Master's In-person

Master of Science in Biomedical Informatics

Curriculum

Data done right. Health informatics at UChicago

We designed UChicago’s bioinformatics degree program to propel you into this exciting and innovative career. Built for busy adults, our flexible in-person program can take as little as one year full-time or five years part-time. Our evening and weekend classes—taught by expert instructors, each a practicing professional in the field—boast small classes for maximal personal support and an easily accessible location in downtown Chicago.

Bioinformatics students learn and master:

  • Managing informatics projects
  • Communicating with diverse professional audiences
  • Using informatics methodologies in a range of biomedical settings
  • Navigating the ethical, privacy, and data security considerations at play in the field

Program format

  • Students can typically expect core course class sizes to range between twenty to twenty-five, with elective classes ranging from ten to fifteen
  • Each class meets once per week for three hours, and students complete each course in ten weeks
  • Courses are offered on weeknights and Saturday mornings to accommodate working professionals
Program Format Estimated Time to Completion Able to work Full-time?
Full-time 1 year Yes
Part-Time 2-5 years Yes

Biomedical Informatics curriculum

The master's in bioinformatics program requires the successful completion of 12 courses.

To earn their degree, students must complete:

All MScBMI students are expected to have introductory-level competency in the following areas:

  • Statistics: this can be fulfilled by a course such as Introduction to Statistics or Biostatistics
  • Health Sciences of Clinical Care: this can be fulfilled by a survey or overview course in health sciences or a clinical degree.

In your application, please indicate in your personal statement which courses in your transcript fulfill this program requirement or how you plan to fulfill these requirements. The MScBMI program does offer convenient bootcamps for all incoming students to help satisfy these prerequisites.

Biostatistics proficiency assessment

The Biostatistics Proficiency is designed to assess students’ proficiency with basic statistical concepts such as descriptive statistics, random variables and probability, statistics inference, chi square, analysis of variance, correlation, and linear regression. Results of the assessment will determine whether students should enroll into the pre-quarter, 3-week biostatistics bootcamp.

Data analysis proficiency assessment

The Data Analysis Proficiency is designed to gauge students’ current knowledge of statistics and data analysis. Concepts covered by this assessment include descriptive statistics, statistics inference, types of variables, probability, analysis of variance, correlation and linear regression, basic programming concepts in R as required for analyzing and reporting data. Results of the assessment will guide students’ enrollment into an introductory level or intermediate level data analysis course.

Core courses

Core courses in the master in bioinformatics program expose students to the practical applications and theoretical elements that impact health informatics. Our graduates learn key skills for understanding, designing, and managing health information technology systems and projects, all of which will prepare them to excel in this field. Course offerings may change within an academic year. Students must choose five of the following core courses:

Introduction to Biomedical Informatics

MSBI 31100

This course will cover the fundamentals of informatics as it applies to health care and research. Specific topics will include: radiology, imaging, and nursing informatics; using clinical data for research; overview of bioinformatics; coding in clinical care and billing; terminologies and ontology mapping; security and privacy including HIPAA and HITECH; mobile health and telemedicine; human-computer interaction; decision support; meaningful use; quality reporting; the Affordable Care Act; and clinical laboratory informatics.

Leadership and Management for Informaticians

MSBI 31200

This course will introduce students to key concepts in project management and team building for biomedical informatics projects. Specific topics will include: defining project scope, goals, and metrics; managerial supervision; team motivation; team communication and conflict resolution; and communication during and after projects to maximize success and impact.

Concepts in Computer Programming

MSBI 31300

This course will provide an introductory and intermediate level overview of computer science and programming for students who are not working in technology-based professions. Students will learn concepts in computer programming and how programming language works, as well as theories behind information system design and management. Specific topics include: Python programming language; fundamental data structure; algorithm design; basic project management of development projects.

Ethics and Policy Questions: Genomics, Health Care, and Big Data

MSBI 31500

This course will provide students with an understanding of critical ethical, legal and social issues related to biomedical informatics, with an emphasis on policies in the US. Specific topics include: balancing privacy and discovery in the context of big data analysis; data stewardship; human genomic data; implications of future innovation for privacy and ethics; and guarding against misuse of data.

