The Standard

HL7 has announced the appointment of Professor Rachel Dunscombe as its new Chief Executive Officer effective January 19, marking the start of the organization’s next phase of growth in global health data interoperability. She succeeds Charles Jaffe, MD, PhD, who concludes nearly two decades of leadership at HL7.

Rachel brings extensive global experience in digital health, interoperability and standards-based transformation. Prior to joining HL7, she served as CEO of openEHR International, where she helped accelerate worldwide adoption of open health data standards and strengthened collaboration among governments, standards bodies and healthcare organizations.

Her career includes senior roles in healthcare delivery, national digital strategy, executive education and leadership in international standards communities. She has been recognized for her ability to unite diverse stakeholders and advance practical implementation of health data standards at scale.

Winners Recognized for Standards-Based AI Innovation, Collaboration and Real-World Impact

 Today, HL7 announced the winners of its first-annual HL7 AI Challenge, spotlighting innovators developing AI applications powered by open, standards-based frameworks in healthcare. The announcement was made during the morning session of HL7’s 39th Annual Plenary and Working Group Meeting (WGM) in Pittsburgh.

 Judges selected nine honorees from across multiple categories, recognizing innovation, collaboration and real-world impact.

 AI Challenge Overall Awardee Winners

• Robert Lario, PhD (Xzyos.ai) and Kevin Baskin, MD (Vanguard): AI-Conformable Venous Atlas: A Novel Solution for Clinical-Structural Correlation and Medical Device Surveillance
• Verto Health: VERTO Connect: A Solution to Healthcare's Unstructured Data Problem
• Quantek Systems, Inc: DynaMap AI – Active Inference-driven Clinical Workflow Engine

And six honorees were recognized for their contributions in the following specialized categories.

AI Challenge Category Winners

• Pioneer in Healthcare Innovation: (Ignyte Group and Appian) – Bring AI to Work(flow) – Provides robust process improvement throughout the patient lifecycle via AI agentic assistance
• Excellence in AI Transparency & Trust: (Trisotech) – Standardizing Clinical Autonomy: BPM+ Determinism and HL7 Integration for AI Agents
• Interoperability Leadership Award: (Whitefox Cloud Consulting) – Whitefox FHIR Converter
• Open Solution Award: (Omni Health Nexus) – The Intelligent Medical Assistant – Revolutionizing Information Management for Better Care
• Clinical Data Quality & Outcomes Award: (Aidbox Forms from Health Samurai)– AI Assistant for FHIR SDC and Analytics
• Transformative Impact in Healthcare Award: (Let’s Talk Doc) – AI Avatar Patient Communication Platform

Health IT Veteran Leaves Behind Legacy of Shared Data Standards and Interoperability Worldwide

 HL7 announced today that CEO Charles Jaffe, MD, PhD, will step down at the end of year, capping nearly 20 years of organizational leadership.

Under Dr. Jaffe, HL7 strengthened its role as a trusted convener for the global health data community; expanded adoption of foundational data standards, including HL7 Fast Healthcare Interoperability Resources (FHIR®), Clinical Document Architecture (CDA® ), and the HL7 Version 2 messaging standard. He oversaw the integration of HL7 standards into federal regulations and championed worldwide implementation of FHIR to enable scalable, interoperable solutions across providers, payers and technology vendors.

 “On behalf of the board of directors, I want to thank Chuck for his outstanding leadership and commitment to HL7 members, partners and employees, as well as his tremendous success guiding the organization through nearly two decades of evolution and growth,” said Julia Skapik, MD, MPH, Chair of the HL7 Board of Directors. “Under his leadership, HL7 has continued to strengthen its role in advancing interoperability and delivering value to the health care community worldwide.”

Since joining the organization as its first CEO in 2007, Jaffe’s tenure has been marked by innovation, strategic expansion and enhanced international collaboration, positioning HL7 as the architect in shared standards development worldwide.

New Group Advances Workflow and Process Interoperability Using HL7^® FHIR^®

HL7 is pleased to announce the official launch of its HL7 Business Process Modeling (BPM) Community of Practice. Now open for membership, the community is dedicated to advancing interoperability, process consistency, and process automation through the use of formal modeling techniques promoting better modeling, sharing, and execution of clinical and administrative workflows across the healthcare ecosystem.

BPM Community of Practice builds upon three open standards-based languages – referenced together as “BPM+”, and include:  

• BPMN (Business Process Model and Notation): For prescriptive workflows
• CMMN (Case Management Model and Notation): For reactive activities
• DMN (Decision Model and Notation): For complex decision-making rules

The use of these standards, in concert, allows inherent ambiguities in natural-language guidelines to be clarified, providing precise, automatable guidance to improve care quality and consistency. Organizations use BPM+ to model and streamline processes, ensuring accurate and scalable healthcare delivery, process consistency, comparability, and repeatability.

“HL7’s focus is on bringing together communities to advance all aspects of interoperability, and that includes workflow and care processes,” said Ken Rubin, Community Coordinator of the HL7 BPM Community of Practice. “This launch marks an important step in providing the healthcare industry with tools, models, and frameworks to manage care processes more effectively, consistently, and collaboratively.”

Dr. Daniel Vreeman Named Chief AI Officer to Drive Organization's Strategic AI Agenda

HL7 has launched an Artificial Intelligence (AI) Office to establish foundational standards for safe, trustworthy AI in healthcare and convene the global community driving this transformation.

The new office positions HL7 at the forefront of healthcare's AI revolution, creating frameworks that ensure emerging technologies are trusted, explainable, interoperable, and scalable across clinical, operational, and research settings worldwide.

"Artificial intelligence will fundamentally reshape healthcare delivery, evaluation, and payment," said Charles Jaffe, MD, PhD, CEO of HL7 International. "Our new AI Office positions HL7 as the trusted global convener for responsible, standards-driven AI innovation—ensuring these transformative technologies deliver on their promise to improve health for all."

To lead this initiative, HL7 has appointed Daniel Vreeman, DPT, as its first Chief AI Officer (CAIO). Dr. Vreeman will expand his current role as Chief Standards Development Officer to drive HL7's comprehensive AI strategy, including the HL7 AI Challenge, anti-fraud initiatives, and collaborations with regulators and industry partners globally.

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.

Learn about HL7's Fonteva Implementation