Domain Elective Courses: 19 units minimum of domain electives course work is required.

The UC Davis Health Informatics program works with several graduate schools to offer additional domain courses, not listed below. These are available with approval of the student’s academic advisor.

MHI 207 — Medical Decision Support

Units: 4
Instructor: Prabhu Shankar, M.D., M.S.

Course description: Course explores decision support systems for medical application. Topics include medical decision making, uncertainty, review of existing decision support systems, knowledge engineering, data mining, and knowledge based systems.

MHI 208 — Health Informatics in Web-Based Enterprise

Units: 4
Instructor: Mark J. Carroll, M.P.H.

Course description: The purpose of the course is to introduce the student to the decision making processes and technologies that are involved in developing web-based distributed enterprise applications in medicine. With a focus on the informatician's role as a team member.

MHI 212 — Computer Security in Health Informatics

Units: 2
Instructor: Sean Peisert, Ph.D.

Course description: Critical thinking about basic concepts in computer security and privacy. How the computer security and privacy impact health informatics, ranging from electronic health records to telemedicine to remote, virtual surgery.

MHI 289E — Clinical Knowledge for the Health Informaticist

Units: 3
Instructor: Prabhu Shankar, M.D., M.S.

Course description: This course will study the basics of various clinical systems, such as Respiratory, Endocrine and others, when affected by disease.  The focus is on the vocabulary usage, workflows followed while caring, and the healthcare stakeholder requirements while managing the complex, data-intensive patien care.  Students will be introduced to informatics needs of data access, curation, and delivery across clinical disease-focused domains dependent on interoperable and heterogeneous data systems.

MHI 289F — Database and Knowledge Management

Units: 4
Instructor: Matthew Lange, Ph.D.

Course description: Introduces the student to the relational database concepts of normalization, SQL queries and interface design. Students start with basic text filed requirements and go through the process of sequential development of a logical data model followed by normalization to a 3rd normal form and implementation of a physical data model.

MHI 289I — Applied Progamming in Health Informatics

Units: 3
Instructor: Matt Bishop, Ph.D.

Course description: This course will use an applied, intensive and development-focused curriculum to provide students with the skills for accessing, manipulating and evaluating health informatics data.  The course will use Python to develop and analyze real-world datasets.  The course will also provide the foundational skills and tools essential to health data alignment, integration and analysis.