Economic Evaluation for Oncology

Date:

30/04/2020

Organised by:

York Health Economics Consortium

Presenter:

Dr Matthew Taylor (Director), Michelle Green (Project Director), Stuart Mealing (Associate Director) and Will Green (Senior Research Consultant).

Level:

Entry (no or almost no prior knowledge)

Contact:

Niki Baines, 01904323204, niki.baines@york.ac.uk

Map:

View in Google Maps  (YO10 5DD)

Venue:

University of York

Description:

This training day focuses on the development of economic models specifically in the area of oncology. The sessions will include overviews of the most common methods for modelling treatments for cancer, and will pay particular attention to the areas that prove most challenging in HTA, including survival curve analysis, data extrapolation, quality of life modelling (including adverse events), handling treatment discontinuation, modelling disease progression and post-progression model assumptions. The day will draw on examples from previous HTA submissions and will provide a number of recommendations for modelling frameworks. This course will be particularly suited to those people that commission oncology models. Please note that other more ‘hands-on’ modelling courses are run by the University of York.

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

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