Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: Discuss various analytics and use cases using payer published reimbursement contract data under federal mandate of Transparency in Coverage. These contract rates are publicly available in machine readable format (MRF) starting July 1, 2022, and refreshed monthly. By attending the session, you will have a better understanding of the state-of-art development and analytics using MRF data, including the technologies used to extract and analyze huge MRF files, validation and limitations of published rates, and their use cases.

Description: "Discuss research conducted at the Cleveland Clinic to understand levels of anxiety and depression across Northeast Ohio. Specifically, learn how advanced analytical techniques were utilized with social media data from Twitter and Google to estimate the need for psychological support by geography and overtime. The panel will go further to demonstrate how natural language processing (NLP) and machine learning could be used to make operational decisions at a leading health care provider."

Description: Discussion of methods to estimate unpaid claim liability UCL for health plans. Includes traditional IBNR lag method and a lag method based on claims reported but not paid RBNP. Issue No. 45

Description: The presenters will discuss predictive analytics as applied to recent group life and disability experience studies and other applications.

Description: In this session, we will delve into the application of survey data analytics to extract valuable insights from public survey datasets. The discussion will start with the basics of survey design, sampling practices, and estimation of key statistics. Three case studies will be presented: one in the realm of population health and another in medical economics, both demonstrating the use of either SAS or R to perform the survey analytics.

Description: The SOA Research Institute has been publishing its annual Getzen Model of Long-Run Medical Cost Trends for the past decade. The Health Care Cost Trends Strategic Research Committee is looking for a researcher to build on the legacy of the Getzen model and provide annual updates to the SOA’s long-term health care trend projections.

Description: Model design is an important part of being an actuary, and the SOA highlights the importance of the actuarial control cycle of model design, evaluation and monitoring. What tools are at our disposal for these steps? When should we be concerned or excited about model performance? Can we, and should we, use machine learning tools to assist with model improvement or development?

Description: The American Academy of Actuaries Health Solvency Subcommittee and the NAIC Health Risk-Based Capital (E) Working Group are in the process of analyzing and reviewing the H2-Underwriting Risk component and the managed care credit calculation in the health risk-based capital (HRBC) formula. Come learn what changes are ahead! While RBC is designed for solvency issues, also come hear about other ways health insurers manage their capital and surplus levels. Are others doing something you should try?

Description: This paper develops a formal framework to model the behavior of individual and small group health insurance policies in a competitive market. In this framework, anti-selective lapse is not assumed, but arises as a result of rational consumers seeking the best value in a competitive market where the premium rates are restricted by law. The authors obtain a model that addresses a number of fundamental questions which have not been fully answered previously, including the effect of price-induced anti-selective lapse on the mix of insureds in a block and the optimal renewal price to maximize the aggregate profit of a block.