Description: This article is an update on the No Surprises Act, which is a U.S. Act aimed to reduce the risk that a person unexpectedly receives out of network charges for their health care visits.

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: 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: 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: 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.

Description: Presents a step-by-step methodology for calculating confidence intervals for IBNR estimates derived using the Averaqe PMPM method. It is a companion article to the January 2023 Health Watch article presenting the Average PMPM method for generating point estimates of IBNR with zero claims runout.

Description: Cost sharing reduction (CSR) payments are offered to low-income individual insurance buyers under the ACA. After October 2017, the difference in costs between the standard silver plan and CSR variants were defunded. To cover the costs of defunding, insurers have increased rates either through "broad loading" or "silver loading." States are approaching this adjustment differently, which is leading to some interesting differences between states. This article will review these differences.