EpicostR: An R Package for Computing Cancer-Related Healthcare Costs

Accurately quantifying the economic burden of cancer is critical for sustainable healthcare planning and resource allocation, particularly in the context of population aging and the growing number of survivors. Despite rich clinical and administrative data, the lack of a standardized, reproducible framework for integrating these sources and computing cancer-attributable costs remains a major barrier to policy-relevant economic analysis. We present epicostR, a novel R package that implements the core elements of the Epicost methodology to compute direct cancer-related costs distinct for patients’ clinically meaningful phases of care. The determination of phase-specific cost profiles is realized through a data-integration approach that links population-based cancer registries, containing patients’ clinical information, with administrative records tracking major flows of medical expenditures. By combining routines for data quality check and processing, cost computation, and visualization within an open-source and unified toolkit, epicostR provides a fully reproducible workflow for quantifying and validating micro-level cancer cost data. This enables healthcare institutions to autonomously evaluate economic burdens without the need of data sharing, helping to preserve patient privacy which is crucial in medical data setting. Moreover, the introduction of specific S3 classes and related generic methods promotes the development of standardized analysis systems for the production of harmonized outputs, that can both facilitate the comparability among territorial healthcare authorities and the modeling of cost drivers to predict expenditures under specific medical intervention scenarios.