Description: This article on IPV focuses on IPV during the COVID-19 pandemic

Description: PBMs are positioned in the healthcare delivery system as the only entity that is not regulated for profitability. The Commercial Fully Insured Health Insurance Plans are heavily regulated by the State Insurance Commissioner who allows only 2%-3% profit margin. The self-funded Health Plans are regulated by ERISA fiduciary responsibility that prohibits excessive compensation. PBMs are classed as a service provider and are not regulated by either. This allows PBMs to implement large, unreasonable mark ups for profit. PBMs are massive commercial entities, states are trying to sue under antitrust law. PBMs found a sweet spot in the regulation. Large Insurance Carries understood that and either acquired large PBMs or merged with them. It is likely that a combination of measures will be needed to regulate PBMs. The most direct approach would be for Congress to pass a law establishing PBM as a fiduciary under ERISA just like an “investment advisor” providing advice for a fee. Establishing PBM as a fiduciary will help Courts and other Federal Agencies ensure that PBMs do not unfairly retain rebates and inflate the prices of Rx drugs sold to employer health plans, and the US population in general.

Description: Regression to the mean is a phenomenon that arises when comparing sequential data points. It states that when an initial observation is extreme or an outlier, future observations will be closer to the average. Health care actuaries need to understand and be able to mitigate the effects of regression to the mean to avoid misapplying predictive models or misstating measurements of historical effects.

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: ACA risk adjustment is intended to "bridge the gap" between allowed rates and actuarial rates. If risk adjustment methodology is not bridging that gap & becomes an additional input to pricing formulae, it is not serving its intended purpose.

Description: This article is intended to inform readers about the current state of mental health and health care in the US, as were it's heading moving forward.

Description: Traditional risk scoring models include only fixed (non-random) demographic and condition-based variables. By including the provider effect as part of the risk scoring model as a random effect, we can get better estimates of provider performance (incorporating practice patterns conditional on patient morbidity profile). This approach can be generalized to study other factors that are now masked in error variance (i.e. area, Social Determinants) but if modeled could give us better estimates of risk

Description: In preparing claims reserves in the annual statement, health insurers and their opining actuaries will generally include a provision for adverse deviation (PAD) in their reserved amount in order to satisfy language in both in the National Association of Insurance Commissioners (NAIC) Health Annual Statement Instructions and in Actuarial Standards of Practice. This article explores the total level of PAD (both implicit and explicit margin combined) included in the reported claims reserves by examining NAIC filing data from 2016 through 2022.

Description: As actuaries in health care, we spend most of our time focused on reviewing claims, enrollment and clinical data. That information is captured while patients are in health care facilities. Yet most people spend only a small fraction of their time in these facilities. This article explores what types of data are available to actuaries the provide a more holistic view of the member so that a members physical and emotional needs, the social determinants of health can be taken into consideration along with their clinical needs. Two uses cases are presented so actuaries can see how these types of analyses can be leveraged to improve clinical, operational, and financial performance of risk bearing health entities. Understanding the customer (member) not just the patient enables actuaries to provide new insights and values to our stakeholders across a wide range of business and risk applications.

Description: When designing and pricing a healthcare product, it is not only important to know how to model frequency and severity, but it is essential to understand human behavior. Of course, the issue of anti-selection in medical insurance is well known as individuals know more about their health and prior expenditures than an insurer does. This type of behavior is certainly rational, and to be expected.