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 sets forth an approximate solution to problems associated with demonstrating compliance of a limited number of price adjustment activities with regulations such as those contained in Section 300.20(b).

Description: This article provides a summary of selected sessions of the October 2010 NAIC meeting.

Description: This a book review of 'Synthetic State Estimates of Disability Derived from the National Health Survey' by the National Center for Health Statistics. This paper arose in response to the increasing demand for health statistics on the state level.

Description: In this paper we propose a model that can be used to analyze correlated claims data. In the process we introduce a class of multivariate generalized Poisson distributions. Then we present posterior distributions of its parameters. These distributions are difficult to manipulate, so we employ Markov chain Monte Carlo methods to draw random numbers from posteriors and predictive distributions. We present a collection of EXCEL VBA functions and subroutines to perform the simulations.

Description: Summary of the National Conference on Medical Costs, held in Washington, D.C. on June 28-29, 1967.

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 summarizes a recent session at an SOA meeting that presented tips on improving and speeding the product filing process.

Description: This article focuses on the recent surge of digital medicine data being seen in the healthcare industry. While an increase in data can generally be perceived as good, it is important to remember that current privacy practices need to be maintained, if not strengthened, to continually protect healthcare members. The COVID-19 pandemic helped fuel digital medicine data, but it also created new avenues for privacy to potentially be compromised (i.e. healthcare employees using personal devices while working from home). Digital medicine data is a very powerful asset, but it is also a massive responsibility. If mishandled, this data can cause more harm than good.