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: This report describes two methods, an observation-based analysis and an actual to model analysis, to analyze long-term care insurance experience to determine if calendar year trends exist.

Description: This session will discuss: • What is social insurance and advantages of financing LTSS that way • Design decision points for an LTSS program • Existing examples of programs in the US and Abroad • Challenges and differences in pricing state-based LTSS financial reform.

Description: This report describes two methods, an observation-based analysis and an actual to model analysis, to analyze long-term care insurance experience to determine if calendar year trends exist.

Description: Health care has changed rapidly over the past couple of years. The pandemic has shifted consumer behavior in how and where they receive health care as well as consumer attitudes toward health care. Payers continue to design innovative solutions in responses to their patient’s needs and expectations. These changes in consumer behaviors and the responses by payers are expected to impact both health care cost and utilization. Discuss changes in health care that have emerged due to the pandemic and how they are expected to influence actuarial assumptions. Explore epidemiological models commonly used in the industry, the considerations when using these models, as well as the challenges with regards to gathering and interpreting relevant experience data. By attending this session, you will be able to: Identify shifts in consumer behavior that have emerged from the pandemic and describe how payers are responding to new patient expectations. Discuss how these post-pandemic changes by consumers and payers influence medical spending. Determine which actuarial assumptions are impacted and how and if the impact is expected to be temporary or permanent. Discuss considerations taken by actuaries and challenges faced when modelling actuarial assumptions post pandemic.

Description: The South African life insurance industry contains the largest life insurance market in Africa, it is highly sophisticated and highly regulated. In the years 2020 and2021, the industry suffered significant mortality losses due toCovid-19. What can we learn from this experience in South Africa?

Description: The time has arrived for ASU 2018-12, otherwise known as Long-Duration Targeted Improvements (LDTI). For health insurance products, the ASU will require considerable efforts to make the necessary changes to valuation systems, procedures, assumptions, and/or methodologies in order to be in compliance. This session is designed to cover LDTI implications specific to carriers of long-term care and supplemental health products, including changes to how attained age rated products will be approached, allocating and discounting the claim liability (IBNR), and how the treatment of Profits Followed by Losses (PFBL) will evolve under LDTI. By attending this session, you will be able to: • Understand LDTI’s key impacts on long-duration health insurance products. • Recognize the treatment of attained age rated products under LDTI. • Comprehend the requirements of allocating the claim liability to cohorts. • Grasp the requirements pertaining to the discounting of the claim liability. • Understand how PFBL will evolve under the new standard.

Description: Data is at the core of the actuaries' role within companies, but how can actuaries translate data insights into informed and actionable decision making? The key is communicating data insights into a language that transcends analysis and enables real-time decisions that can provide an advantage to your management team. Learn an approach to choosing a tool or medium for your data insights, questions to ask yourself to better understand the communication necessary, and perspectives on how actuaries can take a larger role in actionable decisions within the industry. Understand availability, quality, and practical application of data sources health actuaries can access easily, how that data looks, approaches to transforming data into decisions, how it enriches administrative and claims data, and applications to pricing and reserving. Finally, discuss implications of ASOP 23, ASOP 41, and ASOP 56 as it relates to this topic. By attending this session, you will be able to: - Create an action plan on how to transform data into messaging for your leaders. - Use real experiences to formulate a strategy to expand the actuaries' role in informing decisions within the industry, including examples, to illustrate how data can benefit financials of health coverages. - Understand the application of ASOP 23 (Data), ASOP 41 (Communication), and ASOP 56 (Modeling) as it relates to turning data into decisions. - Be knowledgeable about new sources of morbidity for medical care and LTC and how to acquire and apply this information in actuarial models.

Description: Regression to the mean (RTTM) is inflating your health care intervention evaluations if you are not carefully managing it's omnipresent and significant impact RTTM is the statistical phenomenon which arises when comparing sequential data points when an initial observation is extreme or an outlier, and states that with no other intervention, future observations will be closer to the average. Members who had high costs last year will, on average, have lower costs this year, even in the absence of any intervention or clinical program, simply by 'regressing' to the mean. This means that if your clinical programs are simply targeting members who had adverse medical experience last year, you’re targeting the wrong people. And if your savings methodologies are simply last year’s costs minus this year’s costs, the savings are inflated. By attending this session, you will be able to identify situations where RTTM will be a significant factor, how to eliminate it's impact when performing retrospective evaluations, how to identify prospects for clinical intervention with RTTM in mind, and more.