Clinical Informatics Track
The Clinical Informatics track provides instruction and training for students interested in clinical applications methods and applications. The curriculum includes instruction in health data and coding, systems analysis, human-computer interaction, current informatics research, and current applications such as decision support systems, natural language processing, and predictive modeling. Additionally, students learn biostatistical methods, relational database theory and practice, analytics and data science methodologies, consumer health informatics, and interprofessional practice. Electives supplement individual student interests in areas such as computer programming, health data management, health care finance, and public and population health (with scope to include person-empowered participation and inter-professional engagement). Courses use a mixture of theoretical and applied subject matter to provide a solid grounding in current informatics thinking and practice.
Students who pursue the Clinical Informatics track must complete the Health Informatics MS degree en route to completing the PhD. Students who have an MS in Health Informatics from a comparable program may be exempt from this requirement in whole or in part, subject to program review and approval.
Rui Zhang, PhD
Associate Professor and McKnight Presidential Fellow, Core Faculty