Description: Risk adjustment in government regulated health plans has been around for over two decades. Yet the strategies for promoting risk score accuracy haven't varied much during that time. Most health plans, physician groups, and vendors promote chart reviews and/or in-home assessments as the primary vehicle for collecting data not perceived to be present in the routine claims submission and adjudication stream. We know that most organizations trying to coalesce encounter data from multiple sources often fail to ensure that all relevant data is ultimately submitted to CMS or a state Medicaid agency. Crucial data, often with significant financial value, frequently gets lost in the data pipeline, somewhere between the provider's billing system and the health plan and/or its vendors. Because 837-formatted data is difficult to read, it complicates payers and vendor’s abilities to track encounter data so that every service delivered to patients is credited to the applicable risk adjustment formula. It is incumbent upon successful risk-adjusted entities to be able to track encounter data, identify processes and/or vendors which may be mangling or losing data, in order to ensure that risk scores are sufficiently accurate to be compliant with plan sponsor requirements and to ensure appropriate revenue to the health plan or provider group.

Description: 2021 Life Meeting - Session 9A: ASOP 56 - Modeling Begins in the Middle: Don't Forget the Beginning and the End 9.1.21 Recording

Description: A preview of the details and content of the new Certificate in Climate Risk to be offered by the SOA beginning in early 2023.

Description: Watch as presenters highlight the SOA's work on an updated Medicaid underwriting margin model. This research project includes the model along with a set of instructions and a paper describing the key components of underwriting margin, including cost of capital and risk margin. The model was created as a tool for Medicaid actuaries representing both MCO and state principals to determine appropriate underwriting margin components within Medicaid managed care rates. In addition, explore a brief description of the motivation for an underlying theory behind the model. Walk through different model inputs and run through some realistic scenarios that Medicaid actuaries may encounter in states where they operate.

Description: Actuarial transformation is a growing trend with clear impacts on data, software, analytics and reporting. So how does modeling fit in? The presenters will explore how the actuarial modeling function fits into a transformed business, starting with the questions below in a case study discussion to allow attendees to learn from peers.

Description: Stochastic modeling requirements are resulting in more 'run time' and less 'analysis time'. An expensive solution is leveraging cloud infrastructures and robust computing grids. The presenters will explore the use of cluster modeling and present case studies showcasing this automatable and robust technique, which could allow actuaries to recover the time lost to 'run time'. Developing automatable and clustered models requires robust governance practices to ensure credibility of results.

Description: Back in the day, when data was scarce and computers were slow, actuaries were forced to use simple methods to account for risk. By far, the most common method was to add a margin, usually 5% to a “best estimate” calculation. Remarkedly, this method still works quite well in the aggregate. The problem is that, in many cases, decisions today require a more in-depth analysis. For example, how big a risk is a health plan really taking if it lowers its premiums by 10% to attract more members? This session will discuss techniques for measuring risk in today’s environment. Speakers will also share the results from the 5/50 research project, which forms the foundation for the techniques.

Description: Electronic Health Records are here to stay. Take a deep dive into the world of electronic health records and how the industry is poised to utilize this new form of digital medical data to transform the way policies are underwritten and ultimately, transforming the client experience. Listen to industry experts speak about what they are doing to use this data most effectively and how this ultimately develops into ground-breaking solutions for the industry.

Description: The Society of Actuaries Retirement Section Research Committee is seeking researchers to explore new modeling approaches for creating pension plan turnover tables.