HAD5736H

Operations Research: Tools for Quantitative Health Care Decision Making

Prerequisite

see below Learners will be expected to have some background in probability and statistics. All learners are expected to bring laptops to class and have a working knowledge of Microsoft Excel including building equations in Excel.

Description

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:

  • Reconstruct management problems into mathematical models for optimization
  • Graphically describe the mathematical models to understand the relationship of decision alternatives
  • Develop Excel spreadsheets to solve mathematical optimization problems
  • Appraise and justify the value of resource allocation decisions using sensitivity analysis
  • Interpret retrospective data to predict future states
  • Develop models using simulation and queuing theory that predict wait times, service demands and resource utilization
  • Manage project deadlines using quantitative tools
  • Display confidence in using quantitative methods to make health care decisions and hold people accountable for making high quality recommendations
  • 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

Instructors

Dionne M. Aleman

Michael (Mike) Carter

Evaluation

25%
30%
20%
20%
5%

HAD5736H

Operations Research: Tools for Quantitative Health Care Decision Making

Modular

Location(s): TBD

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