Presentation given to UCSF student AMCP chapter on 1-3-11

1. Evaluating Budget Impact Models – A P&T Perspective By Carly J. Paoli, PharmD, MPH UCSF/Amgen Postdoctoral Fellow in Outcomes, Pharmaceutical Economics and Policy Studies paolic@pharmacy.ucsf.edu 3 January 2011

2. Learning Objectives Describe what a budget impact model (BIM) is and what it can and cannot do Define key concepts that support BIMs Learn how to evaluate key assumptions in a BIM Identify strengths and weaknesses of BIMs

3. Health Economic Models Health economic models usually come in two forms: Cost-effectiveness analysis (CEA) models BIMs Both are based upon what is termed decision analytic theory

4. Decision Analysis (DA) The term decision analysis was coined in 1964 by Ronald A. Howard, a professor at Stanford Graphical representation of a decision analytic problem is commonly displayed with a decision tree The decision tree, or model, depicts… Alternatives available to the decision maker (in our case, the health plan) The uncertainty they face (choosing one treatment or drug versus another and the consequences of that decision) Evaluation measures which represent how well each decision can achieve the intended outcome Uncertainties are represented through probabilities and probability distributions The decision maker's attitude to risk is represented by utility (often done with Quality Adjusted Life Years Saved, or QALYs).

5. DA Example 3. Probabilities associated w/choices 4. Outcomes 2. The decision node: two choices Choice 1 Total Cost = $6,000 1. The question being examined Choice 2 Total Cost = $17,250

6. CEA vs. BIM BIM Payer perspective (often the healthcare plan) Probabilities usually known due to modeling of a specific plan’s population Results measured in cost PMPM Utility often skipped b/c health plans mostly interested in cost CEA Societal perspective Probabilities represent a national/international population Results measured in cost per QALYS Utility must be utilized in the model to get a result

7. Sensitivity Analysis Key parameters in the model are varied to see if they affect the results For example, internal research shows that Drug X should have market uptake of approximately 12%. In order to see if the market uptake parameter is a sensitive variable in the model, we will need to vary it. One-way versus two-way sensitivity analyses If a parameter is varied and changes the results in the model then it becomes a key variable up for consideration If all variables are checked through sensitivity analysis and none of them change the results then the model is considered to be “robust to change.”

8. Key Points for Model Evaluation Is the model pathway clinically relevant? Do the cost assumptions seem valid? Are the probabilities in the model correct? Is utility used? If so, is it used appropriately? Was sensitivity analysis conducted? If so, was it done on the correct model parameters? Does the sensitivity analysis make sense?

9. Recommended Reading Briggs A, Clxton K & Sculpher M (eds.) Decision Modeling for Health Economic Evaluation 2006. Oxford University Press, Oxford, UK. Weinstein M. Principles of Good Practice for Decision Analytic Modeling in Health-Care Evaluation: Report of the ISPOR Task Force on Good Research Practices—Modeling Studies. Value in Health2003; 6: 9-17 MauskopfJ. Principles of Good Practice for Budget Impact Analysis: Report of the ISPOR Task Force on Good Research Practices: Budget Impact Analysis. Value in Health 2007; 10: 336-347. Miller DK & Homan SM. Determining Transition Probabilities: Confusions and Suggestions. Medical Decision Making 1994; 14: 52-58. Tufts University CEA Registry: https://research.tufts-nemc.org/cear/default.aspx PetittiDB. Meta-analysis, Decision Analysis, and Cost-effectiveness Analysis: Methods for Quantitative Synthesis in Medicine. Chapter 11 in: Measuring Preferences for Health States. Oxford University Press, Oxford, UK. Weinstein M, Torrance G & McGuire A. QALYs: The Basics. Value in Health 2009; 12(supp 1): S5-9. Hay JW, Smeeding J, Carroll NV, Drummond M, Garrison LP, Mansley EC, Mullins CD, Mycka JM, Seal B & Shi L.Good Research Practices for Measuring Drug Costs in Cost Effectiveness Analyses: Issues and Recommendations: The ISPOR Drug Cost Task Force Report—Part I. Value in Health2010; 13: 3-7. SonnenbergF & Beck JR. Markov Models in Medical Decision Making: A Practical Guide. Medical Decision Making 1993; 13: 322-338.

10. Educational Opportunity Alternate Opportunities After Graduation – The Path to Obtaining A Fellowship Student Educational Programming AMCP Annual Meeting & Showcase Minneapolis, MN Friday, April 29th, 2011 from 4-5pm (day and time subject to change)

11. Questions Thanks so much! Feel free to email me if you have questions 