SYSTEMATIC REVIEW APPROACHES FOR HTA- HORSES FOR COURSES?

Author(s)

Kenworthy J*;Langham J, Chetty M PHMR Associates, London, United Kingdom

Systematic reviews aim to identify, select, synthesize and appraise all high quality research evidence relevant to a particular research question, and are widely accepted as the gold standard for providing the best evidence for use in decision making. They are essential, routine components of submission data packages for health technology assessments (HTAs) of products undergoing evaluation for reimbursement and market access. Additionally, systematic reviews are often the source for clinical evidence used in health economic modelling to evaluate cost-effectiveness. Thus, they represent a substantial investment of resources, and incorrect or incomplete reviews could invalidate the proposed clinical and economic value of a product set out in a health technology submission and result in unfavourable reimbursement decisions and/or delayed market access. There are a number of best practice criteria set down for systematic reviews; the most widely recognised being from the Cochrane group. However, when carrying out a systematic review for HTA purposes researchers should be aware of the additional requirements set out by each agency. The Cochrane, UK National Institute for Clinical Excellence (NICE) and Germany’s Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesenis (IQWIG) methodological guidelines for conducting and reporting systematic reviews were analysed and an ‘inclusive’ checklist of requirements was developed to ensure the systematic review and meta-analysis met the broad set of HTA requirements and minimise the risk of having to repeat the procedure or create the need for a HTA review group to carry out its own review, which could potentially lead to an unfavourable reimbursement decision or a restriction on use.   An awareness of specific HTA systematic review requirements can help optimise the preparation of a data package for HTA submission and hence maximise the chances of success.

Conference/Value in Health Info

2013-11, ISPOR Europe 2013, The Convention Centre Dublin

Value in Health, Vol. 16, No. 7 (November 2013)

Code

PRM224

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Multiple Diseases

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