Description: As actuaries in health care, we spend most of our time focused on reviewing claims, enrollment and clinical data. That information is captured while patients are in health care facilities. Yet most people spend only a small fraction of their time in these facilities. This article explores what types of data are available to actuaries the provide a more holistic view of the member so that a members physical and emotional needs, the social determinants of health can be taken into consideration along with their clinical needs. Two uses cases are presented so actuaries can see how these types of analyses can be leveraged to improve clinical, operational, and financial performance of risk bearing health entities. Understanding the customer (member) not just the patient enables actuaries to provide new insights and values to our stakeholders across a wide range of business and risk applications.

Description: A report analyzing the cost of care for deceased cancer patients over the last six months of life.

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: ACA risk adjustment is intended to "bridge the gap" between allowed rates and actuarial rates. If risk adjustment methodology is not bridging that gap & becomes an additional input to pricing formulae, it is not serving its intended purpose.

Description: Social determinants of health (SDoH) have been a topic of growing interest in recent years, yet consensus about what the phrase represents and how health-related social needs should be studied or addressed by employers, health plans, providers and other stakeholders in the business of health care have been lacking. For many, low-income populations come to mind when considering the topic, yet SDoH include a wide range of factors beyond income. Many types of data are available, yet each presents distinct challenges and opportunities for analysis. In this article, we describe some of the underlying context for considering SDoH, as well as some of the potential data sources to consult and challenges to grapple with on this important topic.

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: View information on the Health Economics Module.

Description: Response to March 2021 Practice Note on ASOP 6