Multi-Criteria Decision Support for Evidence-Based Decision Making

Evidence-based medicine aims to apply the best available evidence gained from scientific research to medical decision making. Most of health care professionals apply evidence-based medicine in decisions of their daily work, e.g. in prescription, regulatory- and reimbursement policy decisions. Although the scientific evidence is mostly transparent and achieved with methodological rigour, the actual decisions are often unstructured, ad hoc and lack transparency. Multi-Criteria Decision Aiding (MCDA) methods can help in making structured and transparent decisions. MCDA methods have proven their usefulness in one-off decisions, but their usability in repeated decisions has been limited by the lack of domain-specific implementations including a model generation subsystem fed with stochastic data. Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of MCDA methods that can handle uncertain, imprecise, and missing information about the decision alternatives’ performances, decision makers’ preferences, and technical parameters. In this presentation, I will introduce the SMAA methodology together with some recent applications, and show how a decision support system including a SMAA module can help to bridge the gap between aggregate clinical data and evidence-based decision making.

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