A REVIEW OF EXPANDED ACCESS PROGRAMS (EAP) AND THEIR CONSIDERATION BY HEALTH PLAN DECISION-MAKERS IN THE UNITED STATES
Author(s)
Khurdayan V, Rizzo M, Darity A, Mun DDouble Helix Consulting, New York, NY, USA
OBJECTIVES: After failing approved treatments, patients may receive investigational therapies through participation in a clinical trial or an expanded access program (EAP). EAPs were established after the FDA decided to allow patients access to investigational drugs for treatment purposes, and since then EAPs have been set up in various therapeutic areas including oncology and infectious diseases. No analysis, however, has been completed evaluating the use and value of EAP data to US payers. METHODS: We analyzed the impact of EAP data on the US payer decision making process in drug formulary positioning. Using examples of different types of drug data including EAP, payers were asked how each type affected drug coverage. After reviewing these results, we assessed payers’ awareness of EAP relative to other data types to determine future impacts of EAP. Our study allowed us to define the key value drivers for EAP trials and construct a value matrix to evaluate future EAP opportunities. RESULTS: Payers in the United States had a low awareness of EAP data driven by a lack of exposure to the data type but mostly attributed to their sole use of RCT data in formulary decisions. While most payers agreed that EAP data has little influence on their decision making process, they did highlight factors that make EAP data more valuable to other stakeholders and discussed how EAP data could improve product perception. CONCLUSIONS: Our findings suggest that payers will not change their management approach and formulary decisions based on EAP data. Payers realize that EAP data might be more representative of the real world patient population than data from RCTs; however, RCTs will remain the gold standard data source to evaluate agents for reimbursement and formulary placement.
Conference/Value in Health Info
2011-05, ISPOR 2011, Baltimore, MD, USA
Value in Health, Vol. 14, No. 3 (May 2011)
Code
PCN138
Topic
Methodological & Statistical Research
Topic Subcategory
Modeling and simulation
Disease
Oncology