This course introduces quantitative methods and their applications to health care decision-making. The use of these methods has recently become an active and growing area of practice and research in contexts including wait list management, patient flow, population demand estimates, health human resource management, and the coordination of resources for elective and emergency services. This course is designed to provide health care decision makers with an introduction to several useful quantitative methods that can provide insight and support for complex decisions. We will cover the following topics: mathematical model formulation; linear programming and optimization; forecasting; queuing theory and simulation modeling; project management; introduction to decision analysis.

This class is not intended for learners who have a background in operations research.

Learner objectives: upon completion of this course, students will be able to: 1) Reconstruct management problems into mathematical models for optimization. 2) Graphically describe the mathematical models to understand the relationship of decision alternatives. 3) Develop Excel spreadsheets to solve mathematical optimization problems. 4) Appraise and justify the value of resource allocation decisions using sensitivity analysis. 5) Interpret retrospective data to predict future states. 6) Develop models using simulation and queuing theory that predict wait times, service demands, and resource utilization. 7) Manage project deadlines using quantitative tools. 8) Display confidence in using quantitative methods to make health care decisions and hold people accountable for making high quality recommendations. 9) Be willing to face quantitative facts even when they are counter-intuitive.

Learner competencies: accountability; achievement orientation; analytical thinking; initiative; innovative thinking; performance measurement; project management; self-confidence.