Determining the Baseline Strategy in a Cost-Effectiveness Analysis with Treatment Sequences

In response to a growing number of treatment options in many disease areas, health technology assessments need to evaluate sequences of treatments instead of individual interventions. This study investigated the impact of the baseline strategy on the cost-effectiveness results, when a sequence of treatments was used. First, we reviewed submissions to the UK National Institute for Health and Care and Excellence to understand how economic models that used comparisons of treatment sequences defined the baseline strategy. We then built a simple Markov model to use as a case study. The analysis we conducted contained four hypothetical treatments of varying cost-effectiveness relationships to a fixed control (best supportive care): Treatment A was cost effective, Treatment B was extendedly dominated by Treatment A, Treatment C was cost effective, but had a greater cost than both Treatment A and Treatment B, and Treatment D was not cost effective. Our review of the National Institute for Health and Care and Excellence submissions showed that, in most cases, authors relied on clinical guidelines, expert opinion or previously developed models to define the baseline strategy (n = 31). In several cases, the choice of a baseline strategy was not explained (n = 9). Several studies used the model to identify the optimal position for the new intervention (n = 5). Using the model, all possible permutations between the hypothetical treatments were generated and ranked by their net monetary benefit. We showed that (1) a non-cost-effective treatment would never be part of an optimal sequence and (2) the choice of baseline treatment sequence can change the cost-effectiveness estimate of a new intervention. If the aim of the decision maker is the efficient distribution of healthcare resources based on cost effectiveness, then the baseline strategy should be created based on the ranking of the net-monetary benefit. Ignoring the cost effectiveness of individual treatments when defining the baseline strategy, may lead to spurious results.