Health Economics and Outcomes Research (HEOR) Training Modules for Your Team
Targeting busy professionals at all experience levels
Empower your team to:
- Engage colleagues in HEOR discussions
- Interpret HEOR studies
- Communicate HEOR data more effectively
- Understand how analyses are used by decision makers
- Become better navigator of pharmacoeconomic literature
Select tailored modules that benefit your team
Pharmacoeconomic principles
- Define pharmacoeconomic research and how it’s used
- Identify ways a medication can be considered “cost-effective”
- Distinguish among types of costs (direct medical, direct non-medical, indirect, intangible)
- Describe types of outcomes (e.g., surrogate vs final, economic, clinical, patient reported) and how they are incorporated into cost-effectiveness analyses
- Recognize how to interpret a cost-effectiveness plane
- Describe various study perspectives
- Identify the importance of sensitivity analysis.
Pharmacoeconomic methodology
- Identify differences among various pharmacoeconomic methodologies, such as cost of-illness analysis, cost-minimization analysis, cost-effectiveness analysis, cost-utility analysis, and cost-benefit analysis
- Calculate the incremental cost-effectiveness for one medication over another
- Describe how utility values are used to calculate a quality-adjusted life year difference between average cost-effectiveness ratios and incremental cost-effectiveness ratios
- Describe the advantages of using cost-effectiveness acceptability curves .
Patient-Reported Outcomes (PRO) assessment
- Define patient-reported outcomes (PROs) and when they should be used
- Identify types of instruments used to measure PROs, including generic and disease-specific tools
- Describe examples of commonly used PRO instruments, including the SF-36 Health Survey and the EQ-5D
- Discuss the importance of measuring what is important to the patient
- Outline recommendations in the PRO Guidance
- Explain how a PRO instrument can be considered valid and reliable
Real World Evidence (RWE). Overview of methods
- Clarify definitions and policy issues, and why RWE has received so much attention from various stakeholders
- Describe different types of RWE studies including associated advantages and disadvantages
- Differentiate observational study designs including cohort, case control, and pragmatic trials
- Discuss statistical techniques used in observational research such as propensity score matching
- Compare and contrast various tools available for evaluating observational studies
Health Economics Modelling. Basics and Advanced
- Describe the steps in building a decision tree
- Build a decision tree using Excel software
- Differentiate between decision trees and Markov models
- Identify disease conditions where a Markov analysis is preferred to a decision tree
- Build a Markov model using Excel software
- Interpret Markov structures and results presented in publications
- Fully probabilistic Markov/Monte Carlo models (Bayesian statistics – based)
- DES models (Discrete Event Simulation)
Budget Impact Analysis (BIA)
- Define components included in budget impact analyses
- Discuss ISPOR Principles of Good Practice for Budget Impact Analysis
- Describe examples of published budget impact analyses
- Identify key questions that are raised about budget impact analyses
- Outline differences between budget impact and pharmacoeconomic analyses
- Discuss ways to best communicate budget impact models with end users
With flexible solutions
Person to person modules
Person to group modules
Classical online modules
Interactive online modules (webinar)
