Description: Statement that the SOA has formed a task force to address the morbidity tables used for minimum reserves of individual and group health insurance contracts. Issue No. 35.

Description: Methods and assumptions used in the valuation of savings by external care vendors

Description: This article provides an overview of critical illness insurance: history, product description, and the three primary ways to offer critical illness coverage in the United States. This article also contains an illustration of an issue age premium rate calculation, as well as product features and rating applications specific to the various types of critical illness coverage.

Description: CMS provides ACOs with monthly claims data for members, including their medical visits and ACO program eligibility. This data can be divided into Membership and Claims tables through the ETL process. However, when calculating PMPY at specific levels of detail using these tables, issues arise due to unrelated dimensions, leading to inaccurate and understated results. This article presents a solution to this problem by utilizing Tableau's data blending capabilities.

Description: Response to March 2021 Practice Note on ASOP 6

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: 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: Health Watch Newsletter, May 2006, Issue No. 52. This article presents information from a recently completed client-sponsored survey of hospital contracting best practices. Individual health plans were evaluated using a structured survey document. The primary objective of the survey was to identify best practices that the client sponsor could implement to improve its already better-than-average hospital contracting practices

Description: This article provides a brief overview of the current state of machine learning (ML) and artificial intelligence (AI) as they apply to actuarial science, including discussion around the integration of actuarial judgment with ML and AI. It concludes with an example of explainable ML through a python tool known as SHAP (SHapley Additive exPlanations), which is able to explain the key drivers behind individual ML or AI predictions.

Description: Results of an SOA survey regarding the expectation for 2015 accruals for 3Rs and cost sharing reduction payments