Yale Clinical Informatics Fellowship

Few fellowships combine immersive training across a leading academic health system and the nation's largest integrated healthcare system with the resources of one of the world's premier research universities. Yale fellows gain hands-on operational experience while leveraging a multidisciplinary informatics ecosystem, graduate coursework across the university, and the option to pursue a Master of Health Sciences in Clinical Informatics & Data Science.

Yale New Haven Health offers enterprise-scale experience in clinical operations, AI implementation, digital health, clinical decision support, and health system innovation across a multi-state academic health system. Fellows work alongside operational leaders deploying technologies that improve care while gaining exposure to the strategic governance and leadership required to scale innovation across a modern healthcare enterprise.

VA Connecticut Healthcare System provides experience within the nation's largest integrated healthcare system, including national-scale informatics, interoperability, implementation science, federal health IT, quality improvement, and one of the world's largest clinical data environments. Fellows contribute to operational and research initiatives that improve care for Veterans while collaborating with national VA informatics and research leaders.

Together, these complementary environments—combined with Yale's unparalleled academic resources—provide exceptional breadth in operational, technical, and leadership training.

The fellowship provides access to one of the nation’s most comprehensive ecosystems for biomedical, clinical, and health informatics, artificial intelligence, clinical data science, and medical research.

Within the School of Medicine, at the Department of Biomedical Informatics & Data Science (BIDS) and Yale Biomedical Informatics & Computing (YBIC), fellows collaborate with leading investigators and gain access to secure clinical data, advanced computing infrastructure, and AI research. Beyond the School of Medicine, this ecosystem extends through partnerships with the Department of Biostatistics at the Yale School of Public Health and the Harvey Cushing/John Hay Whitney Medical Library, which provide expertise in statistical methods, data science, biomedical informatics, bioinformatics, and research computing.

Graduate coursework is available through programs in Computational Biology & Biomedical Informatics (CB&B), Health Informatics, and the optional pursuit of a Master of Health Sciences in Clinical Informatics & Data Science, with additional opportunities in Biostatistics, Computer Science, Management, Investigative Medicine, Statistics & Data Science, allowing fellows to tailor their education to their career goals.

No two fellows follow the same path.

Working closely with operational leaders and nationally recognized faculty, fellows develop expertise in areas such as:

• Artificial intelligence and clinical decision support
• Clinical data science and predictive analytics
• Learning health systems and implementation science
• Human-centered design and workflow redesign
• EHR governance, interoperability, and digital health
• Clinical research informatics

Rather than observing informatics, fellows become integral members of multidisciplinary teams designing and deploying technologies that improve patient care.

Our greatest strength is individualized mentorship and professional development.

Working within the ACCELERATE Clinical Informatics & Digital Innovation Laboratory, fellows work closely with the program director and faculty throughout both years, receiving longitudinal mentorship in leadership, research, technical skills, career development, scientific writing, and national networking. This apprenticeship model enables fellows to build deep expertise, meaningful collaborations, and lasting professional relationships.

Life in New Haven

Graduates leave prepared to lead clinical informatics across academic medicine, health system leadership, and industry.

Our alumni have pursued careers in faculty leadership, NIH-funded research, enterprise informatics, clinical AI, digital health, and healthcare technology.