Master's Programs
Date July 7, 2026
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Biostatistics vs. health informatics and AI at Brown University: Finding your path in health data

Data is transforming health care — and the right skills can put you at the forefront. At Brown University, master’s programs in biostatistics and health informatics and AI open different doors: one teaches you to uncover insights hidden in data to inform research, clinical practice and public health decisions, while the other teaches you to put data into action to improve patient care. Which path will you take?

An illustration of four diverse medical professionals interacting with interconnected, floating digital screens.

In today’s health care world, data is more than numbers. It’s a tool that drives decisions, shapes policies and improves patient outcomes. At Brown University, two paths in master’s programs explore health data from different angles: biostatistics and health informatics and AI. While both prepare students for careers that make a real-world impact, they approach the field in distinct ways.

Think of it like this: biostatistics uncovers the story hidden in the numbers by designing studies and analyzing data to answer questions in medicine, public health and health policies, while health informatics and AI puts that story into action in real-world health care systems.

Biostatistics: Turning numbers into insight

Brown’s biostatistics programs are designed for students who want to build expertise in statistical analysis and data interpretation. Offered in both on-campus and online formats, the programs focus on identifying patterns in medical and public health data, applying statistical and machine learning methods and working with real-world datasets. 

Through a thesis (residential) or capstone project (online), students develop programming, data science and collaborative skills while learning to work alongside clinicians, researchers and public health professionals to support evidence-based decision-making.

What can you do with a master’s in biostatistics? 
  • Graduates are prepared for high-impact careers as biostatisticians, data analysts and research scientists in clinical, academic and government settings.

Learn more about Brown’s on-campus Biostatistics program | Explore the online Biostatistics option

Health informatics and AI: Applying data to improve health care

Health informatics and AI focuses on how data moves through health care systems and how it can be applied to improve patient care. Brown’s program blends data science, artificial intelligence and leadership skills, teaching students to understand data within electronic health records, optimize clinical workflows and implement systems that enhance health care delivery. 

What can you do with a master’s in health informatics and AI? 
  • Graduates are equipped to work as health informaticians, health IT specialists or health care consultants—roles that bridge technology, data and patient care.

Learn more about Brown's Health Informatics and AI

Why Brown?

Choosing Brown means joining a university known for interdisciplinary learning, innovation and collaboration. Students benefit from top-tier faculty, hands-on experience and a community that supports real-world problem-solving. The programs are designed not only to teach technical skills but also to provide opportunities to apply them in meaningful ways, whether through research, capstone projects or system improvements. The online Biostatistics program also offers flexibility for working professionals who want to advance their expertise without relocating, allowing them to balance graduate study with career, family and personal commitments

What is the difference between biostatistics and health informatics and AI?

While both fields are data-driven, the key difference is in their approach and application:

  • Biostatistics is ideal for those who want to take a quantitative approach, using statistical methods to analyze complex data to inform medical research and public health decisions.
  • Health Informatics and AI is best for students who want to apply data and technology directly to improve health care operations, systems and patient outcomes.