In this chapter, we have provided instructions for how to estimate the population size for the indicated and reimbursement-eligible population. As described above, this population will often not include all those with a diagnosis of the condition of interest but will be restricted to a subset based on condition severity, treatment his- tory, or other factors. These restrictions may be part of the marketing indication or added as restrictions for public or private reimbursement. Although the size of the indicated and reimbursement-eligible population will be a key determinant of the budget impact of the new drug, there may be circumstances where it is more appro- priate to include all those with the condition of interest in the budget-impact analysis.
As we will describe in the next chapter, the budget impact will also depend on the treatment mix with and without the new drug. In many cases, the only data available on the current treatment mix for a specific condition will be for all patients with that condition rather than broken out by condition severity or treatment history. For example, the current drug treatment mix for children and adolescents with attention- deficit/hyperactivity disorder (ADHD) will be available from market research data for all drug-treated patients but may not be available specifically for those who are intolerant of stimulants or for whom treatment with a stimulant has failed. However, the indication and reimbursement-eligible population for a new ADHD drug might only include those who are intolerant of stimulants or for whom treatment with a stimulant has failed. There are two options that we can use to estimate the budget impact of this new drug in this situation. We can develop estimates of the size of the indicated and reimbursement-eligible population as described in this chapter, and we can then estimate the treatment shares with and without the new drug in the treatment mix for the indicated and reimbursement-eligible population using observational database studies or expert opinion. Or we can estimate the size of the
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total drug-treated ADHD child and adolescent population, without considering the restricted indication for the new drug and use the available market research data estimates for the current treatment mix (i.e., estimate the eligible population at a broader level and use the available treatment mix data). If we use the first option, then the predicted uptake rates for the new drug and the new treatment mix will be those expected in the indicated and reimbursement-eligible population. If we use the second option, then the predicted uptake rates for the new drug in all drug- treated ADHD children and adolescents, a much broader population, will be much lower and the new treatment mix will be that expected in all drug-treated children with ADHD. Instructions for estimating the treatment mix for the budget-impact estimates with and without the new drug are presented in Chap. 4.
Exercises
Exercise 3.1 Explain the differences in incidence and prevalence and how they affect a budget-impact analysis.
Exercise 3.2 Explain the difference between the prevalence of a condition and the proportion of patients identified as having the condition.
Exercise 3.3 Why is it important to give budget holders population estimates for funneling their total population down to a population eligible for a specific treat- ment? Why is it important to allow the budget holders to change this information?
Exercise 3.4 How would a budget holder estimate the prevalence of a condi- tion by using annual incidence and life expectancy?
Exercise 3.5 List some attributes of a new treatment that might change the size of a treatment-eligible population and how those attributes may change the size of the population.
Exercise 3.6 Provide an example in which the treated population may differ from the population indicated for a new treatment.
Exercise 3.7 Develop case studies in which it is important to account for changes in the population size due to a new drug’s impact on cure rate, disease pro- gression, and survival.
Exercise 3.8 Identify a condition for which a new drug may be approved and may require patient subgrouping. Outline potential sources for data that may be used to reduce the population to the reimbursement-eligible population.
Exercise 3.9 Choose a condition for which a budget-impact analysis may be constructed for a new drug. Apply the funnel-down approach to identify the number of patients in the reimbursement-eligible population. Expand the funnel down to include consideration of patient subgroups.
Exercise 3.10 A new drug has come on the market to treat acute coronary syn- drome. Construct a funnel-down approach to estimate the number of patients in the reimbursement-eligible population. How would the reimbursement-eligible population change if a companion diagnostic were approved to better select patients for treatment? Discuss the impact if the companion diagnostic were con-
S. Earnshaw and J. Mauskopf
sidered for reimbursement versus if the companion diagnostic were not considered for reimbursement.
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© Springer International Publishing AG 2017
J. Mauskopf et al., Budget-Impact Analysis of Health Care Interventions, DOI 10.1007/978-3-319-50482-7_4
Chapter 4
Estimating the Treatment Mix
Thor-Henrik Brodtkorb, Josephine Mauskopf, and Stephanie Earnshaw
Abstract The mix of drugs used for estimating the cost and outcomes for the budget- impact analysis will likely change over the analysis time horizon even with- out the introduction of the new drug. This could be because of changes in treatment patterns or increasing uptake of recently approved drugs or patent expiration of cur- rent drugs. When a new drug is added to the formulary, the mix of drugs used for the budget-impact analysis will also change and depend upon the uptake of the new drug, whether it is added to currently used drugs or which of the currently used treatments it replaces. In this chapter, issues that may affect the treatment mix and methods for determining the treatment mix with and without the new drug are pre- sented. Potential sources of data are also discussed.
Keywords Treatment mix • Generic entry • Treatment shares • Projected mix
• Treatment switch • Market share • Drug uptake • Redistribution
Chapter Goals
To show how to estimate changes in the treatment mix over the analysis time horizon, both with and without the new drug in the mix, including accounting for the impact of loss of patent protection and entry of generic products over the analysis time horizon.
T.-H Brodtkorb (*) • J. Mauskopf • S. Earnshaw RTI Health Solutions,
RTI International, Ljungskile, Sweden e-mail: tbrodtkorb@rti.org
Once the size of the eligible population has been estimated for each analysis year with and without the new drug1 on the formulary, the next step is to estimate the treatment shares of the different drugs used by this population each year. Treatment shares might be expected to change over time both with and without the new drug in the treatment mix for several reasons:
• Changes in standard of care occur over time, with growing uptake of recently approved drugs and/or the new drug substituting for or being added to older drugs.
• Other new branded drugs are introduced during the analysis time horizon.
• Generic formulations of current drugs are introduced during the analysis time horizon.
To avoid excessively large numbers of drugs included in the treatment mix con- sidered within a budget-impact analysis, the treatment mix should include only those current drugs whose use might be affected by the addition of the new drug to the formulary over the analysis time horizon. Although our focus for this book is on drugs, the current treatment mix could include drug treatments, surgical treatments, or just watchful waiting (no active treatment). If surgical treatments or watchful waiting are likely to change when the new drug is added to the treatment mix, then they need to be included in the treatment mix tables along with their price, efficacy, and safety information to use in the analysis.