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

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: Any prudent organization that is obligated to cover health claims will consider the risk that those medical claims vastly exceed expectations. This is true for an employer self-funding employee health benefits, a health system contracted with two-way risk (e.g., Accountable Care Organizations ACOs), and a small or mid-sized health insurance company. Without protection, these risk bearers can incur ruinous losses. Interestingly, the forms of insurance sold to cover such large medical claims, although quite similar, sometimes go by different names depending upon the buyer. • Employer Stop-loss (ESL): self-funded employers who want protection against large unanticipated claims • Provider Excess (PXS): at-risk health systems who have taken delegated risk from a public or private payer and desire protection against large unanticipated claims • Medical Excess/HMO Reinsurance (HMO Re): health insurers (including HMOs) who desire protection against large unanticipated claims The concepts we discuss in this article apply to all three categories of large claim risk.

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: Review of a report by Alan Mills introducing Complexity Science, a discipline which could help actuaries to model and manage complex systems, such as the health care system.

Description: Article explores why many integrated delivery systems are struggling and what actions they need to take to succeed.

Description: This article is a brief overview of what digital health is, how it is regulated, and who some of the big unicorns are.