Subject: COURSE: EVIDENCE SYNTHESIS FOR HTA
EVIDENCE SYNTHESIS FOR HEALTH TECHNOLOGY ASSESSMENT: SYSTEMATIC REVIEW AND (PAIRWISE AND NETWORK) META-ANALYSIS OF TREATMENT EFFECT EVIDENCE
DATE: 6-8 MAY 2020
LOCATION: GLASGOW, UK
**Discount applies for participants from academic institutions and low- and middle-income (LMIC) countries**
The Health Economics and Health Technology Assessment (HEHTA) Research Group at the University of Glasgow is running a three-day workshop on the systematic review and synthesis of evidence regarding treatment effects. Now in its 9th edition, this course is continually being updated to include hot topics in the area. Course participants will gain hands-on experience of conducting pairwise and network meta-analyses, and an understanding of contextual issues through the analysis of case-studies.
The course is holistic in covering the whole process from the strategic analysis of the decision problem, through conduct of systematic reviews, to synthesis and interpretation of results. The faculty, which includes staff from reimbursement agencies and members of appraisal committees, have extensive practical experience of conducting synthesis and applying the results to real life problems.
Who is the course aimed at?
The course is designed for health technology assessment (HTA) practitioners, such as health economists, health service researchers and healthcare professionals who are interested in learning the key concepts involved in the design and undertaking of evidence synthesis in the context of HTA
What are the learning objectives?
At the end of the course, through problem-based learning, participants should be able to:
· Design and conduct high quality systematic reviews
· Conduct appropriate pairwise and network meta-analyses using Stata and/or R
· Explore bias and heterogeneity
· Gain an awareness of the practical challenges in evidence synthesis
What will the course cover?
This course will explore the principles and the practice of conducting a systematic review and meta-analysis through a mixture of presentations from members of the faculty, together with hands-on computer-based exercises using Stata and/or R, and discussions of case studies.
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