The Standard

Innovators worldwide invited to demonstrate how HL7 standards and
AI can revolutionize healthcare

HL7 is proud to announce the launch HL7 AI Challenge 2025, a global innovation competition designed to spotlight the transformative potential of artificial intelligence (AI) when powered by open health data standards. Selected winners will be recognized on stage during HL7’s 39th Annual Plenary, Working Group Meeting, September 13-19, 2025, in Pittsburgh.

The HL7 AI Challenge is open to any individual, team or organization across academia, industry, and government using HL7 standards to power AI applications that solve real-world clinical, operational or equity-focused problems. HL7 membership is not required, and there is no cost to participate.

 The competition builds on HL7’s long-standing commitment to enabling interoperable, standards-based healthcare innovation and reflects growing global interest in aligning AI adoption with ethical, explainable and secure data practices.

“As AI becomes more deeply embedded in healthcare, we must ensure it advances—not undermines—trust, transparency, and patient outcomes,” said Dr. Charles Jaffe, CEO of HL7 International. “The HL7 AI Challenge invites technologists, researchers and clinicians worldwide to showcase how open standards can anchor responsible, scalable AI innovation, bridging the health IT and AI communities for the benefit of all.”

New publication outlines opportunities for accelerating and improving the use of AI to support payment integrity and reduce fraud, waste, and abuse

Last week, HL7 International released a new report outlining the actions needed to fully realize the benefits of artificial intelligence (AI) in improving payment integrity and reducing fraud, waste, and abuse. Reducing Fraud and Improving Payment Integrity in Healthcare Through the Use of AI brings together insights from payers, providers, and technology experts to define AI opportunities and emerging solutions, current challenges, implementation strategies, and standards needed to increase transparency and trust.

“The U.S. spends more than $900 billion annually on administrative complexity, waste, and improper payments,” said Charles Jaffe, MD, PhD, CEO of HL7 International. “This publication identifies practical and standards-based approaches to harnessing AI for one of healthcare’s most persistent and costly challenges.”

Key recommendations from the report include:

• Developing standards for explainable AI in healthcare with specific transparency requirements and bias mitigation protocols.
• Creating standards and infrastructure for trust and verification of AI-generated results.
• Establishing frameworks for human-in-the-loop validation that balance automation with clinical expertise.
• Implementing pilot programs focused on provider-payer collaboration that create mutually beneficial scenarios for all stakeholders.

A report from the HL7 Da Vinci Project describes how two pioneering organizations demonstrated the real-world practicality and value of applying standard application program interfaces (APIs) to streamline the prior authorization process.

Regence, a payer based in the Pacific Northwest, and MultiCare Health System, a provider based in Washington state, spent about a year testing and fine-tuning processes that leverage HL7’s Fast Healthcare Interoperability Resources (FHIR^®) standard for APIs.

In addition, dozens of other organizations have tested FHIR APIs at more than 15 Connectathon testing events.

"Our response to interoperability isn’t just about managing data—it’s about building the future of healthcare through open standards." - Dan Vreeman, DPT, Chief Standards Development Officer, HL7 International

Last week at Civitas 2024 in Detroit, HL7 International/s Chief Standards Development Officer,Dan Vreeman, DPT, led an insightful panel session on how HL7® Fast Healthcare Interoperability Resources (FHIR®) is revolutionizing interoperability. As data sharing becomes increasingly critical, HL7 is at the forefront, driving collaboration with over 45 organizations and developing 35-45 new FHIR implementation guides annually! Dan was joined by leaders from the Da Vinci Project, FAST, Gravity Project, and Helios, to discuss their HL7 FHIR Accelerator projects, including objectives and progress made to date in advancing open data standards development and interoperability.

Health Level Seven International (HL7^®), the global authority on interoperability of health information technology with members in 55 countries, announced election results for its board of directors, international council and technical steering committee during its annual business meeting at the 38th Annual Plenary and Working Group Meeting in Atlanta.

Chair-Elect

The membership selected Carol Macumber, executive vice president of Clinical Architecture, as chair-elect in 2025 and board chair for 2026-2027.

