Description: This session will present three utilized underwriting models that can be used for mid-size employer group medical renewals. Key assumptions will be discussed including a significant focus on the stop loss risk since that is the major insured risk.

Description: Actuarial Roles in Health

Description: Review a recently completed research project for a multi-stakeholder data consortium on social determinants of health (SDOH). In this project, claims, external SDOH data, geospatial analysis, and machine learning models were used to examine several questions: How to identify SDOH vulnerabilities? How sensitive are the findings with respect to provider coding pattern variations? How much variability in cost can be explained by SDOH vs. morbidity? What are the key risk drivers revealed by machine learning models? The session will review the methodology and main findings from this project.

Description: Focus on how innovative health care organizations develop their value proposition for their intended buyers. Presenters will share information about their specific solution and the methods used to derive credible savings estimates, ROI, and performance guarantees. Learn about data utilized, the methods deployed, advantages, disadvantages, and buyers' reaction. This session is expected to be technical, highly informative, and interactive with audience members.

Description: After three decades of relatively stable overall inflation trends, the United States has seen significant increases over the last twelve months. What could this mean for inflation in the medical sector? Explore past patterns between the two phenomena, and what drivers stakeholders can monitor to be best aware of what could be coming.

Description: Learn about key topics affecting actuaries working in the dental insurance space! The session will include valuable information for health actuaries looking to better understand how dental fits into Medicaid, Medicare, commercial, and ACA markets.

Description: In this session, you will learn about key cost drivers in pharmacy trends, including but not limited to: New high-cost drugs, including gene therapies, that treat rare and/or expensive conditions such as spinal muscular atrophy (SMA), inherited retinal disease, hemophilia A and B, Duchenne muscular dystrophy (DMD), sickle cell anemia and cerebral adrenoleukodystrophy (CALD) Other cost drivers in the prescription drug category, including the emergence of GLP-1s, digital therapeutics, targeted immunomodulators, accelerated approval drugs and expanded indications The implications of the end of the COVID-19 Public Health Emergency (PHE) on the costs of COVID-19 vaccines, testing and treatment claims Downward influences on pharmacy costs, such as the availability of new generic drugs and biosimilars Emerging trends in pharmacy benefits manager (PBM) contracting, the initial portion of this discussion will be led by a pharmacist and former state pharmacy director.

Description: As the healthcare industry becomes increasingly complex, actuaries are under pressure to analyze vast amounts of data and make informed decisions quickly. Artificial intelligence (AI) technologies like ChatGPT offer a promising solution, providing powerful tools for data analysis and natural language processing. Come explore the use of ChatGPT in actuarial analysis, focusing on healthcare applications. Begin with an introduction to ChatGPT and how it works, including its ability to understand and generate natural language responses. Then expect a discussion on the potential benefits of using ChatGPT in healthcare actuarial analysis, including improved accuracy, efficiency, and scalability. Through case studies and examples, we will demonstrate how ChatGPT can be used to analyze complex healthcare data sets, including electronic health records (EHRs), claims data, and patient surveys. We will also discuss how ChatGPT can be integrated with other AI tools, such as predictive modeling and machine learning, to enhance actuarial analysis. Finally, learn about some of the potential challenges and limitations of using ChatGPT in actuarial analysis, such as data privacy concerns and the need for human oversight. There will also be guidance on best practices for using ChatGPT in a healthcare actuarial context, including data preparation, model training, and interpretability.

Description: In this session, we will provide examples and highlight real-world analytics that have been done to compare providers of tertiary and quaternary (T/Q) services (i.e., complex and potentially rare conditions). We also will address the need for analytics like this, who the potential audiences are, the data necessary to complete an analysis, and we will walk through actual case studies.

Description: The presenters will discuss current focuses in behavioral healthcare (MH/SUD). This may include cost and utilization trends, access to care, modalities of care (e.g., telehealth, app-based solutions, etc.), and other hot topics. The attendees will hear perspectives related to the overall landscape of behavioral healthcare in the US and how that impacts actuaries.