Health Informatics Concentration (HI)

The M.S. with a concentration in Health Informatics is a two-year program that provides well-rounded training in health informatics, with a balance of core courses from such areas as information sciences, clinical informatics, clinical research informatics, consumer health and population health informatics, and data science, and more broadly health policy, social and behavioral science, biostatistics, and epidemiology. First-year courses survey the field; the typical second-year courses are more technical and put greater emphasis on mastering the skills in health informatics.

Applicants should typically have an undergraduate degree with a focus in health, computer science, and mathematics/statistics. Students whose native language is not English must take and submit scores from the TOEFL or IELTS examination. Part-time enrollment is not permitted.

Degree Requirements

The Health Informatics concentration consists of a total of fourteen courses: eight required courses, four electives, and satisfactory completion and presentation of a yearlong, two-course capstone project. Students demonstrating a mastery of topics covered by the required courses may replace them with more advanced courses but must receive written permission from the DGS and their adviser prior to enrolling in the substitute courses.

The graduate school requires an overall grade average of High Pass, including grades of Honors in at least two full-term graduate courses for students enrolled in a two-year program. In order to maintain the minimum average of High Pass, each grade of Pass on the student’s transcript must be balanced by one grade of Honors. Each grade of Fail must be balanced by two grades of Honors. If a student retakes a course in which the student has received a failing grade, only the newer grade will be considered in calculating this average. The initial grade of Fail, however, will remain on the student’s transcript. A grade awarded at the conclusion of a full-year course in which no grade is awarded at the end of the first term would be counted twice in calculating this average.


Required Courses

BIS 550Topics in Biomedical Informatics and Data Science1
BIS 560Introduction to Health Informatics1
BIS 562Clinical Decision Support1
or BIS 640 User-Centered Design of Digital Health Tools
BIS 633Population and Public Health Informatics1
BIS 634Computational Methods for Informatics1
BIS 638Clinical Database Management Systems and Ontologies1
BIS 685Capstone in Health Informatics1
BIS 686Capstone in Health Informatics1
EPH 508Foundations of Epidemiology and Public Health1
or EPH 509 Fundamentals of Epidemiology
EPH 608Frontiers of Public Health 11
MS Suggested Electives in Informatics, Statistics and Data Science (4 course units)
BIS 540Fundamentals of Clinical Trials1
BIS 567Bayesian Statistics1
BIS 568Applied Artificial Intelligence in Healthcare1
BIS 620Data Science Software Systems1
BIS 621Regression Models for Public Health1
BIS 623Advanced Regression Models1
BIS 628Longitudinal and Multilevel Data Analysis1
BIS 630Applied Survival Analysis1
BIS 662Computational Statistics1
BIS 691Theory of Generalized Linear Models1
BIS 692Statistical Methods in Computational Biology1
CB&B 555Unsupervised Learning for Big Data 11
CB&B 567Topics in Deep Learning: Methods and Biomedical Applications 11
CB&B 663Deep Learning Theory and Applications 11
CDE 534Applied Analytic Methods in Epidemiology1
CDE 566Causal Inference Methods in Public Health Research1
CPSC 540Database Design and Implementation 11
CPSC 546Data and Information Visualization 11
CPSC 564Algorithms and their Societal Implications 11
CPSC 577Natural Language Processing 11
CPSC 581Introduction to Machine Learning 11
CPSC 582Current Topics in Applied Machine Learning 11
CPSC 583Deep Learning on Graph-Structured Data 11
CPSC 670Topics in Natural Language Processing 11
EMD 533Implementation Science1
EMD 553Transmission Dynamic Models for Understanding Infectious Diseases1
ENAS 544Fundamentals of Medical Imaging1
EPH 510Health Policy and Health Care Systems1
HPM 559Big Data, Privacy, and Public Health Ethics1
HPM 560Health Economics and U.S. Health Policy1
HPM 570Cost-Effectiveness Analysis and Decision-Making1
HPM 573Advanced Topics in Modeling Health Care Decisions1
IMED 625Principles of Clinical Research 11
INP 560R Stats for Neuroscience1
MGT 534Personal Leadership 24
MGT 612Introduction to Social Entrepreneurship 24
MGT 656Management of Software Development 24
S&DS 517Applied Machine Learning and Causal Inference 11
S&DS 530Data Exploration and Analysis 11
S&DS 562Computational Tools for Data Science 11
S&DS 563Multivariate Statistical Methods for the Social Sciences 11
S&DS 565Introductory Machine Learning 11
S&DS 583Time Series with R/Python 11
S&DS 610Statistical Inference 11
S&DS 663Computational Mathematics Situational Awareness and Survival Skills 11
S&DS 664Information Theory 11

In addition, in the second year of the program, students are required to complete an independent capstone project (BIS 685/BIS 686) under the direction of a faculty member. This project may fall into one of the main areas—clinical informatics; clinical research informatics; population health informatics; and implementation of new methods and technology—and may include elements from several of these areas. Students are required to prepare a carefully written report and make an oral presentation of the work to the faculty and students. A capstone committee consisting of two faculty members and one outside reader will provide guidance to the candidate as to the suitability of the project and will monitor its progress.


Upon receiving an M.S. in the Health Informatics concentration of Public Health, the student will be able to:

  • Select informatics methods appropriate for a given public health context
  • Compare the health information system structure and function across regional, national, and international settings
  • Assess population informatics needs, assets, and capacities that affect communities’ health
  • Propose strategies to identify stakeholders and build coalitions and partnerships for influencing public health informatics
  • Communicate audience-appropriate public health content, both in writing and through oral presentation
  • Apply systems thinking tools to a public health informatics issue