Abstract
The purpose of budget-impact analysis is to project the potential future impact of the introduction of a new drug or other intervention on payer or provider budgets. Because estimates of current input values as well as assumptions about the structural model elements and changes in many input values over the analysis time horizon are needed, the results are estimated with uncertainty. Therefore, it is important for the model to include a method for performing uncertainty analyses. Uncertainty analyses allow the user to test the impact of different structural elements, assumptions, and input parameter values on the outcomes of the budget-impact analysis. In this chapter, methods for testing the impact on the results are presented (1) for alternative scenarios created using data and assumptions known to the budget holder and (2) for estimated ranges of input parameter values using uncertain data estimates and assumptions.
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Notes
- 1.
In this chapter we make the simplifying assumption that the budget-impact analysis is based on the introduction of a new drug to the current mix of drugs for treatment of a condition. Changes in our recommended approaches to estimate the budget impacts of other types of healthcare interventions (i.e., vaccines, diagnostics, surgery, and devices) are discussed in Chap. 13.
References
Canon JL, Vansteenkiste J, Bodoky G, Mateos MV, Bastit L, Ferreira I, et al. Randomized, double-blind, active-controlled trial of every-3-week darbepoetin alfa for the treatment of chemotherapy-induced anemia. J Natl Cancer Inst. 2006;98(4):273–84. Cited in: Rubin et al. 2008.
Mauskopf J. Modelling technique, structural assumptions, input parameter values: which has the most impact on the results of a cost-effectiveness analysis? Pharmacoeconomics. 2014;32(6):521–3. doi:10.1007/s40273-014-0157-7.
National Institute for Health and Care Excellence (NICE). Guide to the methods of technology appraisal 2013. 2013. http://nice.org.uk/process/pmg9. Accessed 5 Aug 2016.
Neyt M, Cleemput I, Van de Sande S, Thiry N. Belgian guidelines for budget impact analyses. Acta Clin Belg. 2015;70(3):175–80. doi:10.1179/2295333714Y.0000000118.
Purmonen TT, Auvinen PK, Martikainen JA. Budget impact analysis of trastuzumab in early breast cancer: a hospital district perspective. Int J Technol Assess Health Care. 2010;26(2):163–9. doi:10.1017/S0266462310000103.
Rubin RJ, Glaspy JA, Adams JL, Mafilios MS, Wang SM, Viswanathan HN, et al. Budget impact analysis of darbepoetin alfa every 3 weeks versus epoetin alfa every week for the treatment of chemotherapy-induced anaemia from a US payer’s perspective. J Med Econ. 2008;11(2):199–213. doi:10.3111/13696990801959656.
Sullivan SD, Mauskopf JA, Augustovski F, Caro JJ, Lee KM, Minchin M, et al. Budget impact analysis—principles of good practice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value Health. 2014;17(1):5–14. doi:10.1016/j.jval.2013.08.2291.
Taylor K, Ganly P, Charu V, DiBenedetto J, Kracht K, Rossi G, et al. Randomized, double-blind, placebo-controlled study of darbepoetin alfa every 3 weeks for the treatment of chemotherapy-induced anemia. Blood. 2005;106:992A–3A. (abstract 3556). Cited in: Rubin et al. 2008.
Tosteson ANA, Burge RT, Marshall DA, Lindsay R. Therapies for treatment of osteoporosis in US women: cost-effectiveness and budget impact considerations. Am J Manag Care. 2008;14(9):605–15.
Waltzman R, Croot C, Justice GR, Fesen MR, Charu V, Williams D. Randomized comparison of epoetin alfa (40,000 U weekly) and darbepoetin alfa (200 microg every 2 weeks) in anemic patients with cancer receiving chemotherapy. Oncologist. 2005;10(8):642–50. Cited in: Rubin et al. 2008.
Witzig TE, Silberstein PT, Loprinzi CL, Sloan JA, Novotny PJ, Mailliard JA, et al. Phase III, randomized, double-blind study of epoetin alfa compared with placebo in anemic patients receiving chemotherapy. J Clin Oncol. 2005;23(12):2606–17. Cited in: Rubin et al. 2008.
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Mauskopf, J., Earnshaw, S. (2017). Uncertainty Analysis. In: Budget-Impact Analysis of Health Care Interventions. Adis, Cham. https://doi.org/10.1007/978-3-319-50482-7_8
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DOI: https://doi.org/10.1007/978-3-319-50482-7_8
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