Decision Analytic Modelling for Economic Evaluation

Start: 4th April 2016, York, England.University_of_york_banner

Decision analytic modelling is widely used internationally as a means of estimating the costs, outcomes and cost-effectiveness of different interventions and programmes in health care and public health. In particular, these methods are often employed to assess the value of new pharmaceuticals as a basis for health systems to determine whether they should be funded.

The Foundations Course in Modelling Methods is designed for those coming new to Decision Analytic Modelling for Economic Evaluation. This 2-day course will run on 4th & 5th April 2016 at the University of York.

Now in its 14th year, the University of York will also be running their 3-day Advanced Course in Modelling Methods for those with some experience in developing models for economic evaluation.
This will run from 6th – 8th April 2016 (directly after the Foundations Course).

The courses are delivered as a collaboration between the Centre for Health Economics at the University of York and Health Economics and Health Technology Assessment at the University of Glasgow. Both courses involve presentations from faculty with extensive experience in designing and programming decision models for economic evaluation, and using them to support decision making by health systems internationally. The courses also include tutored hands-on computer-based exercises to build understanding and practical skills.

Find more information and detailed programs of both courses here.

General information

Date:
Foundations Course
4 and 5 April 2016

Advanced Course
6 and 8 April 2016

Program:
Click here to find an overview about the program.

Course language:
English

Course location:
Classes will be held at the University of York.

Contact:
Linda Baillie
Course administrator
che-admod@york.ac.uk 
Tel: +44 (0)1904 321401

Register here.

 

Tip: More up to date educational events for medical doctors and health professionals can be found online in the Education Database »medicine & health«.

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