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Emisor:
AES ECONSALUD <[log in para visualizar]>
Reply To:
Economía de la Salud <[log in para visualizar]>
Fecha:
Mon, 21 Mar 2016 19:12:01 +0100
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Course Title: Statistical Methods for Value of Information Analysis
Course Dates: 8th - 10th June 2016
Course Location: University College, London
Course Website: https://www.ucl.ac.uk/statistics/research/statistics-health-economics/Short_course_VOI 

Course Lecturers:
Gianluca Baio (University College London)
Anna Heath (University College London)
Mark Strong (University of Sheffield)
Nicky Welton (University of Bristol, ConDuCT-II Hub for Trials Methodology Research)

Cost: 
For 3 days: £300 (£150 for students)
For the 1st day only: £100 (£50 for students)
For 2nd and 3rd days: £200 (£100 for students)

This course is subsidised by MRC Network of Hubs for Trials Methodology Research and UCL.
Travel bursaries are also available for students and hub network members, courtesy of the MRC Network of Hubs for Trials Methodology Research. To apply, contact [log in para visualizar] Two free places available per hub.

Registration: Registration is open, please visit the UCL online store: http://onlinestore.ucl.ac.uk/browse/extra_info.asp?compid=1&modid=2&catid=250&prodid=1342

Places available: 70 for Day 1; 30 for Days 2 and 3.

Course Description:
Day 1, 9:30 – 16:30, will cover: 
•	The interpretation of results from a probabilistic approach to cost-effectiveness analysis
•	The interpretation of the expected value of perfect information (EVPI), expected value of partial perfect information (EVPPI) and expected value of sample information measures
•	Possible uses of EVPPI for research prioritisation and adoption/reimbursement decisions
•	Potential use of EVSI for designing new research studies
This day will be an introduction to value of information and has no pre-requisites. This day can be taken as a stand-alone course.

Day 2, 9:00 – 16:30, will cover:
•	Simple probabilistic cost-effectiveness analysis in R, using the BCEA package
•	Simulation approaches to the computation of EVPI and EVPPI, and computation using R
•	Algebraic tricks that can be used to reduce computational burden of EVPPI, calculation using R
•	The computational challenges for EVPPI and EVSI

This day will be a mixture of lectures and computer practical. Therefore, some knowledge of computer programming is preferable, ideally in R. Knowledge of value of information methods (or attendance to Day 1) are necessary.

Day 3, 9:30 – 16:15, will cover:
•	Meta-modelling approaches for the computation of EVPPI 
•	The SAVI Web App for computation of EVPPI
•	The R package BCEA for computation of EVPPI

This day follows from Day 2 and again will be a mixture of lectures and computer practicals.

Who should attend: Anyone with interest in VoI methods and their application in Health-Economic Evaluations. 

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