Immunization Safety Branch, NIP, CDC Using the Web-Based Vaccine Selection Algorithm to Assemble Least-Cost Pediatric Immunization Formularies Daniel A. Allwine, M.S. This work is supported by Contract No. 200-2002-00789 from the Centers for Disease Control and Prevention (CDC). CDC Project Officer: Bruce G. Weniger, M.D., M.P.H. Immunization Safety Branch, NIP, CDC

Participants and Contributions A collaborative effort between government, academia, and industry. GOVERNMENT: Centers for Disease Control and Prevention Bruce G. Weniger, M.D., M.P.H. - Project Officer, SBIR Contract No. 200-2002-00789 - Vaccine Domain knowledge. ACADEMIA: University of Illinois at Urbana-Champaign Southern Illinois University Edwardsville Sheldon H. Jacobson, Ph.D. Edward C. Sewell, Ph.D. - Modeling and algorithm development. INDUSTRY: Austral Engineering and Software, Inc. Daniel A. Allwine, M.S., Alan R. Lindsey, Ph.D., M. A. QadeerAhmed, M.S., Jenna E. Bradford Software and user interface design and web implementation. Technology transition and commercialization.

Protect the Population from Vaccine-Preventable Diseases Health Care Goal Protect the Population from Vaccine-Preventable Diseases CONSIDERATIONS Medically Sound Cost-Effective

Project Motivation “COMBINATION CHAOS” The economic factors involved in establishing a cost-effective pediatric immunization formulary are not straight forward. Some tangible and intangible costs: Vaccines and related products Administration, storage, and delivery Pain and suffering (leads to avoidance) Potential treatment for unvaccinated individuals Combination vaccines are making the procurement landscape more complicated. “COMBINATION CHAOS”

Project Objectives  Assist health care professionals in making vaccine formulary choices for purchasing. Automate determination of best-value formularies to procure. Facilitate use of vaccine selection algorithm through a user-friendly website Provide access to large number of users throughout the health care system. Allow users to customize costs for their particular situation. Objectives in providing information about web site Best –value means economic best value, based on cost components of interest.

Problem Characteristics Specific Goal: Find optimal formulary Lowest-cost set of vaccines that satisfies the Recommended Childhood and Adolescent Immunization Schedule Considers cost factors beyond vaccine purchase price Puzzle Analogy: Put pieces together to form the picture We know the desired picture Each piece has a price There are many extra pieces A piece can be used in more than once Up to 5,000,000 different ways to assemble the puzzle We must find the least expensive way

Some Potential Users of Website Government Health Departments Minimize Cost to Taxpayers Maximize Coverage Private Health Care Organizations Minimize Cost to Clients Maximize Benefits Vaccine Manufacturers Establish Pricing Guidelines Enhance Competition MAXIMIZE PROFITS!! Public Sector: Federal and State agencies, county and city public health departments Health Insurance Companies: Use to negotiate better prices with vaccine manufacturers Use to determine which vaccine products to provide (hence reimburse) Vaccine Manufacturers: Use to evaluate value of and price for new and existing vaccine products (More on this Later)

Software Demonstration Go To www.VaccineSelection.com Public Sector: Federal and State agencies, county and city public health departments Health Insurance Companies: Use to negotiate better prices with vaccine manufacturers Use to determine which vaccine products to provide (hence reimburse) Vaccine Manufacturers: Use to evaluate value of and price for new and existing vaccine products

Revenue Modeling Scenario 1 Case 1: Pediarix = $38.34/dose Case 2: Pediarix = $33.00/dose Assumptions (Both Cases): Perinatal HBV = 50% DTPa Matching = 50% Federal Contract Pricing Net Effect: Reducing Glaxo’s price of Pediarix by 14% INCREASES Glaxo’s revenue by an average of 38.42% !! Dollars Public Sector: Federal and State agencies, county and city public health departments Health Insurance Companies: Use to negotiate better prices with vaccine manufacturers Use to determine which vaccine products to provide (hence reimburse) Vaccine Manufacturers: Use to evaluate value of and price for new and existing vaccine products Monte Carlo simulation: 1,000 randomized samples for each data point.

