Description: Read the October 2019 issue of Health Watch, published by the Health Section. Practical information for actuaries, articles impact sections, section activities. This is the first digital-only issue of the newsletter.

Description: Read the February 2020 issue of Health Watch, published by the Health Section. Practical information for actuaries, articles impact sections, section activities.

Description: This article provides a brief overview of the current state of machine learning (ML) and artificial intelligence (AI) as they apply to actuarial science, including discussion around the integration of actuarial judgment with ML and AI. It concludes with an example of explainable ML through a python tool known as SHAP (SHapley Additive exPlanations), which is able to explain the key drivers behind individual ML or AI predictions.

Description: Read the October 2019 issues of Health Watch, published by the Health Section. Practical information for actuaries, articles impact sections, section activities. This is the second digital-only issue of the newsletter.

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: According to the Actuarial Standards Board’s Actuarial Standard of Practice No. 49 (ASOP 49), actuarially sound Medicaid managed care capitation rates will include a provision for underwriting gain in order to provide compensation for the risks assumed by an MCO. However, there is no generally accepted method for quantifying underwriting gain in managed Medicaid capitation rates. This article discusses a new model developed to address this void and calculate underwriting gain. The model was developed by researching existing financial literature and performing a statistical analysis of industry data to build out a framework that can be leveraged to estimate underwriting gain.

Description: In this article, the author discusses the considerations and advantages of implementing an integrated enterprise risk management program for a health insurance company, and presents a summary of Aetna's experience with ERM as a case study.

Description: On average, contracts receiving their first star rating receive 3.20 stars, compared to existing or established contracts receiving 3.90 stars on average. This 0.70 disparity in quality ratings creates significant hardship on new contracts when this lower star rating decreases their payments in the following calendar year. This article explores the disparity in Medicare Advantage Star Ratings between contracts receiving their first star ratings (“New” contracts) and existing contracts, including: 1. Understanding what happens to Medicare Advantage Payments when contracts receive lower star ratings? – What is the Star Rating cliff and why does it matter to new contracts? 2. Explaining when a contract receives their first star rating and how much enrollment this requires – When does the Star Rating cliff occur? 3. Noting which specific star measures “New” contracts struggle with, including those contracts under large parent organizations, contracts with rapid growth, and all other new contracts. – How can my contract avoid the Star Rating cliff?

Description: This article discusses the advantages, logistical concerns, and pricing formulas of implementing a TNHP, in which members pay less for treatment from providers who meet higher quality and cost-effectiveness standards.

Description: SOA interview with David Axene