gms | German Medical Science

Entscheiden trotz Unsicherheit: 14. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin

Deutsches Netzwerk Evidenzbasierte Medizin e. V.

15.03. - 16.03.2013, Berlin

When is Enough Evidence Enough? – Using Systematic Decision Analysis and Value-of-Information Analysis to Determine the Need for Further Evidence

Meeting Abstract

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  • corresponding author Uwe Siebert - Dept. of Public Health and Health Technology Assessment, UMIT – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL – Center for Personalized Cancer Medicine, Innsbruck, Austria; Center for Health Decision Science, Dept. of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA; Institute for Technology Assessment and Dept. of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

Entscheiden trotz Unsicherheit. 14. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin. Berlin, 15.-16.03.2013. Düsseldorf: German Medical Science GMS Publishing House; 2013. Doc13ebmD5

doi: 10.3205/13ebm037, urn:nbn:de:0183-13ebm0375

Published: March 11, 2013

© 2013 Siebert.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Target group: All Stakeholders involved or interested in how to determine whether or not further evidence is needed to make decisions.

Background: Decision Analysis and Value-of-Information Analysis (DA-VOI) provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. Using best available existing evidence, this approach focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which further information will reduce this uncertainty. The quantitatively framework values the additional information to be generated by further research, and considers the decision maker’s objectives and resource constraints.

Content of the Tutorial:

  • Motivation:
    In medical decision making under uncertainty, there are two fundamental questions. The first fundamental question is: “Given the best available evidence (and its uncertainty), which decision should be made for now?”. The second type of question is: "Once the decision has been made for now, and given the degree of the remaining uncertainty, should we gather further evidence (i.e., perform further studies), and if yes, which studies (e.g. efficacy, side effects, quality of life, costs etc.) with which sample sizes are needed?"
  • Introduction to the framework of systematic value-of-information analysis to guide further research:
    The theoretical foundations and practical methods of decision analysis and value of information analysis will be explained using simple examples.
  • Applied case examples in prevention and treatment:
    Using applied cases from the published literature in oncology and neurological disorders, results of value-of-information analysis will be presented. It will also be discussed how the DA-VOI framework has been used by HTA agencies to guide further research.
  • Discussion:
    Strengths and limitations will be discussed interactively with the audience and questions from the audience will be answered.
  • Outlook:
    Take-home messages will be derived from the workshop and future challenges will be addressed.

Requirements: none

Workshop Language: English

Reading Material for Preparation: [1], [2], [3], [4].


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Claxton K, Neumann PJ, Araki S, Weinstein MC. Bayesian value-of-information analysis. An application to a policy model of Alzheimer's disease. Int J Technol Assess Health Care. 2001;17(1):38-55.
Claxton KP, Sculpher MJ. Using value of information analysis to prioritise health research: some lessons from recent UK experience. Pharmacoeconomics. 2006;24(11):1055-68.
Siebert U. When should decision-analytic modeling be used in the economic evaluation of health care? Eur J Health Econom. 2003;4(3):143-50.