Health Sciences, B.S. to Health Data Science, M.S. Accelerated Program
Saint Louis University’s accelerated Bachelor of Science in Health Sciences to Master of Science in Health Data Science (M.S.) pathway is designed for students interested in using data to improve health outcomes and advance decision-making in health care.
The health sciences curriculum provides a flexible and customizable foundation that allows you to explore your interests while building core knowledge in health systems, population health, and the factors that influence patient care. Through a combination of required coursework and electives, you can develop skills in data analysis, interpretation, and application within a health care context.
This accelerated pathway gives you the opportunity to begin graduate-level coursework in health data science during your senior year, helping you save time and reduce the overall cost of earning your graduate degree. You will gain experience working with health data, understanding data-driven decision-making, and applying analytical tools to real-world health challenges.
Graduates of this pathway are prepared for roles in health care systems, public health organizations, research institutions, and health technology companies. Career opportunities include health data analyst, clinical data specialist, population health analyst, and roles in quality improvement and health informatics. The program also provides a strong foundation for continued growth in data-driven and analytical careers within the health sector.
Students apply to the accelerated program during their junior year. If accepted, you will begin taking graduate-level courses in your senior year while maintaining undergraduate status, financial aid, and tuition rates. After completing your bachelor’s degree, you will transition to full graduate status, pay graduate tuition, and become eligible for graduate assistantship opportunities.
For additional information, see the catalog entries for the following programs:
Admission Requirements
Eligibility requirements for SLU's health sciences B.S., health information management concentration to health data science, M.S. accelerated program include:
- Students must have a minimum cumulative GPA of 3.00
- Students must be in good academic and disciplinary standing with Saint Louis University and the Doisy College of Health Sciences.
- Students can declare their interest to the accelerated program to their advisor up until the sixth semester.
- No earlier than the sixth semester of collegiate study, students in the accelerated health information management concentration to M.S. health data science track submit a letter of interest to the Health Information Management Program.
Program Requirements
- In the eighth semester, students will apply to the M.S. in health data science program.
- Students will substitute designated graduate health data science courses for undergraduate health information management courses in the seventh and eighth semesters. Students can count up to 15 credits from the M.S. towards the B.S. requirements, but due to the nature of both programs, most students end up counting 9 credits from the M.S. towards the B.S.
- Accepted students will continue M.S. in health data science graduate coursework in the summer semester after graduating with a B.S in health sciences, health information management concentration.
This roadmap is just one example of a semester-by-semester plan of study for this program. There are other plans students can and do take. The plan of study for each particular student is established in consultation with each student’s academic advisor; this roadmap does not replace academic advising appointments.
Roadmap notes:
- This Roadmap assumes full-time enrollment unless otherwise noted.
- Courses/Milestones marked with an “!” are critical and must be completed in the semester listed in the Roadmap to ensure a timely graduation.
- Course availability and sequencing are subject to change.
| Year One | ||
|---|---|---|
| Fall | Credits | |
| CORE 1000 | Ignite First Year Seminar | 2 |
| MATH 1200 | College Algebra | 3 |
| HSCI 1000 | Introduction to Health Sciences | 1 |
| BIOL 1240 & BIOL 1245 |
General Biology: Information Flow and Evolution and Principles of Biology I Laboratory (satisfies CORE 3800) |
4 |
| University Elective | 3 | |
| Credits | 13 | |
| Spring | ||
| CORE 1600 | Ultimate Questions: Theology | 3 |
| BIOL 1260 & BIOL 1265 |
General Biology: Transformations of Energy and Matter or Principles of Chemistry 1 Lecture and Principles of Chemistry 1 Lab |
4 |
| STAT 1300 | Elementary Statistics with Computers | 3 |
| CORE 1900 | Eloquentia Perfecta 1: Written and Visual Communication | 3 |
| University Elective | 3 | |
| Credits | 16 | |
| Year Two | ||
| Fall | ||
| HSCI 2000 | The US Health Care System | 3 |
| HSCI 2200 | Medical Terminology | 3 |
| HIM 3000 | Introduction to Health Information Concepts and Practice | 3 |
| CORE 1200 | Eloquentia Perfecta 2: Oral and Visual Communication | 3 |
| CORE 1700 | Ultimate Questions: Philosophy | 3 |
| Credits | 15 | |
| Spring | ||
| HSCI 2100 | Health Care Management | 3 |
| HSCI 2400 | Professional Development Seminar | 1 |
| CORE 2800 | Eloquentia Perfecta 3: Creative Expression | 2-3 |
| HSCI Elective | Health Sciences Major Elective | 3 |
| University Elective | 3 | |
| Credits | 12-13 | |
| Year Three | ||
| Fall | ||
| HSCI 3200 | Aspects of Health Law | 3 |
| HSCI 3700 | Research Methods | 3 |
| HSCI Elective | Health Sciences Major Elective | 3 |
| CORE 3600 | Ways of Thinking: Social and Behavioral Sciences | 3 |
| University Elective | 3 | |
| Credits | 15 | |
| Spring | ||
| HSCI 3910 | Internship | 1-3 |
| HSCI Elective | Health Sciences Major Electives | 6 |
| CORE 3400 | Ways of Thinking: Aesthetics, History, and Culture | 3 |
| CORE 3500 | Cura Personalis 3: Self in the World | 1 |
| University Elective | 3 | |
| Credits | 14-16 | |
| Year Four | ||
| Fall | ||
| HSCI 4100 | Healthcare Technology and Informatics | 3 |
| HSCI Elective | Health Sciences Major Elective | 3 |
| CORE | Equity and Global Identities: Identities in Context | 3 |
| HDS 5000 | Foundations in Health Data Science | 3 |
| ORES 5300 | Foundations of Health Outcomes Research | 3 |
| Credits | 15 | |
| Spring | ||
| HSCI 4500 | Hot Topics in Health Care | 3 |
| HSCI Elective | Health Sciences Major Elective | 3 |
| HDS 5130 | Healthcare Organization, Management, and Policy | 3 |
| ORES 5160 | Data Management and Programming in Healthcare | 3 |
| University Elective | 3 | |
| Credits | 15 | |
| Year Five | ||
| Fall | ||
| HDS 5310 | Analytics, Statistics & Visualization Methods in Health Data Science | 3 |
| HDS 5330 | Predictive Modeling and Health Machine Learning | 3 |
| Credits | 6 | |
| Spring | ||
| HDS 5430 | Image Processing and Deep Learning Diagnostics | 3 |
| HDS 5230 | High-Performance Computing and Health Artificial Intelligence | 3 |
| Credits | 6 | |
| Year Six | ||
| Fall | ||
| HDS 5530 | Natural Language Processing in Medicine | 3 |
| HDS 5960 | Capstone Experience | 3 |
| Credits | 6 | |
| Total Credits | 133-136 | |
Contact Doisy College of Health Sciences
Recruitment specialist
314-977-2570
dchs@health.slu.edu