Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. Complexity in the healthcare decisions is inevitable, whether a high-level decision, such as that made by a budget holder, allocating limited resources across treatments, or at the micro-level, such as a patient’s decision on the best treatment alternative.

Decision makers, whether they are individuals or committees, have difficulty processing and systematically evaluating relevant information. This assessment process involves confronting trade- offs between the alternatives under consideration. Each decision maker will need to prioritize what matters most. If more than one individual is involved, the priorities of involved decision makers can, and frequently do, conflict, increasing the difficulty and complexity of the decision-making process. Despite this complexity, decisions are made: even sticking with status quo is itself a decision.

The decision-making process can be improved by working with decision makers and stakeholders providing support and structure to the process. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. This set of techniques provides clarity on which criteria are relevant, the importance attached to each, and how to use this information in a framework for assessing the available alternatives. By doing so, they can help increase the consistency, transparency, and legitimacy of decisions.

MCDA is defined as “an extension of decision theory that covers any decision with multiple objectives”. MCDA comprises a broad set of methodological approaches, originating from operations research, yet with a rich intellectual grounding in other disciplines. MCDA methods are widely used in public-sector and private-sector decisions on transport, immigration, education, investment, environment, energy, defense, and so forth. The health care sector has been relatively slow to apply MCDA. But as more researchers and practitioners have become aware of the techniques, there has been a sharp increase in its health care application.

Methods of MCDA are available to analyze and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process.

A challenge for users of MCDA, however, is that there are many MCDA methods available. These differ not just in how MCDA is put into practice but also in terms of the fundamental theories and beliefs underpinning them. The existence of different schools of thought, representing different positions on how MCDA should be performed, makes the choice of MCDA method to use in any given context quite complex. This is made still more difficult by the existence of various commercial and not-for-profit MCDA “toolkits” promoted by their developers. The current literature on MCDA in healthcare offers little guidance to users on how to choose from the bewildering array of approaches, on the “best” approach for different types of decisions, and what the relevant considerations are. In the absence of guidance on how to implement MCDA techniques in health care, MCDA can be misused and the decision makers misled.

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