Reimbursement Policy and Drug Shortages

• 成果类型: Article; Early Access
• 署名作者: Zhao, Xuejun; Jia, Justin; Zhao, Hui
• 署名单位: University of North Carolina; University of North Carolina Charlotte; University of Tennessee System; University of Tennessee Knoxville; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2023.02223
• 发表日期: 2025
• 关键词: pharmaceutical supply chain; drug shortages; drug reimbursement policy; data-driven reimbursement; group purchasing organizations; game theory

摘要

Generic drug shortages have posed significant challenges to the U.S. pharmaceutical industry and the government for two decades, causing severe consequences and drawing widespread attention. Substantial efforts have been devoted to identifying the causes, with some linking shortages to Medicare's adoption of the average sales price (ASP) policy for hospital drug reimbursement. However, little research has captured the connections among reimbursement policies, shortages, and the influence of group purchasing organizations (GPOs), which play a key role in representing hospitals to set prices with manufacturers. Recognizing that the reimbursement policy influences shortages through affecting supply chain parties' decisions, we analyze a drug supply model that captures the essential elements and tradeoffs in drug wholesale price decisions. We find that under the ASP policy, the interplay of two opposing effects, the free-ride effect and the aligning effect, guides wholesale pricing decisions and affects shortage outcomes. We capture key factors influencing these effects and show that the ASP policy actually possesses resistance to shortages of drugs that have experienced shortages. Overcoming the challenges of limited data transparency, especially on GPOs, we further conduct numerical analysis incorporating various data sources (with the aid of machine learning) to gain additional insights. In addition to confirming ASP's resistance to shortages, the numerical analysis quantitatively investigates the impact of policy and GPO-related parameters. We provide a thorough discussion of policy implications based on our theoretical and numerical findings. Notably, compared with the previously adopted fixed-price reimbursement policy, which we model as a benchmark in our analysis, ASP represents a market-data-driven policy. This distinction underscores the importance of a deep understanding of such policies for future policy evaluation and shortage mitigation.