Developing appropriate methods for handling missing data in health economic evaluation.

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Policy makers worldwide use health economic evaluation to help decide which health care interventions to provide. An important concern faced by economic evaluation studies is that there may be missing data. However, most published studies ignore this or use inappropriate methods to address the problem. If missing data are not addressed appropriately this can lead to misleading cost-effectiveness results and scarce health care resources being misallocated. Careful analytical methods are required to address missing data across different circumstances in health economic evaluation. I propose to conduct a comprehensive programme of research to address this gap in knowledge, using both simulation work and data from clinical areas of high policy relevance. The research will develop and test alternative methods for addressing missing data and show the impact that better methods can have in the evaluation of health interventions and health care providers. Methods will be thoroughly disseminated to applied researchers and policy makers to improve current practice. By helping improve the quality of cost-effectiveness studies which are used to inform policy making, this research will help ensure that scarce resources are allocated in the best ways for improving the population's health.