Description: The article documents the efficacy of infra-low frequency neurofeedback regarding how it improves patient no show rates, decreases mental health symptoms by 40% or more, and self-harm and suicidal ideations.

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: 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: 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 paper presents a method for analyzing the experience of a stop-loss underwriter to develop a claim continuance table. This method is designed to deal with the limitations presented from certain limited information so as to get the most out of the available information. To the extent this approach is succesful, the credibility of the experience analysis will be maximized, thus minimizing the reliance on external data. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This paper presents a procedure for calculating aggregate stop-loss premiums that takes parameter uncertainty into account. From Actuarial Research Clearing House ARCH 1988, Vol. 3

Description: This article describes Medicare Supplement and short-term care products in more detail, and we compare their risk profiles. We explore the concept that these two products—when offered together—may provide a complementary hedge of certain policyholder behavior risks.

Description: This paper provides a method for estimating long-tailed unpaid losses from paid loss development using trended generalized bondy development. From Actuarial Research Clearing House 1993, VOL. 3.

Description: Actuaries are leveraging predictive modeling and machine learning more and more as they strive to provide greater value to their stakeholders. Actuarial standards of practice provide guidance around modeling and data. The world has changed significantly over the last few years, so it is important these models be tested for fairness as well as any statistical biases. This article addresses some of the key issues actuaries need to be aware of as Corporations and society work through the responsible us of this technology and underlying data.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.