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There is considerable interest and discussion surrounding the use of so-called big data in health care. Such datasets are often created when genome sequencing technologies are developed and evaluated. Given that genomics is an area where there are fewer clinical trials compared to medicines, there is an opportunity to use health economic data collected as part of large sequencing initiatives to inform cost-effectiveness analyses. However, there are numerous challenges associated with a big data approach to evaluating the cost-effectiveness of sequencing technologies. This chapter considers the main methodological and practical challenges of using big data in this context. A key challenge is how to link resource use and cost data from large observational cohort studies to the genomic information obtained from sequencing. Several potential solutions to specific challenges are proposed.

Original publication




Book title

Economic Evaluation in Genomic and Precision Medicine

Publication Date



113 - 121