PHARMACOECONOMIC APPLICATIONS IN FORMULARY MANAGEMENT- BUDGET IMPACT ANALYSIS OF CLORFARABINE AT A MAJOR CANCER CENTER

Author(s)

Lesley-Ann Miller, PhD, Research Specialist, Jason Lau, BA, Research Data Coordinator, Lincy S. Lal, PhD, Research Specialist, Rebecca Arbuckle, RPh, MS, DirectorUniversity of Texas M.D. Anderson Cancer Center, Houston, TX, USA

OBJECTIVES Develop a budget impact analysis to present to the Pharmacy and Therapeutics (P&T) Committee for approval of clorfarabine (FDA-approved for ALL in December 2004) to the institution's Formulary for acute lymphoblastic leukemia (ALL). A post-approval study was performed to assess the accuracy and validity of our model. METHODS A pre-approval annual budget impact model for clorfarabine was developed for an institutional population of 24 ALL patients, and presented to P&T in May 2005. Assumptions regarding clorfarabine's number of doses per cycle and median number of cycles per patient were estimated from published clinical trials and clinicians estimated use. In August 2008, a post-approval economic analysis was conducted to assess the actual annual budget impact of clorfarabine. We reviewed all use (excluding investigational) of clorfarabine from June 2006 through May 2007. We also reviewed charge and reimbursement data for clorfarabine for the same time period. All costs were adjusted to 2008 dollars. RESULTS During the study period for the post-approval analysis, we treated 23 patients with clorfarabine; of these, only 5 (22%) were for ALL, 13 (56%) for acute myelogenous leukemia and 5 (22%) for other indications. For the ALL population, we had a positive reimbursement margin, and reimbursement to charge ratio was 77%. For all indications, the overall reimbursement to charge ratio for clorfarabine was 53%. Actual budget impact was $1,105,598; less than the $2,430,000 predicted from the pre-approval model. CONCLUSIONS The result of the post-approval budget impact analysis of clorfarabine was lower than that estimated by the pre-approval model. Our pre-approval model included only ALL patients and overestimated the number of patients actually treated. Major factors driving the difference between the pre- and post-approval studies were actual drug cost per dose, actual number of doses per patient, and off-label usage. Future studies will include estimation of off-label usage in the pre-approval model.

Conference/Value in Health Info

2009-05, ISPOR 2009, Orlando, FL, USA

Value in Health, Vol. 12, No. 3 (May 2009)

Code

PCN22

Topic

Economic Evaluation

Topic Subcategory

Budget Impact Analysis

Disease

Oncology

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