Master's In-person

Master of Science in Biomedical Informatics

Concentrations

A health informatics degree that sets you apart

The University of Chicago excels at offering students customized curricula through specialized offerings. You can focus your degree in Biomedical Informatics into specific areas of interest through four concentrations, as well as through a variety of elective coursework that can help you further stand out in this exciting and burgeoning field. 

Choose the path that is right for you

Biomedical Informatics students can choose one of four concentrations. Bioinformatics allows you to dig into genomic and other biological data while working with DNA and RNA. With Clinical Informatics, you can use data across clinical systems that will provide the whole picture of a patient's health. Healthcare Delivery Science 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. 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.

NOTE: Selecting a concentration is not required to complete the master's in biomedical informatics program.

Bioinformatics concentration

Are you passionate about genomics? Focus your master’s degree on Bioinformatics

Bioinformatics is the application of computation and analytics tools to capture and interpret biological data. It allows us to better understand gene and protein functions, evolutionary relationships, and to predict protein structures. It works with DNA, RNA, and genes to provide a functional understanding of the human genome, resulting in enhanced discovery of drug targets and individualized therapy.

Learn tangible skills in machine learning, AI, and genomics

Our concentration in Bioinformatics prepares you for this interdisciplinary field where computer science, physics, mathematics, and biology come together to forge crucial medical discoveries. This focus is critical for modern biology and medical data management and will put you at the forefront of medical research.

Within the Bioinformatics concentration, students will study:

  • Molecular biology research tools and knowledge extraction engines
  • Utilities for DNA and RNA sequencing
  • Genomic data visualization
  • Concepts, techniques and algorithms used in machine learning

In addition to a capstone project centered on Bioinformatics, the following courses are required to complete the concentration: 

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

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

Clinical Informatics concentration

Improve decision support systems with a focus on Clinical Informatics

Clinical Informatics uses health information tools such as electronic health records, clinical decision systems, and health information exchange to support and improve patient care. You can help bridge the gaps in these systems and solve some of the biggest clinical data issues facing healthcare today with this concentration in our biomedical informatics program.

Create a clearer picture of patient’s health

Our specialized offering in Clinical Informatics will help you understand the expanding role of decision support systems in the genomic era. You will see how data derived across clinical systems can interoperate and provide a whole picture of patients’ health, leading to better outcomes for the patient and time savings for the providers. 

Within the Clinical Informatics concentration, students will learn to:

  • Apply health information technology tools such as electronic health records, clinical decision support, and health information exchange to support and improve care
  • Describe current uses of decision support systems in healthcare
  • Design, implement, and evaluate a decision support system to solve a real world health system problem
  • Understand the expanding role of decision support systems in the genomic era
  • Describe the ways in which data across clinical systems can interoperate and provide a whole picture of patients’ health
  • Discuss the use of health information technology standards to support interoperability

In addition to a capstone project that explores Clinical Informatics, students in the concentration must complete the following courses:

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.

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.

Healthcare Delivery Science concentration

Refine the patient experience—gain knowledge in Healthcare Delivery Systems

Healthcare Delivery Science focuses on how patients receive care, from scheduling appointments to researching the most successful and cost-effective ways to receive treatment. The goal is to improve the quality, outcomes, and cost of healthcare. This crucial field helps to improve healthcare by ensuring that systems are in place to provide the best, most effective services from start to finish. 

Help bring better healthcare to more people

Healthcare systems need improvement. They are strained, missing crucial pieces, and not well-connected. With a concentration in Healthcare Delivery Systems within our biomedical informatics graduate program, you will master the skills and knowledge to embed necessary healthcare delivery science into health systems to improve patient care on multiple levels. Bridge the gaps and advance the care experience.

Within the Healthcare Delivery Science concentration, students will learn:

  • The interconnectedness of systems and processes within healthcare delivery
  • How healthcare is delivered to the patient and how it can be improved
  • How costs can be reduced during the patient journey

To fulfill the concentration, students must complete a capstone project that explores Healthcare Delivery Science and complete the following courses:

Decision Support Systems and Health Care

MSBI 32300

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.

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.

Population Health concentration

Are you up for a challenge on a large scale? Translate data that will improve Population Health

Population Health Informatics delves into community-level health. Whether helping to prepare for threats of antibiotic-resistant infections and biological attacks or helping to better understand community health data to improve care and outcomes to underserved communities, this is a field that requires the knowledge and skills to use data to produce better outcomes for large populations. 

Serve your community and beyond

Use big data and advanced analytics techniques to engage in population health surveillance; manage chronic illness and infectious disease outbreaks; and establish prevention programs within neighborhoods and across cities, counties, and states. Accessing and analyzing public health data allows policymakers and local healthcare providers to make better decisions about resource allocation and more strategic approaches to public engagement. Focus your biomedical informatics degree at UChicago on Population Health Informatics and lead community health into the future.

Within the Population Health Informatics concentration, students will learn:

  • How to use data to identify the incidence and prevalence of diseases in populations to improve operational awareness in organizations
  • To assess data quality to determine if it is sufficient to answer necessary questions, maintain privacy, and meet legal requirements
  • How to tailor analytic results to assist in policy decisions, goal setting, and outcomes evaluations
  • To use population health data to understand and assess the environmental and community based factors that contribute to public health and disease prevention
  • To focus their studies and research on data systems and analysis specific to resource allocation, chronic and infectious disease prevention, and the increased use of evidence-based solutions to improve the quality of life for communities.

In addition to a capstone project that explores Population Health Informatics, students in the concentration will need to complete the following courses:

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

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.

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