Introduction to Applied Data Analysis

MSBI 31800

This course will introduce students to the concepts of research design, working with healthcare data, managing secondary data sets, and basic data analysis including descriptive statistics and measures of association. The course will outline methods for identifying appropriate datasets and using tools to analyze data, evaluate hypotheses, and interpret results. The goal is to help students learn how to describe, present, summarize, and organize data effectively in the area of biomedicine.

Customize your degree with elective courses

The University of Chicago excels at offering students customized curricula through specialized offerings. You can personalize your degree with a wide range of electives that prepares students with the critical skills, practical knowledge, and confidence to understand, build, and improve informatics solutions that can help address the most significant challenges in healthcare today. Students must choose four of the following elective courses:

Intermediate Applied Data Analysis

MSBI 32000

This course will enable students to focus on applying informatics methods to real-world scenarios. The course will be customized for students wanting to pursue research or clinical informatics projects. In the research group, we will use a case-study based approach to identify appropriate datasets, use analytic tools to analyze data, evaluating hypotheses, and interpret results. In the clinical group, we will focus on the methods of diagnosing issues within current or proposed clinical systems, using informatics to address issues, and evaluate the results.

Prerequisites

MSBI 31300: Concepts in Computer Programming with a grade of B or higher

HIT Integration, Interoperability Standards

MSBI 32100

This course will provide students with an understanding of healthcare information technology (HIT) standards and interoperability. Lessons will include: a review of key standards such as IHE initiative, HL7, DICOM, CCOW, and others; the role of non-medical standards (HTTP, XML, etc.) in biomedical informatics; policy issues related to data exchange between institutions; use of service oriented architecture (SOA); enterprise business integration; and HIPAA polices and standards.

Decision Support Systems and Health Care

MSBI 32300 | In-person

This course will give students an overview of computer-assisted management information and decision systems used in health organizations. Topics will include: the analysis and design of databases for decision-making; data and information flow and reporting; security, privacy and confidentiality in using decision support systems; and best practices for change management in decision support systems.

Introduction to Bioinformatics

MSBI 32400

This course will provide students with an introduction to the tools and applications of bioinformatics. Examples will focus on genetic and genomic technologies including basic Illumina molecular biology; utilities for DNA sequencing; and knowledge extraction engines.

Prerequisites

MSBI 31300: Concepts in Computer Programming

Advanced Bioinformatics: Genome Analysis

MSBI 32500 | In-person

This course will follow on from the Introduction to Bioinformatics and will include advanced topics such as: Linux and high performance computing; genomic data visualization; R programming in bioinformatics; and RNA sequencing data analysis.

Prerequisites 

MSBI 32400: Introduction to Bioinformatics

Geographic Information Systems and Health Information

MSBI 32600

Increasingly, health care professionals are integrating data and data analysis techniques into the formulation of strategies, approaches, and frameworks for addressing complex health issues. Among the various data analysis tools being used in the health care and public policy fields Geographic Information Systems (GIS) are unique in their ability to tie health data to a geographic location. This makes a GIS much more than mapping software; by providing users with a suite of tools for manipulating, analyzing, and visualizing data in a spatial way a GIS can reveal relationships, trends and patterns that would not be apparent in other data analysis applications. GIS analysis methods can be used across disciplines to answer the kinds of complex multi-dimensional questions frequently found in the health care field.

In this class, students will learn about fundamental GIS concepts while building the basic skills necessary to integrate a GIS into a decision making process. Concepts presented in lecture will be put into practice through hands-on laboratory exercises utilizing QGIS, a cross-platform free and open-source desktop geographic information system. Additionally, the course will incorporate cases studies into laboratory exercises to ground GIS analysis techniques in real world learning scenarios.

