Description: The proposed session will introduce Outcome Based Risk Sharing Arrangements (“OBRSA”) between health insurance payers (“payers”, including insurance companies, health plans, sponsored employers, and government programs) and pharmaceutical manufacturers (“pharma”), and it’s intended to meet the needs of actuaries who focus on pharmacy benefits and risk sharing arrangements. The covered content will include (1) the background of OBRSAs, definitions, stakeholders, and OBRSA’s role in shifting the system from volume-based toward value-based; (2) conflicting perspectives about OBRSAs between payers and pharma (cultural and methodological); (3) identification of incentive gaps between payers and pharma, and incentive alignment between them; (4) barriers to implement OBRSAs; (5) limitations and considerations of OBRSA implementation; and (5) hypothetic OBRSA examples.

Description: Can we improve upon traditional methods of risk measurement and risk selection? Panelists discuss potential applications of predictive modeling, including individual underwriting, group rating and provider reimbursement. They focus on ways in which predictive modeling can be used to improve risk selection, experience rating and provider reimbursement. A session at the Health/Pension Spring Meeting held in New Orleans, Louisiana June 15-17, 2005. From the Record of the Society of Actuaries, Vol. 31, No. 2.

Description: This article provides information on how to navigate the Internet's World Wide Web and tap into resources of interest to actuaries.

Description: This article delves into a new line of statistical thinking of the author, that may be useful for product development actuaries. The key concept is how product design can produce products that diversify quickly, meaning that the company can be confident of a profitable product line, based on fewer sales than might be true for other designs.

Description: SOA Product Development Section Contest Winning Article. Contest was to provide a creative article on future technology for the life insurance industry.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: Technology has streamlined countless processes in our daily lives, and insurance is no stranger to this transformation. Technology can make insurance simpler and more personal for consumers, and can enable actuaries to better analyze unstructured data, make good decisions, create new products, and find channels to enhance profitability, provided they can tame the flood of information pouring in from across the digital ecosystem.

Description: The article focuses on the use of predictive analytics in the development of experience studies, pros and cons of using predictive analytics versus traditional techniques, and the implications for setting assumptions and improving profitability.

Description: Society of Actuaries research efforts currently in development