Description: Response to March 2021 Practice Note on ASOP 6

Description: CMS provides ACOs with monthly claims data for members, including their medical visits and ACO program eligibility. This data can be divided into Membership and Claims tables through the ETL process. However, when calculating PMPY at specific levels of detail using these tables, issues arise due to unrelated dimensions, leading to inaccurate and understated results. This article presents a solution to this problem by utilizing Tableau's data blending capabilities.

Description: Learn how modernization of data, models, and technology are influencing workflows. This webcast will address how workflows are changing in response to new regulatory requirements and the impacts the changes have on modeling and end-to-end future state operating models. Industry leading actuaries will discuss: How team collaboration can increase quality and speed of reporting to internal and external stakeholders How to strengthen controls and compliance frameworks across finance and actuarial departments How to modernize actuarial input/output for strategic analysis and insights How to attract and retain top talent by improving opportunities for actuaries There will also be dedicated time to ask questions of those who have made the transition.

Description: In 2020 the Actuarial Innovation and Technology Steering Committee held a data visualization contest. Entries showed a variety of strengths including smart use of tools, user-friendly dashboards, and displays paired with actuarial analysis that can lead an end-user through a process of discovery. In this webcast a data visualization expert will review the winning entries with the contestants. We'll discuss how the different strengths of these entries can be combined to create a powerful tool for communication and understanding.

Description: Learn about the latest developments in hospital and payer price transparency data. Hear experiences working with the data and attempts to gain meaningful insights for actuarial and other purposes. Discover challenges and workarounds associated with this data, including file size, comparability of prices, duplication of prices, aggregating provider NPIs into meaningful groupings, and missing payer information.

Description: This report describes two methods, an observation-based analysis and an actual to model analysis, to analyze long-term care insurance experience to determine if calendar year trends exist.

Description: After a sustained period of mortality improvement, U.S. population mortality improvement has stagnated in recent years. The presenters will discuss mortality improvement trends in the U.S. population and the causes of death contributing to these trends. U.S. population cause of death trends will be analyzed and compared to trends in the insured population. Mortality rates for major causes of death will be compared between the U.S. population and the insured population. In addition, assumption setting for both older age and later duration mortality as well as mortality improvement will be covered.

Description: This webcast will walk through several statistical methods for imputing race and ethnicity from U.S. datasets, highlighting strengths and weaknesses and evaluating accuracy.

Description: Are you searching for an overview of the SOA Research Institute's Mortality & Longevity Strategic Research Program? Join us for an introduction into studies focusing on the historical U.S. population and insured mortality trends. Two research projects are observed in this webcast, one examining the impact of COVID-19 on mental illness and the impact of mental illness on U.S. Mortality & Longevity. The second study looks into the Group Life COVID-19 Mortality Survey and the high level view of U.S. group term life insurance mortality results during the pandemic. Come explore the research goals and the future for the Mortality & Longevity Strategic Program.

Description: The famous 80/20 rule in data science states that only 20% of your time working with data is spent driving insightful business analytics. The rest of your time is spent trying to query, clean and organize your data. Even with this knowledge, the majority of actuarial training/focus is on the 20 percent. This session takes a different approach, focusing solely on speeding up your work on the other 80 percent. Practical examples will be part of a code walkthrough in R.