Unifying research and reimbursement decisions: a framework and algorithm for policy choice?

Abstract

The purpose of this study is to develop a general, unified theoretical framework which combines assessments of: i) cost-effectiveness, ii) the need for different types of evidence, iii) sources of uncertainty which cannot be resolved by research but only over time, and iv) investment and future reversal costs, within which the range of possible decisions ('only in research' (OIR), 'approval with evidence development' (AED), Approve or Reject) can be considered.  Decisions are commonly made when there is uncertainty surrounding cost-effectiveness and where further evidence may be valuable. However, approval can have an impact on the prospects of acquiring particular types of evidence and may require investment or impose future reversal costs.   There may also be other sources of uncertainty which can only be resolved over time.  Each of these considerations interact, making the implications for reimbursement and research decisions complex and sometimes unexpected.  Through a sequence of numerical examples, generalised through notation, each of these previously but separately considered areas are unified.   A single numerical example, comparing two technologies over 3 time periods is built upon in stages (with general notation) providing an intuitive demonstration of the potential impact of each additional consideration; explaining the sometimes complex interactions.   The resulting framework is used to construct an algorithm for policy choice, identifying the appropriate sequence of assessments which lead to different types of reimbursement and research decisions.