Session Details

PM03: An Introduction to Research Prioritisation and Study Design Using Value of Information Analysi

(Event: SMDM 42nd Annual Meeting: Virtual Meeting)

Oct 13, 2020 1:00PM - Oct 13, 2020 4:00PM

Session Type: Short Course- PM 1/2 Day

Description

Background

VOI encompasses a suite of measures that quantify the value of reducing parametric uncertainty within a health economic model. VOI measures can determine whether the current evidence base for a health economic decision model is sufficient to make policy decisions. They can also direct future research by determining the model inputs with the greatest influence on decision uncertainty. In addition to this, VOI measures can determine the optimal design for a research study. Despite this versatility, VOI has rarely been used in practice for research prioritization and study design. This is due to a lack of familiarity, difficulties interpreting these measures, concerns about the assumptions underpinning them and computational complexity. The Collaborative Network for Value of Information (ConVOI) group is an international team of experts in developing and applying cutting edge VOI methods that aim to address these challenges.

Course Type

Half Day

Course Level

Beginner

Format Requirements

This course is a mixture of informal lectures and discussion sessions. The lectures will present the definition of key VOI measures, discuss the assumptions underpinning VOI analyses and demonstrate a number of graphical displays for VOI measures. Participants will discuss and interpret examples of VOI analysis from the literature. We will provide R code for all examples so that participants can continue to explore what they learn during the course. Participants should have some knowledge of health economic evaluation/decision-analytic modeling and Probabilistic Sensitivity Analysis (PSA).

Description & Objectives

The purpose of this course is to introduce VOI measures and their use in decision modelling. The course will introduce these measures, discuss their presentation and assumptions. By the end of the course, participants will be able to:

Interpret the Expected Value of Perfect Information (EVPI)
Interpret the Expected Value of Perfect Partial Information (EVPPI)
Interpret the Expected Value of Sample Information (EVSI)
Interpret the Expected Net Benefit of Sampling (ENBS)
Discuss key assumptions that impact a VOI analysis
Explore the results of a VOI analysis using graphical displays
Critically evaluate the assumptions underpinning VOI analyses
Understand how VOI analysis can be used to determine research priorities and design clinical

Course Director

Jeremy D. Goldhaber-Fiebert, PhD
- Centers for Health Policy and Primary Care and Outcomes Research, Center for Health Policy and Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA
- Anna Heath, PhD
- University of Toronto, Toronto, ON, Canada

Course Faculty

Fernando Alarid-Escudero, PhD
- Health Policy and Management, Division of Public Administration, Center for Research and Teaching in Economics (CIDE), Aguascalientes, AG, Mexico
Hawre Jalal, MD, PhD
- University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA
- Natalia Kunst, MSc
- Yale University School of Medicine, New Haven, CT

Session Fees

	Fee Type	Member Fee	Non-Member Fee
This session is free
	Early:	$40.00	$40.00
	Regular:	$40.00	$40.00
	Late:	$40.00	$40.00
This session is free
	Early:	$20.00	$20.00
	Regular:	$20.00	$20.00
	Late:	$20.00	$20.00