Fundamentals of Medical Decision Making [ESP70]

Detailed information about this course:

Description

Faculty: Beate Jahn, PhD

This course will provide an introduction to health care decision making. Given uncertainty, trade-offs and values, how should patients, policymakers and clinicians decide among diagnostic and therapeutic choices to make optimal decisions? Medical interventions may have benefits but also adverse effects, e.g., undesirable complications or false or inconclusive results.

Clinical and health policy decisions necessitate weighing benefits and harms and trading off competing objectives (life expectancy, quality of life, costs). We will discuss a proactive approach involving decision analysis to integrate evidence and values for optimal and efficient care choices in the face of uncertainty.

Course content includes interpretation of clinical data and test results, testing and treatment thresholds, estimating prognosis, decision tree construction (e.g., Markov models and Monte Carlo simulations), life expectancy, quality of life assessment, cost-effectiveness analysis, health technology assessment, diagnostic reasoning, and shared decision making.

Teaching methods: Interactive lectures, breakout group discussions and exercises.

Objectives

The student is able to:

• Apply a systematic rational approach to decision making in health care
• Experience patient-centered clinical decisions based on evidence and preferences
• Recognize the role of uncertainty in testing and treatment decisions
• Assess, value and weigh benefits and harms in medical decision making
• Describe how to consider economic costs in health care policy decisions
  
  

Participant profile

Those in clinical care, health research, quality improvement, technology assessment, academia, health industry, or government who have interest in learning how to improve the process by which medical decisions are made in clinical practice for individuals and in health policy for populations, including clinical researchers, clinical epidemiologists, decision scientists, public health or public policy researchers or administrators, and those in health technology assessment or value-based healthcare.

Assessment

Attendance