Early Economic Modelling to Inform Clinical Trial Design & Other Decisions
Date:
15/07/2020
Organised by:
York Health Economics Consortium
Presenter:
Dr Matthew Taylor (Director), Michelle Green (Project Director) and Julie Glanville (Associate Director), YHEC.
Level:
Entry (no or almost no prior knowledge)
Contact:
Niki Baines, 01904323204, niki.baines@york.ac.uk
Description:
Economic evaluations are increasingly used as tools to inform decision-makers about the cost-effectiveness of health technologies. Such evaluations are often undertaken during the late stages of the technology development (i.e. around the time of product launch or, in some cases, post-launch). However, there is an increasing need for the manufacturers of the technology to appraise the likely cost-effectiveness of the intervention before making decisions on price and indication, as well as to inform the development of clinical trials. The purposes of early economic modelling is to allow the user to determine the relative importance of different parameter inputs, in order to inform decisions on pricing, target populations and prioritisation of further research.
This one-day training session will cover the fundamental aspects of early economic modelling as well as exploring more advanced methods such as value of information analysis.
This course can be booked as a stand-alone day or can be combined with the ‘Health Utilities for Economic Models’ the following day.
We ask that you bring your own laptops to this course. If you do not have access to a laptop, please contact Niki (Training Course Administrator).
Cost:
Early bird: £240
Full price: £300
Website and registration:
Region:
Yorkshire and Humberside
Keywords:
Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, Research Management and Impact, Research Skills, Communication and Dissemination
Related publications and presentations:
Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
Research Management and Impact
Research Skills, Communication and Dissemination