Revenue Modeling Scenario 2 Dollars Potentially $ MILLIONS !! Public Sector: Federal and State agencies, county and city public health departments Health Insurance Companies: Use to negotiate better prices with vaccine manufacturers Use to determine which vaccine products to provide (hence reimburse) Vaccine Manufacturers: Use to evaluate value of and price for new and existing vaccine products Assumptions: DTPa Matching = 50%, Federal Contract Prices

Closing Remarks Existing Website Additional Services Customizable cost data Guaranteed optimal formulary Meets Recommended Immunization Schedule Enables what-if scenarios Currently free to use Additional Services Assistance with custom vaccine procurement scenarios Automation Revenue/Profit modeling Objectives in providing information about web site Best –value means economic best value, based on cost components of interest.

www.VaccineSelection.com THANK YOU!

www.VaccineSelection.com General settings Per-product settings

www.VaccineSelection.com Add a vaccine product Set visit cost Set injection cost

www.vaccineselection.com DTPa brand macthing HBV perinatal dose

Sample Website Output

The Schedule

Technical Content CDC/Academia collaboration since 1996. Operations research modeling and economic vaccine selection algorithm within the childhood immunization schedule. Weniger, B.G., Chen, R.T., Jacobson, S.H. Sewell, E.C. Deuson, R., Livengood, J.R., Orenstein, W.A., 1998, "Addressing the Challenges to Immunization Practice with an Economic Algorithm for Vaccine Selection," Vaccine, 16(19), 1885-1897. Jacobson, S.H., Sewell, E.C., Deuson, R., Weniger, B.G., 1999, “An Integer Programming Model for Vaccine Procurement and Delivery for Childhood Immunization: A Pilot Study,” Health Care Management Science, 2, 1-9. Sewell, E.C., Jacobson, S.H., Weniger, B.G., 2001, “ “Reverse Engineering” a Formulary Selection Algorithm to Determine the Economic Value of Pentavalent and Hexavalent Combination Vaccines,” Pediatric Infectious Disease Journal, 20(11), S45-S56. Jacobson, S.H., Sewell, E.C., 2002, "Using Monte Carlo Simulation to Determine Combination Vaccine Price Distributions for Childhood Diseases,” Health Care Management Science, 5(1). Jacobson, S.H., Sewell, E.C., Allwine, D.A., Medina, E.A., and Weniger, B.G., “Designing pediatric vaccine formularies and pricing combination vaccines using operations research models and algorithms,” Special Report. Expert Review of Vaccines 2(1), 15-19, 2003. Jacobson, S.H., Karnani, T., and Sewell, E.C., “Analyzing the economic value of the hepatitis-B - Haemophilus influenzae type B combination vaccine by reverse engineering a formulary selection algorithm,” Vaccine 2003;21:2169-2177.

Operations Research Model Operations research model currently captures: ACIP recommended childhood immunization schedule requirements. Cost components (e.g., vaccine purchase prices, labor costs, office visit costs, injection costs). Vaccine constraints (e.g., number of injections, age limitations, brand matching). Vaccine wastage by expiration.

Vaccine Selection Algorithm Uses operations research principles to determine the best-value (lowest cost) vaccine formulary that satisfies all the constraints. Efficiently search across all possible sets of vaccine products There are approximately 100,000 to 5,000,000 vaccine formularies to examine for each set of cost data. As additional vaccines (particularly combination vaccines) are added to the market, this number will grow exponentially!

Search Tree Organized procedure to examine all the possibilities At each level, must choose a vaccine for a disease/month. Preprocessing eliminates vaccines that cannot possibly be in best-value formulary. Pruning eliminates useless branches. MRK None GSK MRK HIB-HBV AVP HIB Month 2 DTPa HBV

Search Engine and Validation “Back End” Search Engine is written in C++ Typical problem Solved in less than one second 500,000 to 1,000,000 branches (partial solutions). 50,000 to 100,000 full solutions are examined Problem was also modeled as an Integer Program (IP) Used AMPL to generate the IP from the data, CPLEX to solve the IP Randomly generated 1,000 test problems Input parameters randomly chosen Prices randomly generated Existing vaccines randomly chosen for inclusion/exclusion Hypothetical combination vaccines randomly created Test problems solved using both the search engine and the IP. Same solutions were found by both methods.

Website Architecture and User Interface Developed in state-of-the-art Microsoft® .NET platform Server Software: .NET components: solver in C++ and a managed wrapper in C# Default and user-customized vaccine data in SQL database Middleware Software: ASP.NET scripts generate HTML and Javascript code Served to web browser (client) by Internet Information Server Client software: user interface through common browsers Best when viewed in Internet Explorer Recently released a more friendly user interface for occasional users Similar to common tax preparation software packages Interview driven