Current challenges in health economic modeling of cancer therapies: a research inquiry.

BACKGROUND The demand for economic models that evaluate cancer treatments is increasing, as healthcare decision makers struggle for ways to manage their budgets while providing the best care possible to patients with cancer. Yet, after nearly 2 decades of cultivating and refining techniques for modeling the cost-effectiveness and budget impact of cancer therapies, serious methodologic and policy challenges have emerged that question the adequacy of economic modeling as a sound decision-making tool in oncology. OBJECTIVES We sought to explore some of the contentious issues associated with the development and use of oncology economic models as informative tools in current healthcare decision-making. Our objective was to draw attention to these complex pharmacoeconomic concerns and to promote discussion within the oncology and health economics research communities. METHODS Using our combined expertise in health economics research and economic modeling, we structured our inquiry around the following 4 questions: (1) Are economic models adequately addressing questions relevant to oncology decision makers; (2) What are the methodologic limitations of oncology economic models; (3) What guidelines are followed for developing oncology economic models; and (4) Is the evolution of oncology economic modeling keeping pace with treatment innovation? Within the context of each of these questions, we discuss issues related to the technical limitations of oncology modeling, the availability of adequate data for developing models, and the problems with how modeling analyses and results are presented and interpreted. DISCUSSION There is general acceptance that economic models are good, essential tools for decision-making, but the practice of oncology and its rapidly evolving technologies present unique challenges that make assessing and demonstrating value especially complex. There is wide latitude for improvement in oncology modeling methodologies and how model results are presented and interpreted. CONCLUSION Complex technical and data availability issues with oncology economic modeling pose serious concerns that need to be addressed. It is our hope that this article will provide a framework to guide future discourse on this important topic.