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Master of Science - Health Informatics Concentration

The science of health informatics drives innovation-defining future approaches to information and knowledge management in biomedical research, clinical care, and public health. Health informatics (HI) comprises applied research and the practice of informatics across clinical and public health domains. Informatics researchers develop, introduce, and evaluate new biomedically motivated methods in areas as diverse as data mining, natural language or text processing, cognitive science, human-computer interaction, decision support, databases and algorithms for analyzing large amounts of data generated in public health, clinical research and genomics/proteomics.

The MS degree will provide 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, data science and more broadly health policy, social and behavioral science, biostatistics and epidemiology. The length of study for the MS in HI is two academic years. 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. The degree also requires a capstone project in the second year.

Applicants should typically have an undergraduate degree with a focus in health, computer science and mathematics/statistics. Students with a master’s degree or other related degrees may be allowed to enroll in additional elective courses in lieu of required courses, if they can demonstrate prior proficiency in required courses.

Apply

For more information and to apply to the MS program, visit the Yale Graduate School of Arts and Sciences website. Please choose "Public Health" as the program. Then select Biostatistics as the concentration. Do not try to use SOPHAS.

Degree Requirements - MS in Health Informatics

2020-21 Matriculation

The M.S. degree requires a total of 14 course units. The M.S in Health Informatics requires the student to complete or acquire an exemption from the following courses. Full time students must carry a minimum of 4 course units each semester. If a course is waived, a substitute course must be identified.

MS Required Courses (10 course units)

  • BIS 633 Population and Public Health Informatics - 1 unit
  • BIS 634 Computational Methods for Informatics - 1 unit
  • CBB 740/ BIS 560 Introduction to Health Informatics - 1unit
  • CBB 750/ BIS 550 Core Topics in Biomedical Informatics - 1 unit
  • EPH 508 Foundations of Epidemiology and Public Health - 1unit
  • EPH 608 Frontiers of Public Health * - 1 unit
  • BIS 638 Clinical Database Management Systems and Ontologies - 1 unit
  • BIS 562 Clinical Decision Support - 1 unit
  • EPH 600 Research Ethics and Responsibilities - 0 units
  • BIS 685 Capstone I- 1 unit
  • BIS 686 Capstone II - 1 unit

MS Suggested Electives in Informatics, Statistics and Data Science (4 course units)

Four of the following:

  • BIS 540 Fundamentals of Clinical Trials - 1 unit
  • BIS 557 Computational Statistics - 1 unit
  • BIS 567 Bayesian Statistics - 1 unit
  • BIS 621 Regression Models for Public Health - 1 unit
  • BIS 628 Longitudinal and Multilevel Data Analysis - 1 unit
  • BIS 643 Theory of Survival Analysis - 1 unit
  • BIS 679 Advanced Statistical Programming in SAS and R - 1 unit
  • BIS 691 Theory of Generalized Linear Models - 1 unit
  • CB&B 555 Unsupervised Learning for Big Data - 1 unit
  • CB&B 567 Topics in Deep Learning: Methods and Biomedical Applications - 1 unit
  • CB&B 645 Statistical Methods in Computational Biology - 1 unit
  • CDE 566 Causal Inference Methods in Public Health Research - 1 unit
  • CPSC 546 Data and Information Visualization - 1 unit
  • CPSC 577 Natural Language Processing - 1 unit
  • CPSC 564 Topics in Foundations of Machine Learning - 1 unit
  • EMD 533 Implementation Science - 1 unit
  • EPH 510 Health Policy and Health Care Systems - 1 unit
  • HPM 560 Health Economics and U.S. Health Policy - 1 unit
  • HPM 570 Cost-Effectiveness Analysis and Decision-Making - 1 unit
  • IMED 625 Principles of Clinical Research - 1 unit
  • NURS 922 Introduction to Clinical Research Informatics - 1 unit
  • MGT 534 Personal Leadership - 1 unit
  • MGT 656 Managing Software Development - 1 unit
  • S&DS 530 Data Exploration and Analysis - 1 unit
  • S&DS 555 Introductory Machine Learning - 1 unit
  • S&DS 562 Computational Tools for Data Science - 1 unit
  • S&DS 565 Applied Data Mining and Machine Learning - 1 unit
  • S&DS 583 Time Series with R/Python - 1 unit
  • S&DS 584 Applied Graphical Models - 1 unit
  • S&DS 610 Statistical Inference - 1 unit
  • S&DS 663 Computational Methods for Data Science - 1 unit
  • S&DS 664 Information Theory - 1 unit
  • S&DS 670 Theory of Deep Learning - 1 unit

*Students entering the program with an MPH or relevant graduate degree may be exempt from this requirement.

rev. 5.20.2020