Session Details

PM03: Optimal Research Design Using Value of Information

(Event: SMDM 41st Annual Meeting: Portland, OR)

Oct 20, 2019 2:00PM - Oct 20, 2019 5:30PM

Session Type: Short Course- PM 1/2 Day

Description

Background

EVSI has long been touted as a method for research prioritisation and study design. Based on a health economic decision model, EVSI computes the monetary value of performing research. This value can be compared with the cost of conducting the research to determine whether there it has a potential positive net benefit. Despite these advantages, the computational complexity of this type of analysis has hindered its implementation in practice. Recently, methods have been developed to reduce this computational burden and allow for the estimation of EVSI in practice. The Collaborative Network for Value of Information (ConVOI) group is a team of researchers, including the developers of four recent EVSI estimation methods, that aims to improve the visibility and implementation of EVSI in research prioritization and study design.

Course Type

Half Day

CourseLevel

Advanced

Format Requirements

This course is a mixture of lectures and practicals in which participants will work through R code on their own computers. The lectures will present EVSI as a tool to design clinical research and the recently developed computation methods. The practicals will then focus on implementing these methods using prepared R code and the R package EVSI. Participants require experience using R and knowledge of probabilistic health economic modelling and prior exposure to the basic concepts of Value of Information analysis. Some knowledge of Bayesian statistical methods is helpful but not required.

Overview

This course presents the Expected Value of Sample Information (EVSI), a decision-theoretic measure of the monetary value of collecting additional information through potential future research. Participants will be introduced to EVSI and how it can be used to design research studies. The course will also give a demonstration of how to efficiently compute EVSI in practice with accompanying code provided in R.

Description & Objectives

The purpose of this course is to introduce EVSI as a tool for research prioritisation and study design. The course will introduce several recent methods for the calculation of EVSI alongside R code to calculate and present these measures. By the end of the course, participants will be able to

Define the Expected Value of Sample Information (EVSI)
Distinguish four recently developed calculation methods for EVSI
Decide which EVSI calculation method is suitable for a given health economic decision model
Calculate EVSI in R for two different health economic models
Present EVSI analyses using standardised, publication-quality graphics
Discuss key assumptions for calculating the Expected Net Benefit of Sampling (ENBS)
Design efficient future research studies by determining their optimal sample sizes

Description

Course Directors

Anna Heath
- University of Toronto
Hawre Jalal
- University of Pittsburgh Graduate School of Public Health

Course Faculty

Fernando Alarid-Escudero
- Drug Policy Program, Center for Research and Teaching in Economics (CIDE)
- Jeremy D. Goldhaber-Fiebert
  - Stanford Health Policy, Centers for Health Policy and Primary Care and Outcomes Research, Stanford University
- Natalia R. Kunst
  - Yale University School of Medicine

Session Fees

	Fee Type	Member Fee	Non-Member Fee
This session is free
	Early:	$204.00	$332.00
	Regular:	$250.00	$378.00
	Late:	$250.00	$378.00
This session is free
	Early:	$174.00	$174.00
	Regular:	$220.00	$220.00
	Late:	$220.00	$220.00