

The upcoming 90-minute session will focus on:

• The Evolving Transparency Landscape: An overview of how recent federal actions and the No Surprises Act are driving an industry effort to increase transparency and empower patients.
  
• Standardizing Good Faith Estimates: Insights into the HL7 FHIR-based approach to PCT and how it automates the exchange of cost data between providers and payers.
• Real-World Pilot Progress: First-hand accounts from Aetna/CVS Health and Kyruus Health on how they are leveraging FHIR along with their existing infrastructure and previous work to streamline implementation of PCT, as well as lessons learned.
• The Role of Innovative Apps: How standardized data enables accurate, real-time access to medical costs via consumer-facing applications prior to the delivery of care.
• Collaboration Strategies: What organizations should keep in mind when working in an ecosystem-based solution, where it’s not just one group involved but a whole mix of partners that need to collaborate for success.

How States Can Move From Fragmented Programs to Shared, Scalable Infrastructure Using FAST

The CMS Aligned Networks Pledge marks a clear inflection point in federal health IT policy. For the first time, Centers for Medicare & Medicaid Services (CMS) is not simply setting compliance requirements for individual programs—it is asking the healthcare ecosystem to operate as connected networks, capable of secure, real-time, standards-based data exchange across payers, providers, public health and patients.

For states, this shift is significant.

States are no longer just one participant among many. They are increasingly the anchor for trust, identity, consent and directory infrastructure that enable CMS-aligned networks to function at scale. Medicaid programs, state CIO offices and HIEs sit at the intersection of policy, operations and technology. The CMS Aligned Networks Pledge makes that role explicit.

This blog explains:

1. What the CMS Aligned Networks Pledge really changes for states
2. Why traditional, program-by-program approaches will not scale
3. How the  HL7® FHIR® at Scale Taskforce (FAST)  provides the infrastructure states can reuse across initiatives
4. How states can leverage existing systems and vendors without starting over

The CMS Aligned Networks Pledge: A Shift from Programs to Infrastructure

Historically, CMS initiatives have been implemented as discrete programs:

• A new reporting requirement
• A new API mandate
• A new exchange use case
• Trusted digital identity and patient matching
• Scalable security and partner onboarding
• Computable, portable consent
• Authoritative directories for endpoint discovery

The CMS Aligned Networks Pledge represents a different expectation.

CMS is signaling that future interoperability depends on shared infrastructure capabilities, including:

• Trusted digital identity and patient matching
• Scalable security and partner onboarding
• Computable, portable consent
• Authoritative directories for endpoint discovery

These are not features of a single application. They are ecosystem functions.

For states, this means success is no longer measured by whether a single system goes live, but by whether multiple programs can reuse the same trust and exchange foundations.