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PhD Seminar in Health Policy: Using Secondary Data to Conduct Health Policy Research


East Baltimore
1st term
Health Policy and Management
1 credits
Academic Year:
2021 - 2022
Instruction Method:
Class Times:
  • Monday,  1:30 - 3:20pm
Auditors Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor:
Lauren Nicholas

300.721 -724 and successful passing of HPM PhD qualifying exam


Provides a small class-size, doctoral-focused experience and examines some of the most common data sources used in the field to study health policy and management research topics. Emphasizes secondary data sources and discusses: (1) data structure and challenges with conducting research with secondary data; (2) developing research questions and testable hypotheses using these data sources; (3) strategies for data cleaning, work flow management, and replication; (4) data protection and storage related concerns; and (5) orally communicating strengths and weaknesses of datasets in the context of research talks. Exposes doctoral students to faculty research projects and the specific datasets being used to conduct this research.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Explain data structure, methodological approaches and challenges associated with conducting research using some of the most common secondary datasets available for health policy and management research
  2. Critically evaluate the use of various data sources for studying contemporary health policy and management issues
Methods of Assessment:

Class participation (20%); Dataset presentation (80%)

Enrollment Restriction:

2nd year (or beyond) HPM PhD students only

Instructor Consent:

No consent required