Professor of Biomedical Informatics & Data Science; Vice Chair for Education, Biomedical Informatics & Data Science; Professor, Biostatistics
Clinical Informatics & Data Science (MHS-CIDS) Track
The Clinical Informatics and Data Science MHS is designed for graduates with clinical backgrounds who wish to gain competency in informatics and data science through core required courses and research activities. The science of informatics drives innovation that is defining future approaches to information and knowledge management in biomedical research and healthcare. Biomedical data science includes the design, implementation, and evaluation of statistical learning/machine learning models for pattern recognition, diagnosis, and prognosis, as well as other artificial intelligence (AI) models.
Program Objectives
Objectives include providing well-rounded training in clinical informatics and data science, with a balance of core courses from such areas as information sciences, clinical informatics, clinical research informatics, data science, and statistics. Graduates of this program will be equipped to develop, introduce, and evaluate new biomedically motivated methods in areas as diverse as clinical decision support, data mining, natural language or text processing, human-computer interaction, databases, and algorithms for analyzing large amounts of data generated in health, clinical research, and genomics/proteomics.
Course & Graduation Requirements
Required courses cover basics of clinical informatics and data science; other courses and topics cover clinical decision support, computer system architectures, networks, security, data management, human factors engineering, clinical data standards, analytical methods and data science, and medical AI.
Also, the curriculum includes other courses and electives including leadership models, processes, and practices, effective interdisciplinary team management, effective communications, project management, strategic and financial planning for clinical information systems, and change management. There is also a leadership development course shared across tracks.
To graduate, participants must write a research paper for submission, and present their research.
| Sample Outline of Required Coursework: MHS-Clinical Informatics & Data Science | Year 1 Summer | Year 1 Fall | Year 1 Spring | Year 2 Summer | Year 2 Fall | Year 2 Spring |
|---|---|---|---|---|---|---|
| IMED 645: Introduction to Biostatistics in Clinical Investigation | X | | | | | |
| IMED625: Principles of Clinical Research | X | | | | | |
| IMED630: Ethical Issues in Biomedical Research | | X | | | | |
| BIS 560/CBB 740: Introduction to Health Informatics | | X | | | | |
| Elective 1 | | | X | | | |
| Elective 2 | | | | | X | |
| Elective 3 | | X | ||||
| Mentored Research Project | X | X | X | X | X | X |
| MHS Research in Progress Series | | X | X | X | |
Time Allowance & Department Commitment
For candidates who are currently employed, this is a two-year program requiring a 50-75% time commitment. If you are a YSM resident, fellow, or faculty your department chair or division chief must approve this time commitment in writing. This program is intended for those who plan to pursue a career at Yale. While this is not a strict requirement, because of Yale’s investment in the participant, it will be an important consideration. If a participant is unable to complete the degree in two years, approval of an extension is required by the Yale MHS Degree Program and the Track Academic Director.
Contact Us & Track Leadership
Questions?
For questions, contact the track director, Cynthia Brandt, MD, MPH.