Curriculum

Master and Measure

The MS in Population Health Sciences provides a thorough foundation in population health and health analytics while focusing on specific methods, topic areas, and professional development classes to help reach the student’s career goals. Courses are much more than lectures, featuring team-based case studies, collaborative research projects, and hands-on experience with analytics software and study design. Students are taught by department’s faculty, who are world-renowned researchers in implementation science, health economics, and patient-centered outcomes. In their first year, students take classes in population health, statistical methods and programming, research methods, and professional development. The program’s second year mixes electives and experiential learning.

Full course descriptions for the 2019-2020 academic year are available here.


“Dr. Emily O'Brien consistently provided insightful real-world examples to clarify statistical concepts. She's an excellent instructor.”

- 2019 Matriculant


Curriculum

  • Four courses in applied analytic methods
    • Two core courses with labs
    • Two analytics electives)
  • Two foundational courses in population health sciences 
  • Two courses in population health sciences research methods and study design
  • Two professional development seminars 
  • Two electives 
  • A capstone project
    • Two-semester internship
    • Master’s Paper or Thesis
  • A course in academic integrity and responsible conduct of research

Course Schedule

Year 1 Fall (11 credits) Spring (11 credits)
  PHS 701: Applied Analytic Methods I (3 credits) PHS 702: Applied Analytic Methods II (3 credits)
  PHS 703: Statistical Programming for Population Health Sciences I (1 credit) PHS 704: Statistical Programming for Population Health Sciences II (1 credit)
  PHS 705: Topics in Population Health Sciences I (3 credits) PHS 706: Topics in Population Health Sciences II (3 credits)
  PHS 707: Research Methods & Study Design I (3 credits) PHS 708: Research Methods & Study Design II (3 credits)
  PHS 709: Professional Development I (1 credit) PHS 710: Professional Development II (1 credit)
Year 2 Fall (9 credits) Spring (9 credits)
  Analytic Elective I (3 credits) Analytic Elective II (3 credits)
  General Elective 1 (3 credits) General Elective II (3 credits)
  Capstone Project (3 credits) Capstone Project (3 credits)

Hands On, Real World

To go from theory to practice, in their second year Population Health Science master’s students complete a capstone project tailored to their career aspirations. For those interested in careers outside of research, the capstone involves a year-long internship in Duke Health or entities outside the university such as government or community agencies, payers or the many biomedical companies around the Research Triangle. The internship concludes with a master’s paper based on the experience.

For those interested in a population health sciences doctoral program at Duke or elsewhere or plan a research career, the capstone project involve faculty-mentored individual research including primary data collection and analysis. Students who choose this track complete a thesis or publishable research paper.


In Class with Professor Matt Maciejewski, PhD

​​​​​​​About Dr. Maciejewski

Education: PhD, Health Services Research, University of Minnesota, Twin Cities
Research Focus: Evaluation of surgical and behavioral interventions for management of obesity or cardiometabolic conditions; management and outcomes of complex patients
Teaching: PHS 702 Applied Analytic Methods for Population Health Sciences II 

I want to give my students an understanding of the conditions in which to apply different regression methods and the assumptions underlying different methods. There is rarely just one way to conduct an analysis, so I am also trying to equip students with the ability to think of alternative approaches to operationalizing a research question. We do this with examples from actual data to bring these methods to life.

In their eventual careers, I hope that our students can contribute to their organization in a substantive way—to think creatively and go beyond basic statistical formulas. For students pursuing careers directly after the master’s degree, I would hope that they can have successful careers as analysts working on multidisciplinary teams under the guidance of a PhD methodologist. They should be able to work collaboratively, identify the advantages and disadvantages of alternative analytical approaches, then operationalize a given research question in an empirical analysis. And for students who anticipate studying for their PhD, this course will expose them to a broad range of research methods, so they have the fundamentals to go deeper into specific methodologies as they further their education.