Description: Tree models have been found to provide a good fit to group long term disability recovery and mortality rates. This research paper provides an overview of tree models, and details how they have been used for developing these rates.

Description: This session includes a new idea based on dynamic treatment regime work (OWL) and integrating cost into this work. This will enable identifying the best treatment for a patient based on both outcomes and cost. This is novel for actuaries because in previous analysis we have used cost only in the after-analysis, whereas here we use it in the actual analysis and treatment identification. Moreover, this analysis provides a way to consider multiple treatments for a patient (including the no treatment option) and choosing among those multiple treatments, for both outcomes and cost. This session will share the background theory and set up a case study. The case study will parallel what is in the analysis in the book by Ian Duncan 'Predicting Hospital Readmission with Case Management Recommendation.' This analysis will then go further to compare a situation where there are multiple potential case managers. Also, this will potentially explore care pathways and choosing the best care pathway for a patient based on health outcomes and cost combined.

Description: "A crucial importance in forecasting is to be able to distinguish cases when temporary slowdowns in health care utilization are followed by a “rebound” period of higher utilization. Come explore an analysis of a new mathematical model describing the return-of-care process. By means of simulation and case studies using the R programming language, the relationship between the visibility of these effects and the endogenous variance of the utilization time series is explored. After attending this session, you will be able to: Describe the parameters and mathematical form of the model Apply the model to real-world utilization data"

Description: It goes without saying that the analysis of data is a key aspect of actuarial practice, but do traditional actuarial approaches allow us to see the whole picture? Effective data analysis is also key to the identification of health disparities and measuring progress on health equity. Actuaries and others analyzing data for health equity purposes find themselves looking at data differently.

Description: The instructors in this boot camp session will highlight the SOA's work on an updated Medicaid underwriting margin model. This research project includes an excel model, a set of instructions and a paper describing the key components of underwriting margin, including cost of capital and risk margin.

Description: Explore SOA-sponsored research on Social Determinants of Health (SDOH) during the How Does Where You Live Impact Your Health webcast. Dive into SDOH data and modeling that will focus on cluster analysis. This will help determine the overall impact of your area's affect on your health and life. This webcast also covers an overview of the existing SDOH-related programs that may affect or intersect with health plan or provider SDOH initiatives. Discover the importance of the place you live and future impact of your overall health.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.

Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: Discuss various analytics and use cases using payer published reimbursement contract data under federal mandate of Transparency in Coverage. These contract rates are publicly available in machine readable format (MRF) starting July 1, 2022, and refreshed monthly. By attending the session, you will have a better understanding of the state-of-art development and analytics using MRF data, including the technologies used to extract and analyze huge MRF files, validation and limitations of published rates, and their use cases.

Description: "Discuss research conducted at the Cleveland Clinic to understand levels of anxiety and depression across Northeast Ohio. Specifically, learn how advanced analytical techniques were utilized with social media data from Twitter and Google to estimate the need for psychological support by geography and overtime. The panel will go further to demonstrate how natural language processing (NLP) and machine learning could be used to make operational decisions at a leading health care provider."