Current practice in cost-effectiveness analysis (CEA) involves the estimation of the incremental cost-effectiveness ratio (ICER) between a new intervention and one alternative comparator reflecting the standard of care. As this focuses on pairwise comparisons, rather than considering the whole range of available alternatives at any given time, this method fails to capture the full impact of bringing the new intervention to market.

A multi-comparator ICER (MC-ICER) evaluating the impact of the new technology on patients treated with all comparators used in clinical practice, rather than a theoretical ‘second-best’ alternative only, was estimated. This can be achieved by weighting the incremental costs and benefits for each comparator by its change in market share to generate an MC-ICER. This is shown using a stylized example with three comparators.

The traditional ICER against the second-best alternative was USD 200,000 per QALY, while the estimated multi-comparator ICER is USD 133,548 per QALY, corresponding to a 33 percent decrease. This reflects the fact that patients who switch to the new intervention are not only those who had been previously treated with one particular comparator, as is assumed in a traditional CEA. The difference between the traditional ICER and the MC-ICER depends on how the new intervention impacts on the uptake of each comparator.

Results show that, when comparator selection was made excluding dominated and extendedly-dominated alternatives, the MC-ICER, produced using the method described above, is lower than the traditional ICER comparing the new intervention to the second-best comparator. This captures the fact that patients may switch to the new intervention not only from the second-best comparator, but from the whole range of alternative treatments. Such patient movements determine the real impact, or opportunity cost, of the new intervention on the healthcare system and, therefore, should be captured in CEA alongside traditional one-way ICERs.