HEALTH TECHNOLOGY ASSESSMENT AND PERSONALIZED MEDICINE: ARE ECONOMIC EVALUATION GUIDELINES SUFFICIENT TO SUPPORT DECISION MAKING?

Abstract

Background: Many jurisdictions delivering health care, including Canada, have developed guidance for conducting economic evaluation, often in the service of larger health technology assessment (HTA) and reimbursement processes. Like any health intervention, personalized medical (PM) interventions have costs and consequences that must be considered by reimbursement authorities with limited resources. However, current approaches to economic evaluation to support decision making have been largely developed from population-based approaches to therapy—that is, evaluating the costs and consequences of single interventions across single populations. This raises the issue as to whether these methods, as they are or more refined, are adequate to address more targeted approaches to therapy, or whether a new paradigm for assessing value in PM is required.Objectives: We describe specific issues relevant to the economic evaluation of diagnostics-based PM and assess whether current guidance for economic evaluation is sufficient to support decision making for PM interventions.Methods: Issues were identified through literature review and informal interviews with national and international experts (n = 10) in these analyses. This article elaborates on findings and discussion at a workshop held in Ottawa, Canada, in January 2012.Results: Specific issues related to better guiding economic evaluation of personalized medicine interventions include: how study questions are developed, populations are characterized, comparators are defined, effectiveness is evaluated, outcomes are valued and how resources are measured. Diagnostics-based PM also highlights the need for analyses outside of economic evaluation to support decision making.Conclusions: The consensus of this group of experts is that the economic evaluation of diagnostics-based PM may not require a new paradigm. However, greater complexity means that existing approaches and tools may require improvement to undertake these more analyses.