[Methods for the analysis and treatment of cost data by micro- and gross-costing approaches]

This work addresses the analysis of individual cost data in the setting of interventional or observational studies using statistical analysis software once the costs per patient have been estimated. It is in fact necessary to be able to present and describe data in an appropriate manner in each of the studied health strategies and to test whether the difference in costs observed between treatment groups is due to chance or not. Furthermore, cost analysis differs from conventional statistical analysis in that cost data have a certain number of specific properties, including their use by health decision-makers. This work also addresses the difficulties that generally arise in regard to the distribution of cost; it explains why the mathematical average constitutes the only relevant measure for economists; and it outlines which analyses are required for inter-strategy cost comparisons. It also covers the issue of missing or censored data, features that are inherent to information collected regarding costs and to sensitivity analyses.