HL7 Board Member Elections

The following members were elected to the HL7 board of directors for the 2025-2026 term:

• Secretary — Yan Heras, Ph.D., principal, Optimum eHealth LLC
• Director — Gora Datta, FHL7, chairman and chief executive officer, CAL2CAL Corporation
• Director — Ken Rubin, FHL7, senior advisor, standards and interoperability, CIDMO, U.S. Department of Veterans Affairs
• Affiliate Director — Ron Parker, FHL7, chair, HL7 Canada; principal, Parker Digital Health Consulting Inc
• Affiliate Director — Line Saele​, chair, HL7 Norway; enterprise architect, Norwegian Institute of Public Health

5 Tips for Getting Your App/Pilot/Project from Idea to Implementation

Are you ready to identify healthcare partners for your real-world pilot?

Have an app developed, but don’t know how to break into healthcare?

Or, perhaps you’ve received a “yes” from healthcare, but now find yourself in a spiral of administrative approvals.

We all have impactful, valuable projects; however, at least in the case of healthcare, we are navigating an industry facing myriad challenges – financial pressure, staff shortages, regulatory compliance. Make it easy for them to work with you and you’ll find a smoother path forward.

At HL7's January’s FHIR Connectathon and Working Group Meeting, Adele Stewart and Elizabeth Sprouse of Double Lantern Informatics hosted the education session “From Ghosted to Welcomed: Developing FHIR-based solutions with healthcare technology acceptance in mind.” Here are five tips from their talk. Want the rest of the scoop? Catch the full talk here.

1. Understand workflow implications.

Build relationships with people in clinical informatics. These individuals will often help you understand workflow implications to your project that must be considered, such as:

• Will you need to save data back to the electronic health record?
• If you need to save back to the chart, how do you navigate this?
  • Where will it be saved?
  • Does the project involve a note that needs to be signed and/or support co-signature?
  • Does a Health Information Management committee need to be involved?
• Does your solution involve a clinical alert? At the healthcare site, is clinical committee review needed for new alerts?
• How will your project alter the current workflow and what training and communications must accompany go-live?

After 32 years of serving HL7 International as the Executive Director, Mark McDougall will retire at the end of this year. HL7 leadership would like to acknowledge Mark's significant contributions to the organization across the decades.

Andy Truscott, FHL7, HL7 Board Chair states, "Mark's unwavering commitment and visionary leadership have been pivotal in advancing healthcare standards and interoperability across our organization. As Executive Director, Mark consistently demonstrated an extraordinary dedication to our mission. His ability to navigate the ever-evolving landscape of healthcare informatics and standards development has been instrumental in shaping HL7 into the dynamic organization it is today. Mark's passion for improving healthcare outcomes through enhanced interoperability has not only guided our work but has served as an inspiration to us all.

As Mark prepares to embark upon retirement, we wish him all the best in his future endeavors. His legacy within HL7 will be enduring, shaping the way we approach healthcare standards and data exchange for years to come.

We acknowledge and honor his exemplary service and commitment to our cause. Thank you, Mark, for your invaluable contributions, and we wish you a retirement filled with happiness, health and new adventures."

This blog post was created through discussion over the past year among various payers, federal entities, providers, quality organizations, and HL7 staff with a focus on the importance of standardized data collection and management of race and ethnicity data. The discussion below represents a synthesis of these themes and identifies ways HL7 can help support the field.

High-quality, reliable, data are key to facilitating achievement of health equity, “the state in which everyone has a fair and just opportunity to attain their highest level of health”. This includes the collection, analysis and sharing of race and ethnicity data. However, misaligned approaches to standardized data collection present challenges to action. In addition, many organizations lack awareness of or experience challenges in applying standards when collecting and exchanging such data. In this blog, we explore existing resources that can help facilitate standardized data collection and management – HL7 is here to help.

The collection of high-quality race and ethnicity data is essential to address preventable differences - disparities - in health and healthcare. Such data are used to drive assessments, identify gaps, and the support decision-making that leads to actions to close gaps while improving outcomes. There are documented use cases by payers, providers, policymakers, and industry, for research, quality improvement and care delivery purposes. These use cases demonstrate how creating more inclusive datasets can support efforts to reduce health disparities and increase access to higher-quality care for historically marginalized communities. For example, race and ethnicity data can help provide transparency on disparate access to and uptake of services that can lead to targeted quality improvement and enhanced services for under-resourced populations. For this to occur, reliable, accurate, and consistent data are needed.