Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. 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. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making.

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions.

The objective of this study is to support those undertaking a multi-criteria decision analysis (MCDA) by reviewing the approaches adopted in healthcare MCDAs to date, how these varied with the objective of the study, and the lessons learned from this experience. Searches of EMBASE and MEDLINE identified 40 studies that provided 41 examples of MCDA in healthcare. Data were extracted on the objective of the study, methods employed, and decision makers' and study authors' reflections on the advantages and disadvantages of the methods. The recent interest in MCDA in healthcare is mirrored in an increase in the application of MCDA to evaluate healthcare interventions. Of the studies identified, the first was published in 1990, but more than half were published since 2011. They were undertaken in 18 different countries, and were designed to support investment (coverage and reimbursement), authorization, prescription, and research funding allocation decisions. Many intervention types were assessed: pharmaceuticals, public health interventions, screening, surgical interventions, and devices. Most used the value measurement approach and scored performance using predefined scales. Beyond these similarities, a diversity of different approaches were adopted, with only limited correspondence between the approach and the type of decision or product. Decision makers consulted as part of these studies, as well as the authors of the studies are positive about the potential of MCDA to improve decision making. Further work is required, however, to develop guidance for those undertaking MCDA.

Objective: Recent years have witnessed an increased interest in the use of multicriteria decision analysis (MCDA) to support health technology assessment (HTA) agencies for setting healthcare priorities. However, its implementation to date has been criticized for being "entirely mechanistic," ignoring opportunity costs, and not following best practice guidelines. This article provides guidance on the use of MCDA in this context. Methods:The present study was based on a systematic review and consensus development. We developed a typology of MCDA studies and good implementation practice. We reviewed 36 studies over the period 1990 to 2018 on their compliance with good practice and developed recommendations. We reached consensus among authors over the course of several review rounds. Results:We identified 3 MCDA study types: qualitative MCDA, quantitative MCDA, and MCDA with decision rules. The types perform differently in terms of quality, consistency, and transparency of recommendations on healthcare priorities. We advise HTA agencies to always include a deliberative component. Agencies should, at a minimum, undertake qualitative MCDA. The use of quantitative MCDA has additional benefits but also poses design challenges. MCDA with decision rules, used by HTA agencies in The Netherlands and the United Kingdom and typically referred to as structured deliberation, has the potential to further improve the formulation of recommendations but has not yet been subjected to broad experimentation and evaluation. Conclusion:MCDA holds large potential to support HTA agencies in setting healthcare priorities, but its implementation needs to be improved.

The potential for multi-criteria decision analysis (MCDA) to support health technology assessment (HTA) has been much discussed, and various HTA agencies are piloting or applying MCDA. Alongside these developments, good practice guidelines for the application of MCDA in health care have been developed. An assessment of current applications of MCDA to HTA in light of good practice guidelines reveals, however, that many have methodologic flaws that undermine their usefulness. Three challenges are considered: the use of additive models, a lack of connection between criteria scales and weights, and the use of MCDA in economic evaluation. More attention needs to be paid to MCDA good practice by researchers, journal editors, and decision makers and further methodologic developments are required if MCDA is to achieve its potential to support HTA.