Background: High quality evidence from randomized clinical trials (RCTs) comes at high costs. In the resource restrained academic setting, thoughtful allocation of financial resources for an RCT is, therefore, a crucial task. However, published estimates of RCT costs and empirical evidence on cost drivers of RCTs in different disciplines and settings are sparse. A commonly accepted, standardized format for cost calculations and estimates of associated unit costs of RCTs would facilitate learning processes in effective budget planning for RCTs.
1. create a comprehensive standardized list of direct and indirect RCT cost items; and
2. to determine the unit costs as well as the average/mean total cost of completed academic RCTs in Switzerland and internationally.
Methods: Based on a systematic literature review (MEDLINE/Embase), a systematic search of the internet (websites and any linked information), and templates from two institutions conducting clinical research in Switzerland, a comprehensive, standardized list of direct and indirect cost items associated with all phases of RCTs was compiled and validated by experts until consensus was reached. Thereafter, it was restructured into a user-friendly, adaptable tool. To determine the actual unit costs associated with each cost item in academia, experts from academic research institutions were surveyed and cost data was aggregated by disease area.
Results: At the time of the Colloquium, we will present an evidence-based, validated, comprehensive, and user-friendly costing template for RCTs in the academic setting. Cost items are stratified by direct and indirect costs at the level of modules, work packages, and items. We will also present actual unit costs and cost ranges associated with RCTs stratified by disease area.
Conclusions: To our knowledge this is the first study to develop a validated standardised tool for costing of RCTs and to systematically collect unit costs of academic clinical research. This evidence base will serve to identify major cost drivers, support efficient allocation of scarce resources, and improve trial planning for more cost-efficient academic research.