Description: Discussion of how to mature value-based contracts between health insurers and provider organizations to improve population health and financial sustainability. Centers around contract parameter consistency, revenue predictability and risk assessment. Intended audience are health plan and ACO actuaries and leaders. Authors are writing from the provider perspective in value-based contracts.

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: Healthcare risk adjustment methodologies have become increasingly complex, largely due to the belief that complexity enhances accuracy. However, a disconnect exists between how healthcare risk is assessed and how payments are adjusted. This article explores the stark difference between measuring the accuracy of a risk assessment model at a member level, and that of a risk adjustment mechanism at the health plan level. I show that a highly simplified approach that does not use diagnosis codes can have similar accuracy on risk adjusted payments to models that do. These findings suggest that accuracy is not a barrier to developing simpler risk adjustment methodologies, which can improve payment accuracy and reduce the financial incentive for coding diagnoses.

Description: This is a brief report that summarizes recent changes in the prevalent medical loss ratio methodologies and also looks at some of the more recent experience of health insurers that filed medical loss ratio reports.

Description: Early in his career, Ehren Nagel, FSA, MAAA, scoured through podcasts and articles about predictive analytics, long suspecting this was a field with potential for him.

Description: In 2018, the Financial Accounting Standards Board (FASB) adopted significant revisions to the U.S. GAAP insurance accounting literature, via Accounting Standards Update (ASU) 2018-12. The title of ASU 2018-12 is “Targeted Improvements to the Accounting for Long-Duration Contracts,” and as a result a common acronym for ASU 2018-12 is LDTI (long-duration targeted improvements).

Description: Yi-Ling Lin, FSA, MAAA, FCA, started the SOA’s Predictive Analytics Certificate Program to keep pace with the impact big data and predictive modeling is having on the health care industry

Description: In 2018, the Financial Accounting Standards Board (FASB) adopted significant revisions to the U.S. GAAP insurance accounting literature, via Accounting Standards Update (ASU) 2018-12. The title of ASU 2018-12 is “Targeted Improvements to the Accounting for Long-Duration Contracts,” and as a result, a common acronym for ASU 2018-12 is LDTI (long-duration targeted improvements).

Description: There are many ways to actively utilize BE approaches – and implementing these important tools can help insurers in many ways.

Description: Social Insurance & Public Finance Section council members provide a recap of sessions from the 2021 SOA Health Meeting, with a focus on sessions covering Medicare, Medicaid, the ACA, and public policy. The authors include a description of SIPF Section-sponsored sections, including a session on the ACA and a session on CMS's Direct Contracting Model.