Studies on Expenditure, Prices, and Value of Disease-Modifying Antirheumatic Drugs

Abstract

Objectives: To determine the expenditure of rheumatoid arthritis (RA) and price changes, and to elicit the preference-based value of disease-modifying antirheumatic drugs (DMARDs). Methods: First, Medical Expenditure Panel Survey (MEPS) data from 2008-2020 were used to estimate the expenditure for RA patients. Secondly, IBM Micromedex®-REDBOOK® data from 1998 to 2021 were used to assess the impact of new brand-name DMARD entries on the price trends of existing drugs. Thirdly, a web-based discrete choice experiment (DCE) was conducted to elicit the preference-based value of DMARDs. Results: The covariate-adjusted results showed a 75% ($17,791 to $31,105) increase in direct costs for the RA cohort from 2008-2020, primarily driven by rising prescription drug costs, 192% ($5,381 to $15,639) in 2020 dollars. Despite the competition, prices for brand-name DMARDs continued to rise, with variable effects of new entries on existing DMARD prices. The study also found that reducing pain was the most important attribute of DMARDs for RA patients, followed by out-of-pocket cost, improving physical function, reducing fatigue, experiencing severe adverse events, and the way the medication is taken. Preference heterogeneity was observed, and the preference-based value ranged from $91 to $231 per month. Conclusion: This study highlighted the increasing trend in the economic burden of RA, and the prices of DMARDs. Patient preferences and affordability should be considered when making treatment decisions. Implications and future research: The increasing trend of RA expenditure, largely driven by the rising costs of DMARDs and the variable impact of competition, highlights the need for a multifaceted approach beyond market competition to tackle the increasing trend of RA expenditure. Given the rising price of DMARDs, clinicians should consider affordability and patient preference when selecting DMARDs. Future research should explore additional data sources to generate a more comprehensive economic burden, investigate the impact of biosimilars on the existing price trends and explore practical methods for incorporating patient preference into policy decisions.