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Course catalog

Healthcare Management · Proposed course

Specialized Elective

Course code
MHM 609
Credit hours
3
Program
MHM
Delivery
Hybrid/Online

Course description

Course overview

This elective course allows students to specialize in an area of professional interest within the healthcare management field. Students may select from three focus areas: Predictive Analytics, Health Economics, or Global Health Policy. Each track emphasizes applied learning and integration of STEM-based analytical methods, management practices, and policy frameworks relevant to modern healthcare challenges.

Course content is presented for institutional review and remains subject to approval and revision.

Academic focus

Course objectives

  1. 01

    Develop specialized knowledge in a selected area of healthcare management.

  2. 02

    Apply analytical and strategic tools to address complex healthcare problems within the chosen concentration.

  3. 03

    Integrate quantitative analysis and evidence-based reasoning into decision-making processes.

  4. 04

    Demonstrate professional communication and research presentation skills.

Learning outcomes

Upon completion

  1. CLO 1

    Demonstrate advanced understanding of the selected concentration topic (maps to PLO 1, PLO 2).

  2. CLO 2

    Apply data analytics and modeling techniques to healthcare challenges (maps to PLO 2, PLO 3).

  3. CLO 3

    Evaluate policy, economic, or predictive implications in healthcare systems (maps to PLO 1, PLO 4).

  4. CLO 4

    Present analytical findings and recommendations using professional communication skills (maps to PLO 7).

Proposed syllabus

Weekly course schedule

The sequence below reflects the current 15-week syllabus and remains subject to institutional review.

  1. Week 1

    Overview of Elective Concentrations and Learning Outcomes

  2. Week 2

    Topic Selection and Research Proposal Development

  3. Week 3

    Literature Review and Problem Definition

  4. Week 4

    Data Collection and Analysis Methods

  5. Week 5

    Predictive Analytics: Modeling and Forecasting Techniques

  6. Week 6

    Health Economics: Cost-Benefit and Cost-Effectiveness Analysis

  7. Week 7

    Global Health Policy: Comparative Frameworks and Governance

  8. Week 8

    Midterm Project Progress Review

  9. Week 9

    Ethics and Equity in Data and Policy Decision-Making

  10. Week 10

    Applied Case Studies in the Chosen Concentration

  11. Week 11

    Quantitative Analysis and Interpretation

  12. Week 12

    Preparing Reports and Visualizations

  13. Week 13

    Project Draft Presentation

  14. Week 14

    Final Project Presentations

  15. Week 15

    Final Exam and Reflection

Evaluation

Assessment and grading

  • Research Proposal – 15%
  • Midterm Progress Report – 20%
  • Final Project – 30%
  • Case Study Presentation – 20%
  • Participation and Discussion – 15%
A = 90–100%B = 80–89%C = 70–79%F = Below 70%

Course resources

Required texts and materials

  • Textbooks and readings will vary by elective focus area:
  • Predictive Analytics:
  • Kuhn, M., & Johnson, K. (2020). Applied predictive modeling (2nd ed.). Springer.
  • Health Economics:
  • Bhattacharya, J., Hyde, T., & Tu, P. (2014). Health economics. Palgrave Macmillan.
  • Global Health Policy:
  • Merson, M. H., & Black, R. E. (2022). Global health: Diseases, programs, systems, and policies (5th ed.). Jones & Bartlett Learning.
  • Additional readings and data sets will be available via the course LMS.