Program Overview

Introduction to the MS in Medical Informatics Program

The Master of Science degree in Medical Informatics at Dartmouth provides rigorous training in applying informatics to the field of medicine, analyzing how to streamline processes and make continuous improvements to patient care.

Program Overview

The program includes a 2-unit capstone that challenges students to refine their data science skills within medical informatics while working on a real-world applied data project. Beyond showcasing technical knowledge, the capstone experience also provides training in critical skills needed for professional success, such as scientific writing, presentation skills, and the ability to translate data science findings to non-data science stakeholders.

Curriculum Structure

• The academic year is divided into four terms.
  • Throughout the academic year, students will take core and elective courses, with core coursework emphasizing topics in computer science, biostatistics, health services research, cost-effectiveness analysis, and decision-making analyses and algorithms.
  • Toward the second half of the year, students will wrap up remaining electives and complete capstone coursework.
• Students need to complete a minimum of 15 units to graduate; core courses are required, and students can choose from several elective options to complete their degree.
• The capstone course will take place in the final, Summer term.
• Students take classes full-time, with approximately 55 hours per week combined coursework and class-time.
• Classes begin in September with graduation in August of the next year.

Academic Calendar

To see the courses offered by term for the MS in Medical Informatics On-Campus program, view the academic calendar. Beginning 2026, this program will begin in the fall.

Learning Objectives

• Core competency in bioinformatics and biostatistics, and epidemiology.
• Competency in foundational biostatistics for complex statistical modeling of public health data.
• The ability to adapt and interpret epidemiological study designs for primary and post-hoc outcomes.
• The ability to identify and validate molecular markers for use in clinical research.
• Working knowledge of clinical, global, molecular, and environmental exposure epidemiology.

Core Coursework

The Medical Informatics curriculum includes required core courses that allow students to dive into concepts such as applied epidemiology, biostatistics, machine learning, molecular biology, and healthcare systems.

Core Courses

• Data Analysis and Visualization
  • HSE 180 Data Visualization
  • HSE 181 Data Wrangling
• Biostatistics
  • HSE 119 Applied Biostatistics OR HSE 120 Foundations of Biostatistics I: Statistical Theory
  • HSE 121 Foundations of Biostatistics II: Statistical Modeling
• Epidemiology
  • HSE 130 Foundations of Epidemiology I: Theory and Methods
• Medical Informatics
  • HSE 140 Decision & Cost Effectiveness Analysis
  • HSE 139 Advanced Methods in Health Services Research
  • PH 147 Advanced Health Services Research with ILE Project
  • HSE 194 Biostatistics Journal Club
  • HSE 192 Health Informatics
  • HSE 271 Advanced Epidemiology Journal Club (not offered every year)
• Computer Science
  • HSE 103 Foundations of Data Science
  • HSE 101 Foundations of Programming for Data Scientists
  • HSE 101.1 Intermediate Programming for Data Scientists
• Professional Development
  • HSE 185.5 Essential Skills for Career Development and Leadership
• Capstone
  • HSE 185 Masters Capstone

Elective Coursework

Through the Medical Informatics elective course options, students can dive deeper into advanced concepts such as applied epidemiology, biostatistics, machine learning, molecular biology, and healthcare systems.

Elective Courses

• Quantitative Biomedical Science
  • HSE 108 Applied Machine Learning
  • HSE 110 Integrative Biomedical Sciences Seminar (0.5 unit)
  • HSE 110.5 Integrative Biomedical Sciences Seminar Project (0.5 unit)
  • HSE 122 Foundations of Biostatistics III: Modeling Complex Data
  • HSE 123 Biostatistics Consulting Lab (0.5 unit)
  • HSE 124 Advanced Biomedical Data Analysis
  • HSE 126 Analysis of Densely Collected Longitudinal Data
  • HSE 139 Advanced Health Services Research
  • HSE 140 Decision & Cost-Effective Analysis
  • HSE 147 Genomics: From Data to Analysis
  • HSE 177 Methods of Statistical Learning for Big Data
  • HSE 180 Data Visualization (0.5 unit)
  • HSE 181 Data Wrangling
  • HSE 192 Health Informatics
  • HSE 193 Independent Journal Club (0.5 unit)
  • HSE 194 Biostatistics Journal Club
  • HSE 195 Independent Study
  • HSE 271 Advanced Epidemiology Journal Club (0.5 unit; not offered every year)
• Computer Science
  • COSC 189 Topics in Applied Computer Science
  • COSC 169 Topics in Computer Systems
  • COSC 269 Topics in Computer System
  • COSC 274 Machine Learning and Statistical Data Analysis
• Public Health Courses at Geisel
  • PH 122/HSE 129 Survey Methods
  • PH 111/HSE 127 Medical Care Epidemiology: Principles, Applications and Insights
  • PH 112 Medical Care & the Corporation
  • PH 115/HSE 144 Value and Resource Allocation
  • PH 151/HSE 145 Environmental Health Science and Policy (0.5 unit)
  • PH 117/HSE 142 Introduction to Quality Improvement in Health Systems (0.5 unit)
  • PH 125/HSE 135 Introduction to Qualitative Methods for Public Health & Healthcare Studies (0.5 unit)
  • PH 131/HSE 138 Patient Centered Health Communication (0.5 unit)
  • PH 154/HSE 141 Determinants in Health Inequities (0.5 unit)
• Thayer School of Engineering
  • ENGS 162 Basic Biological Circuit Engineering
  • ENGS 262 Advanced Biological Circuit Engineering

Limits and Requirements

• QBS 700 Responsible and Ethical Conduct of Research does not count toward the units of coursework required for the MS degree.
• Students who matriculate Fall 2021 and beyond may not take more than 4 units of coursework per quarter unless approved by QBS administration and leadership.
• No more than 3 journal clubs or 1.5 units of journal club courses may count towards elective credit.
• No more than 1 independent study may count towards elective credit.
• No more than 1 independent journal club may count towards elective credit.
• Seek administrative approval for non-listed electives.