Description: "Explore a general introduction to the opportunity of applying a relatively newer area in machine learning called uplift modeling, which has been successfully used in retail (Wayfair etc). The concepts are parallel to the intervention programs in health care, where we are interested in measuring the treatment effects and ultimately directing the right members to the most effective programs, driving the highest value for the programs both from a financial and health outcomes perspective. Uplift modeling can also be viewed in context of causal modeling where we are interested in assigning cause to a treatment relative to a member not receiving the treatment. Check out an introduction on the concept, seehow it relates and builds on existing work, and use a demo to showcase the potential of integrating this ML approach to current work."

Description: Review of a report by Alan Mills introducing Complexity Science, a discipline which could help actuaries to model and manage complex systems, such as the health care system.

Description: 1996 Valuation Actuary Symposium Proceedings, Session 11, discusses health financial projections and projection modeling in general.

Description: This interactive session provides an introduction to behavioral economics, including groups identifying areas where behavioral economics could be applied in actuarial practice. Experience a practical application workshop using behavioral economics for direct sale products. Break out into small groups and develop an outline of a BE based sales program for a product of your choosing to be sold over the internet. Gain feedback and take part in a discussion. By attending the session, you will: - Understand the basic concepts of behavioral economics. - Have some ideas of how it can be applied to actuarial practice. - Learn how to design a product using BE and how to design an experiment to test the effectiveness of an application of BE.

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: This article discusses the advantages, logistical concerns, and pricing formulas of implementing a TNHP, in which members pay less for treatment from providers who meet higher quality and cost-effectiveness standards.

Description: Chapter 1 presents the background to the current study, followed by the methodology used, and a summary of the findings of the study. From Group Medical Insurance Large Claims Database Collection and Analysis, M-HB97-1.

Description: Attend if you are an organization interested in utilizing various kinds of client data to improve the whole insurance sales process, and to develop new applications. Interested parties may include distribution sales force, underwriting, claims, actuarial and finance departments within a typical insurance company, online distribution partners, health care providers and other consulting service providers. The research looks into various use cases, which are typically main issues in modeling in the insurance industry. The research also helps benchmark performance using different languages that may serve as a good reference when best to use a certain language to enhance the development cycle.

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."

Description: The focus of the webcast on Modeling Long–Term Medical Trends for Valuation Purposes was a discussion of the underlying methodology of the model, a walk through of the actual model, and a review of the considerations for its practical usage by actuaries. The running time of this video is 1 hour and 3 minutes. It is a presentation of slides without audio.