Presentation (CTI)

OBJECTIVES: Resources generated by clinical trials—free investigational drugs replacing standard-of-care therapies—remain economically “invisible” in traditional hospital accounting, limiting strategic budget planning. Value Data STUDI, a module of the integrated Value Data ecosystem developed at an Italian university hospital, aimed to determine whether dispersed, fragmented investigational-drug management data can be transformed into structured information to quantify avoided costs and support proactive pharmaceutical expenditure planning.
METHODS: A modular, scalable methodology was implemented through four sequential phases (process mapping/digitalization, traceability, dynamic analysis, standardization), grounded in lean-healthcare principles. A structured data-collection template captured study, design and economic-valuation information. Avoided costs were computed dynamically per administration route: for hospital-pharmacy-compounded parenteral drugs, by multiplying administered investigational therapies by the cost of the corresponding standard-of-care therapy; for non-parenteral/home-dispensed drugs, via an integrated method reconciling pharmacy and investigator dispensing data. Interactive dashboards (Power BI/ETL) enabled real-time projection of avoided costs by pathology, diagnosis and treatment line.
RESULTS: Applied to one university haematology unit (2024), the methodology quantified avoided costs equivalent to 15.4% of regional pharmaceutical expenditure for that unit. Activity managed included 272 trial protocols and 618 investigational drugs/forms, with 218,904 dispensing units processed and 32,738 centrally compounded. Digitalization eliminated paper-based inventory, improved traceability, reduced administrative search time, and enabled dynamic budget projections.
CONCLUSIONS: Value Data STUDI demonstrates that systematic valorization of clinical-trial drug management converts a hidden cost into a measurable, reusable economic resource. As one interoperable component of the broader Value Data ecosystem—alongside negotiated-agreement (MEAs), real-world-data and predictive (Horizon) modules—it offers a replicable, scalable model for evidence-based pharmaceutical governance across hospital, inter-hospital and regional levels.