OP89 The CE-Signal, A New Simplified Health Technology Assessment Method To Determine Whether Interventions Are Cost-Effective

Abstract

IntroductionConducting a cost-effectiveness analysis (CEA) is resource consuming, and therefore the Dutch National Health Care Institute (ZIN) only performs those for interventions with a high budget impact. Sometimes, cost-effectiveness (CE) estimates are clearly below or far above reference values, which makes full cost-effectiveness assessments less vital. The objective of this study was to develop an efficient and simplified method to identify interventions that are clearly cost-(in)effective.MethodsThe method makes use of headroom analysis. Several HTA experts and other relevant stakeholders have been asked to provide feedback on a preliminary version of the CE signal.ResultsThe method consists of five steps. In the first step (i) the relevant willingness-to-pay threshold is determined. Reference values are used by ZIN for the maximum willingness-to-pay per incremental quality-adjusted life year (QALY), depending on burden of disease.In next step (ii) the health gain that can realistically be obtained with the new treatment is estimated. Hereby the effect of the intervention on the clinical outcomes, quality of life and gained life years is determined to estimate the number of QALYs gained, including uncertainty. Then (iii) the societal cost maximum (SCM) of the new treatment is calculated by multiplying step 2 with step 1. In step four (iv) the incremental treatment costs are estimated looking at both the costs and savings for both treatments options for the average patient. In the final step (v) the incremental treatment costs are compared to the SCM to determine if the intervention is probably cost effective, probably not cost-effective or if a conclusion cannot be drawn.ConclusionsThis method has proven to be feasible and could be a valuable addition to the current cost-effectiveness assessment toolbox. The CE-signal is being validated against performing a full cost-effectiveness analysis.