Advanced Concepts in Computer Programming

MSBI 31600 | In-person

This course will introduce students to advanced concepts in computer programming through real-world "end-to-end" case studies. Additionally, this course will provide a comprehensive introduction to the domain of biomedical informatics from a computer programming perspective and will also provide implementation examples that are representative of problems that practitioners in the medical field have to solve. During the course, students will learn how biomedical informaticists access and process healthcare and medical data. Topics will include: common IT methods and tools, important numerical algorithms, commercial products as well as open-source tools and libraries.

Prerequisites

MSBI 31300: Concepts in Computer Programming with a grade of B+ or higher

Population Health Informatics

MSBI 33100 | In-person

As health and healthcare digitizes, the potential to better monitor, target and respond to the needs of populations increases. However, the exponential growth in health information technologies, and associated consumer products, has created an informatics skills gap for even veteran population health professionals. This course provides both a hands-on introduction and conceptual foundation for public health informatics. Students will work with open source surveillance data sets, apply standard terminologies and vocabularies, while furthering their understanding of the intersection of public health practice and informatics. This course will prove valuable for any student tasked with evaluating new data sets for monitoring the health of populations.

Prerequisites

MSBI 31300: Concepts in Computer Programming and MSBI 31800: Introduction to Applied Data Analysis, or MSBI 32000: Intermediate Applied Data Analysis

Machine Learning for Biomedical Informatics

MSBI 33200 | In-person

This introductory course will present an overview of the basics concepts, techniques and algorithms used in Machine Learning. By taking this course students will be introduced to the basic ideas and intuition behind modern Machine Learning techniques. Students taking this course should be able to program in Python in order to complete the assignments required. Due to the mathematical nature of Machine Learning, this course will assume a reasonable level of mathematical maturity.

Prerequisites

MSBI 32000: Intermediate Applied Data Analysis

Topics in Healthcare Delivery Science

MSBI 33400

This course will provide an introductory view of the breadth of healthcare delivery science covering a wide array of topics. The course sessions will delve into the fields and disciplines that comprise HDS including but not limited to: approaches (e.g., quality improvement, implementation science), techniques (e.g., human factors and human-centered design), data and analytics (e.g., program evaluation, machine learning), program design and implementation (e.g., stakeholder engagement, prototype development), and needs and risk assessments, among other topics. Students will have an opportunity to practice many of the skills being demonstrated and taught by the course lecturers and will work on a project of their own throughout the course.

Solve Real-World Problems in Healthcare

Capstone Project

Get hands-on industry experience tailored to your area of focus with the Capstone Project, an applied research project that pairs you with an industry, university, or research partner to develop an actionable biomedical informatics solution for their organization. This experience will push you into discovery, challenge you with problem-based work, and have an immediate and positive impact on your career. 

Students can register and complete the Capstone program throughout the last three-quarters of the master's program.

Capstone Proposal

MSBI 39901

This course will guide students through the writing of their capstone project proposal.

Capstone Implementation

MSBI 39902

In this course, students will begin work on their capstone projects.

Capstone Writing and Presentation

MSBI 39903

Students will work on writing and prepare for the presentation of their capstone projects.

You have options. Pick your concentration in Biomedical Informatics at UChicago

One of the key advantages of UChicago's program is that we offer customized curricula so you can experience a more diverse education and explore which areas of biomedical informatics you would like to focus on. You can choose from a variety of elective courses as well as one of our four concentrations—all of which can help you stand out in this exciting and burgeoning field.

Students can select one of the following concentrations:

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Bioinformatics allows you to dig into genomic and other biological data while working with DNA and RNA.

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With Clinical Informatics, you can use data across clinical systems that will provide the whole picture of a patient's health.

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Health Delivery Sciences allows you to explore the interconnectedness of systems and processes involved in real-world operations and research techniques critical to improving how people receive healthcare.

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The Population Health Informatics concentration will help you unlock solutions in clinical data that can transform healthcare for large populations and solve problems on a wide scale.

Laptop requirements

All students must have a laptop with an updated operating system (OS). Students may need laptops with more memory and/or storage based on the courses taken. Most of our instructors use a Windows OS and may not be able to help troubleshoot software issues on other OS machines.

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