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: Overview of a benefit rush and its effects on companies.

Description: ACA risk adjustment has now been in play for years. The original intent of risk adjustment was to help stabilize the market through measuring risk levels of each issuer. However, the risk adjustment program may have introduced additional uncertainty due to annual market shifts and model changes, making risk adjustment estimation is a difficult task. This article analyzes the results over time, including impacts from market changes and model changes.

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: Discover the key components of value-based care (VBC) contracts and their impact on provider credibility. Learn about benchmarks, measurement period results, and the unique challenges providers face in managing insurance risk. Gain insights into reducing costs and aligning financial incentives in the US healthcare market.

Description: Realizing the impact of medical errors on the U.S. health care system, the Health Section commissioned a research project to measure the annual frequency of medical errors and their total measurable direct and indirect cost to the economy.

Description: Response to March 2021 Practice Note on ASOP 6

Description: Article presents issues for postretirement medical on models, data and the frail elderly. From Health Section News, December 2000, Issue No. 39.

Description: The CMS Risk adjustment model allows actuaries to apply our analytical skills and business knowledge to solve risk and revenue challenges within Health Plans.

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.