Description: The coming wave of biosimilars could dramatically affect prescription drug costs and benefit strategies over the next several years. The launch of many Humira biosimilars in 2023 is the Big Event that will largely determine the impact of the biosimilar wave. Payers have many decisions to make about coverage and formulary tiers. What factors will drive payer decision-making?

Description: Article reviews the data a year into the unwinding of continuous coverage provisions in Medicaid, the impact on enrollment counts, how capitation rates have been adjusted, and compares those results to what has been modeled with the SOA Mediciad Unwinding model.

Description: This is Part 2 of 2 on changes affecting Medigap insurers. It focuses on marketing and regulatory differences between Medigap and Medicare Advantage that affect the competitiveness of Medigap plans.

Description: During the past few years, performance, cost, and risk trends for Medigap products have undergone substantial changes. Some of these trends could ease cost pressures on Medigap insurers, while others might increase them. Part 1 of this Issue Brief article discusses current changing trends and considerations around about how they are impacting Medigap.

Description: The coming wave of biosimilars could have a major impact on prescription drug spend in coming years. The big event of Humira biosimilar launches in 2023 will be significant in determining that ultimate impact. Payers are making coverage decisions. The more biosimilars are utilized, the greater the potential savings. How will biosimilar adoption be maximized?

Description: This article attempts to make a modest contribution to the dialogue on the potential and risks associated with novel treatments such as cell & gene therapies. With a fast-expanding roster of what are believed to be one-time treatments at ever increasing price points aimed at curing a wider swatch of the population, they are as much a source of relief for patients stuck in medical limbo, as they are a source of anxiety for payers.

Description: This Q&A article discusses the use of machine learning to analyze unstructured data. Supriya Ramachandra, a data scientist at SIKKA, explains how her team uses natural language processing techniques, technical aspects of neural networks, LSTM modeling, and natural language processing. Machine learning allows for the classification of large amounts of unorganized data, providing actionable information for actuaries.