Yi Z, Mauskopf J, Herring W, Graham J. Challenges in estimating eligible population size in budget-impact analyses for new health care technologies. Poster presented at the 2020 ISPOR Virtual Conference; May 2020. [abstract] Value Health. 2020 May 1; 23(Suppl 1):S288. doi: 10.1016/j.jval.2020.04.371.

OBJECTIVES: Budget impact analysis estimates the impact the introduction of a new technology has on a health system’s budget. The first step in budget impact analysis is to estimate the eligible population for the new technology, which is typically done using a population funnel. Many studies assume that the upper tiers of the funnel (e.g., epidemiology, percentage meeting certain eligibility criteria) would be unchanged by the introduction of a new technology. Our objective was to illustrate possible scenarios in which the different levels in the population funnel might be impacted by the new technology.

METHODS: A targeted literature review and general hypothesis were used to understand scenarios in which a new technology might impact the size of the treated population.

RESULTS: Findings suggest that new technologies can impact patient and provider motivations for treatment decisions such as the choice of patients to seek treatment or how providers screen for and diagnose disease. Examples include curative or preventive treatments and new treatments in diseases for which there is currently no treatment or only symptomatic treatment. This was seen when new hepatitis C treatments came to market, prompting calls for screening in those at risk but without symptoms. Also, the availability of an antiviral treatment and the rapid test for influenza impacted the number seeking care and the rate of diagnosis. Additional cases in which population dynamics could change include diagnostic testing for targeted therapies, new and easier to use administrative devices for specific therapies, and new, noninvasive testing options.

CONCLUSIONS: For certain technologies, it is important to understand how their entry into the market might change the number of individuals seeking care and diagnosed by their health care providers. Any additional resources used by a higher number of individuals in the final eligible population will add to the budget impact.

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