Budget Impact Analysis Has Limitations in Predicting US Biosimilar Value

The expectation of achieving potentially significant health-system cost savings stemming from competition among an increasing number of available biosimilars has led to widespread interest in developing modeling techniques that can accurately estimate the economic impact of biosimilar adoption.

The expectation of achieving potentially significant health-system cost savings stemming from competition among an increasing number of available biosimilars has led to widespread interest in developing modeling techniques that can accurately estimate the economic impact of biosimilar adoption.

Budget Impact Analysis (BIA) is 1 commonly used methodology for evaluating the economic implications of biosimilar adoption. While some methods of economic evaluation consider the efficiency of healthcare resource allocation, BIA considers its affordability. BIAs are used to address expected changes in healthcare system expenditures after the adoption of a new intervention, and are also used to budget or plan resources. Many countries have incorporated BIAs into formulary listings or decision-making regarding reimbursement at national, regional, and local levels since the 1990s. Despite their growing importance in healthcare decision-making, however, BIAs have not been widely published, according to a new literature review published in PharmacoEconomics.

Steven Simoens, MSc, PhD, of the Department of Pharmaceutical and Pharmacological Sciences at Katholieke Universiteit Leuven, Leuven, Belgium, and colleagues performed a review of the published BIA literature and identified only 12 unique publications that were generally in line with international recommendations for such studies, but even these reports had many deficiencies that the authors say make it difficult to fully understand the potential economic impact and value of biosimilars, the impact of biosimilar supply, and price competition.

The 12 studies the researchers found had “considerable” limitations, which included the range of included costs and reliance on assumptions instead of robust data, a lack of peer-reviewed journal articles, a limited range of cost parameters, reliance on assumptions for parameters such as uptake and drug pricing, a lack of expert validation, and a limited range of sensitivity analyses that were based on arbitrary ranges. To fully understand the potential economic impact and value of biosimilars, the authors said, BIAs should include the impact of biosimilar supply, manufacturer-provided supporting services, and price competition.

The investigators note that most clinical and payer experience with biosimilars stems from European countries that have a single-payer mechanism. In the United States, the implications of biosimilar utilization can be expected to differ because the market is categorized by multiple payers and greater fluidity, both in terms of formulary structure and patients’ choice of different health plans. “Although biosimilar uptake outside of the United States can provide some insight, the unique nature of the US market undoubtedly will result in different interpretations of the value of biosimilars,” they explain. The lack of published data on the budget impact of biosimilars limits interpretation, and additional economic models of biosimilars are needed to assess the range of their potential budget impact on the US healthcare system, the authors conclude.