Is it the time to rethink clinical decision-making strategies? From a single clinical outcome evaluation to a Clinical Multi-criteria Decision Assessment (CMDA)

Multi-criteria decision analysis for health technology assessment: addressing methodological challenges to improve the state of the art

“…A second group of framework studies was developed for specific purposes, exploring one of the following areas: to apply MCDA in clinical decision-making when clinical consensus regarding clinical criteria and weights is required [132]; to inform radiology guideline development [133] and disease management programs [134]; to select an optimal nanomaterial for a given medical application [135]; to inform drug ranking for formulary listing in low-income countries [136]; to propose MCDA in HTA for middle-income countries [137] and to critically reflect upon that proposal [138]; to inform a wide range of decisions, e.g. approval, guidelines and pricing/reimbursement [43]; to evaluate statins for primary prevention of cardiovascular disease [42]; and to select criteria to be used in HTA [139, 140].…”

“…There is a lack of consensus about quantities such as ‘quality of life’ or ‘economic value’ of a healthy individual, which translate into evaluation difficulties. It is difficult to acquire and interpret data across heterogeneous health technologies[18, 19, 21, 24–28, 31, 42, 60, 63, 69, 74, 80, 82–84, 87–89, 91, 94, 97, 98, 102, 103, 112, 113, 126, 130–132, 135, 137, 140, 142, 143, 151–153, 155, 158–160, 164, 165]#2Value System Differences and Participant Selection issues (SOCIAL) (46 studies)There are variations in experts and stakeholders’ views and in the value systems of countries/regions/health systems. Value systems can vary over time and in response to new evidence.…”

“…There are limits to involve a large number of participants in a face-to-face setting. MCDA studies have been involving much smaller numbers of participants than large patient preference studies[19, 21, 24, 26, 27, 31, 33, 36, 57, 59, 60, 62, 63, 65, 66, 72, 73, 75, 78, 80, 82, 84, 97–99, 101–103, 106, 109, 111, 113, 116, 121, 123, 126, 129, 131, 132, 139, 142, 144, 147, 148, 153, 162]#3Participant Difficulties in Evaluation Processes (SOCIAL) (33 studies)Participants face difficulties in interpreting data or in understanding evaluation processes; they also face cognitive difficulties in providing judgments (for instance using swing weighting, comparing mild and serious events, understanding orders of magnitude, interpreting weighting coefficients). Evaluation judgments may be frame-dependent (e.g.…”

“…Not all aspects to be accounted for are quantifiable and it may not be possible to incorporate them into an MCDA model (e.g. context issues related to system capacity and appropriate use of an intervention)[21, 26, 30, 59, 61, 63, 73, 78, 82, 89, 123, 129, 130, 132, 134, 140, 149, 151, 157, 165]#6Uncertainty Modelling Needs (TECHNICAL) (19 studies)Health technology assessment entails uncertainty from multiple sources, related to scoring and weighting methods, criteria choice and with attributes in use (such as some based on point systems), as well as with evaluation judgments. Evaluators may not be able to give exact preference information on weights.…”

“…Acknowledging the existence of different schools of thought, the appropriate weighting technique is essential, as are the circumstances under which a specific technique should be used[18, 26, 33, 43, 58, 68, 69, 98, 121, 122, 126, 128, 134, 146, 148]#9Consensus Promotion and Aggregation of Participant Answers (SOCIAL) (12 studies)Despite the importance of promoting consensus, consensus agreement varies across studies and needs to be both accommodated and reported. There are also issues on how to properly combine individual judgments and to assess consensus[18, 24, 26, 30, 99, 113, 116, 121, 131, 132, 142, 153]#10Introduce Flexibility Features for Universal/General Evaluation Models (TECHNICAL) (9 studies)Despite the ambition of building universal (or general) models to compare distinct technologies across diseases and therapeutic areas, there are conceptual and methodological difficulties in developing such models. Different models tend to be built for different contexts[24, 36, 59, 101, 103, 106, 121, 144, 155]#11MCDA Training and Expertise Needs (TECHNICAL) (7 studies)There is a lack of familiarity with MCDA techniques and, consequently, there is a need for training staff for MCDA implementation, as well as a need for participant training (e.g.…”