Current trends in health technology assessment (HTA) indicate a shift away from the use of cost-effectiveness to value-related measures. A suite of analysis methods, collectively referred to as “risk-benefit analysis”, can be used to address these requirements. Of these, multi-criteria decision analysis (MCDA) is considered a leading candidate for practical application in HTA.
Limitations of cost-effectiveness analyses
The quality-adjusted life-year (QALY), frequently used in cost-effectiveness analyses and once the gold-standard outcome measure for economic evaluation in healthcare, is coming under heavier criticism than ever before. While appropriate in certain situations, the instruments used to generate QALYs have been shown to lack the required sensitivity to capture all benefits of interventions in some therapy areas, including hearing loss and schizophrenia.
Additionally, mounting evidence suggests that the health economist’s old dictum that “a QALY is a QALY is a QALY” is perhaps too much of a simplification. QALYs have a limited scope and may fail to accurately represent some benefits of a particular intervention, such as addressing unmet need, providing innovation and delivering societal benefits (for example, reduction of the caregiver burden).
The risk-benefit approach
Risk-benefit analysis offers an alternative approach where benefits of an intervention are balanced with additional factors alongside monetary costs, broadly defined as “risks.” Risk-benefit analysis offers the opportunity to handle various inputs and outcome measures together, regardless of the units in which they are expressed.
Convenient unit metrics can complement traditional clinical efficacy and monetary measures – for example staff use expressed as units of time can be used alongside direct performance measures such as patient satisfaction or adherence ratios, or with more abstract measures such as innovation or evidence quality.
Multi-criteria decision analysis (MCDA)
The most common and straightforward risk-benefit approach is based on a weighted sum capturing impact and importance; this is called multi-criteria decision analysis (MCDA).
For example, MCDA scores can be used to compare two different medical interventions First, a list of criteria for decision-making is generated. A score is calculated for each criterion across the two interventions to reflect how well or how poorly the alternative interventions perform. Each score is then weighted to reflect the criterion’s relative importance. The weighted scores are summed for each medical intervention, and the sums are compared to determine which intervention is best.
This raises one of the key challenges associated with MCDA—whose preferences should be used to determine how the scores should be weighted? Depending on the scenario, the most relevant preferences could be those of clinicians, budget holders, HTA committees or citizen panels.
MCDA is common in other fields of economics, including others in the healthcare sector, and its validity is well established. Perhaps the most important advantage of MCDA is the similarity it bears with general thought processes used in everyday decision-making.
MCDA has the potential to guide future pricing and market access decisions for new healthcare technologies. The types of evidence healthcare companies will need to provide might change, prompting a rethink of health economic evidence generation, and perhaps clinical development as a whole.