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: This article details the medical stop-loss coverages purchased by HMOs, small insurers and providers taking delegated financial risk in payor agreements. Along the way we will identify strategies purchasers often use to save money on medical stop-loss.

Description: Introduce basic concepts of the Health Risk-Based Capital and show case a few strategies around Risk-Based Capital.

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: 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: Two years ago, before COVID-19 changed everything about how we provide and receive health care, telehealth was largely provided by third-party vendors to treat a narrow range of acute one-and-done conditions. The value proposition was simple: a fast and easy member experience would drive satisfaction and engagement; high member satisfaction and engagement would drive health plan savings and member retention. Clearly, from the perspective of utilization, telehealth—as a viable alternative to in-person care during a pandemic—worked. And with COVID-19’s nudge—or was that a push?—toward cultural acceptance, the health care system is in a better position to capitalize on telehealth’s original promise of expanded access, lower cost and better outcomes than it was two years ago. But in the wake of the pandemic, it is just as clear to us that if telehealth is to live up to its full potential, some changes are needed. The rest of this article presents five ideas for improving the delivery of telehealth going 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: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.

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: 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.