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Research Article: Augmenting clinical trial economic analysis by linking cancer trial data to administrative data: current landscape and future opportunities

Date Published: 2023-08-11

Abstract:
Background Economic analyses based on clinical trial data are costly and time consuming, and alternative methods for performing economic analyses should be explored. Objective and methods In this perspective, we examine the emerging role of administrative data for economic analyses in cancer. Results Compared with routinely collected clinical trial data, routinely collected administrative data have several strengths including high capture rates for healthcare encounters, less resource utilisation, low rates of misclassification, long follow-up periods and the opportunity to collect data points not traditionally captured in clinical trials. However, there are also limitations including the need for accurate data linkage across multiple databases and systems, the costs and time associated with data linkage, the potential time lag between trial data collection and the availability of administrative data, and limited data on quality of life, toxicity and indirect costs. In this perspective, we identify important barriers and potential solutions to performing economic analyses for oncology using administrative data, and outline strategies to increase research in this field. Conclusion The use of routinely collected administrative data sets for economic analyses of clinical trials presents a unique opportunity that could complement and validate economic analyses based on trial-level data.

Introduction:
Economic analyses are an essential component of health technology assessment (HTA). Their primary objectives are to evaluate the full impacts of a health intervention on outcomes and costs over a given time horizon, to shed light on the value and affordability at a population level and to inform drug funding and policy decisions. Resource utilisation inputs required for economic analyses are collected during clinical trials with costs subsequently applied to these data; however, systematically extracting and…

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