Rapid advancements in biotechnologies and health information technology have transformed the landscape of healthcare data generation and utilization. The widespread adoption of electronic health records (EHRs), wearables and smart devices, and social media platforms has produced an unprecedented volume and variety of health-related data. Effectively harnessing these rich data sources requires a workforce skilled in managing, analyzing, and interpreting complex health information to improve care delivery, research, and decision-making. Consequently, the demand for well-trained Health Informatics (HI) professionals and researchers has grown sharply. To meet this need, many new HI education programs have emerged in the past decade. Broadly defined, health informatics covers diverse fields such as medical informatics, data science, health information management, public health informatics, nursing informatics, dental informatics, pathology informatics, health care administration, and other related domains.

Researchers and educators have invested substantial time and efforts in identifying effective strategies for providing high-quality HI education to equip graduates with the knowledge and skills needed to successfully overcome the challenges they face in their careers. However, as an inherently interdisciplinary field, HI education varies widely across institutions and regions, reflecting diverse pedagogical models, curricular structures, and implementation challenges. Moreover, the vast volume of health data presents unprecedented opportunities and obstacles, particularly in providing students with hands-on experiences using real-world data to address real-world healthcare problems. In addition, the rapid progress in generative AI technologies and the corresponding applications has introduced new complexities. Tools such as ChatGPT, Gemini, and Claude are increasingly used by students to assist with coursework, raising important questions about academic integrity, assessment validity, and how best to integrate these emerging technologies into HI education.

To shape the future of health informatics education, the 2026 International Workshop on Health Informatics Education (HI-EDU 2026) will provide a unique platform for close interactions among educators, researchers, students, scholars, and industry professionals who are interested in HI education. We are calling for papers and abstracts that highlight novel approaches, works in progress projects, and original state-of-the-art developments in training activities, program development, education research, tools and resources for HI education and case studies.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

• Regular papers (8-10 pages, including references) will describe mature ideas, where a substantial amount of implementation, experimentation, or data collection and analysis has been completed.
• Short papers (4-6 pages, including references) will describe innovative ideas, where preliminary implementation and validation work have been conducted.
• Abstracts (1 page, including references) will describe your vision, work in progress and preliminary results.

Your submissions must adhere to the IEEE Proceedings Format. All papers will be submitted and handled through EasyChair. Submissions must contain the names and affiliations of authors listed on the paper. The review process will be single-blinded.

List of Topics

• HI Education Research: Original studies on teaching and learning in HI, including the impact of emerging technologies such as LLMs and Generative AI on education and training.
• Education Program Development and Curriculum Improvement: Design, implementation, and evaluation of HI education programs and curricula.
• Pedagogy for High-Quality HI Education: Novel pedagogical approaches, instructional design, and active learning strategies. • Tools and Resources for HI Education: Development and use of educational tools, datasets, simulation environments, apps, and LLM/GAI-based platforms for HI teaching and practice
• Challenges in HI Education: Barriers, challenges, and ethical considerations facing the HI education and training, for instance, assessment integrity and responsible AI adoption related to students’ use of LLM for coursework
• The Current State of HI education: Global perspectives on HI education and training, including the role of AI, LLMs, and automation.
• Opportunities and Constraints: Emerging opportunities for HI education innovation through AI integration, as well as limitations related to resources, accessibility, or policy.
• Case Studies: Best practice, research projects, and case studies in HI education and training

Committees

Program Committee

• TBA

Organizing committee

• Leming Zhou, PhD, FAMIA, Leming.Zhou@pitt.edu, University of Pittsburgh, US
• Huanmei Wu, PhD, FAMIA, huanmei.wu@temple.edu, Temple University, US
• Chiu C Tan, PhD, cctan@temple.edu, Temple University, US.

Publication

All accepted submissions will be published in IEEE Xplore and indexed in other Abstracting and Indexing (A&I) databases. Accepted papers and abstracts have an oral presentation slot at the conference.

Venue

The conference will be held in Minneapolis, MN, USA.

Contact

All questions about submissions should be emailed to Leming.Zhou@pitt.edu.