Sheldon H. Jacobson, Department of Mechanical and Industrial Engineering, University of Illinois, 1206 West Green Street, MC-244, Urbana, IL, USA, Edward C. Sewell, Department of Mathematics and Statistics, Southern Illinois University, Edwardsville, IL, USA, and Bruce G. Weniger, Vaccine Safety and Development Branch, CDC, National Immunization Prog, 1600 Clifton Road (E-61), Atlanta, GA, USA.
KEYWORDS:
Combination Vaccines, Monte Carlo Simulation, Operations Research, Vaccine Selection Algorithm, Formularies
BACKGROUND:
A vaccine selection algorithm using integer programming was previously developed for vaccine purchasers to assemble formularies that satisfy the immunization schedule at the lowest overall cost to payers or to society (www.vaccineselection.com). This operations research tool weighs distinguishing features of economic consequence among competing vaccines.
OBJECTIVE(S):
Demonstrate how Monte Carlo simulation can be used to solve for the probability distribution of "inclusion prices" of hypothetical pentavalent and hexavalent vaccines that would permit each to win a place in lowest-cost formularies in competition with existing vaccines.
METHOD(S):
The algorithm was adapted to solve for the inclusion prices of four not-yet-US-licensed vaccines: DTPa-HIB-HBV, DTPa-HIB-IPV, DTPa-HBV-IPV, and DTPa-HIB-HBV-IPV. Monte Carlo simulation was applied as a sensitivity analysis to the integer programming model underlying the algorithm. Injection cost values were varied using normal, uniform, and exponential distributions so that the coefficients of variation were small, medium and large, respectively. Competing licensed products were set at March 2000 Federal contract prices.
RESULT(S):
Inclusion price probability distributions were normal and exponential for the corresponding injection cost probability distributions. For example, the normal distribution (µ=$20 and s=$4) yielded inclusion prices of $47, $51 and $54 for three doses of DTPa-HIB-IPV (without pertussis matching) at the 20th, 50th, and 80th percentiles, respectively. However, the uniform injection cost probability distributions resulted in non-uniform inclusion prices.
CONCLUSIONS(S):
These distributions provide pricing and market share information for combination vaccine prices across various populations. Monte Carlo simulation provides a quantitative tool for rational pricing and economic evaluation of new combinations entering the market.
LEARNING OBJECTIVES:
Understand the sensitivity of the point estimates for inclusion prices for hypothetical vaccines winning places in best-value formularies. Appreciate how operations research modeling, analysis, and Monte Carlo simulation are used to assess the economic value of combination vaccines.
Web Page:
www.vaccineselection.com
See more of Selecting Vaccines for Your Formulary: Tools for Purchasing Decisions
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