RAPID: Shared decision models to guide drug allocation during a pediatric chemotherapy shortage

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

Drug shortages require decisions on the allocation of essential drugs that are in limited supply. Vincristine is a chemotherapeutic drug that is central to many treatment regimens involving the most common pediatric cancers. Currently, we are experiencing a vincristine shortage in the United States expected to last through 2020 and there is no drug substitution that has equal efficacy or mode of action. Children have already been impacted by the current vincristine shortage and it is expected that cancer drug shortages will continue to increase at an alarming rate given the lack of profitability and fragility of the supply chain. Clinicians experience uncertainty in how best to allocate drugs in limited supply, and communicate status updates across institutions. Additionally, it is difficult to assess the health and economic consequences of various shortage scenarios. This study fills an important scientific gap in understanding how decisions regarding drug shortages are made in real time. Modeling and simulating shared decision models have implications for not only the current vincristine drug shortage, but future drug shortages at large, including those represented by pandemic situations. Modeling the health and economic impacts may also have policy implications for regulations supporting the supply chain requirements of critical drugs without substitutions. This project advances the knowledge of assessments of risk and trade-offs in the context of a drug shortage. Additionally, this project identifies information critical to drug shortage communication among clinicians, hospital systems, patients and families impacted by the shortage, drug manufacturers, regulators, and society at large. Tis project advances the development of scientific methods necessary to promote national health and welfare. By testing shared decision models necessary to guide drug allocation, the investigators will develop a decision framework that can also be applied in practice. Specifically, this project uses a mixed-modal approach of immersive qualitative methods followed by decision analytic modeling and Monte Carlo simulation to (1) evaluate current decision-making processes for drug allocation given the vincristine pediatric chemotherapy shortage and (2) use stakeholder-guided decisions and real-world data to model and simulate the clinical and economic outcomes of various drug allocation shortage scenarios. While the lens of this award is focused on the current vincristine shortage, the methods and principles of this work are novel in terms of understanding how decision making and risk communication processes are occurring in the context of uncertainty and lack of alternative treatment strategies. This methodological approach is also used to develop best practices for future decision analysis of drug shortages. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.