Description: A look at the near future and far future of various elements of Actuarial Models as defined through ASOP 51. What is driving the complexity for inputs, calculations, and outputs. Howe will actuaries handle these challenge?

Description: In this article, we discuss the future of wearable technology in life insurance. Evidence from recent research shows that low levels of physical activity, as measured by steps per day indicate much higher mortality risk while higher levels of activity correspond with lower risk. The article shares insights of how insurers can use wearables to innovate by improving the customer journey, expanding insurability, engaging customers, promoting healthy lifestyles and improving risk assessment. Lastly, we discuss the challenges and considerations when using new data and technology to ensure success.

Description: The barrier between humans and machines continues to blur, but curiously, this may have been prediction thousands of years ago in ancient myths. This article looks to how some of the early legends are becoming manifest in modern technology, particularly in the area of elder care. From automation, to humanoid assistants, to mind clones will the age of technology bring a new utopia?

Description: Technology is transforming the retirement space and more changes are expected in the future. Join a panel of experts to discuss what are the opportunities, trends and challenges associated with new technologies in the retirement landscape and how it is expected to impact consumers, if we can enable their successful integration.

Description: You really can have it all: readily available and relevant information derived from consistent and understood data. Getting at the Truth requires a good datawarehouse design and an appropriate business data model. Add a powerful and flexible Web–based analytical interface to get at the data and success in the pursuit of Truth will happen.

Description: Many new and innovative companies are leveraging technology to improve the effectiveness of the care provided to patients. They are employing better tools to identify patients who can benefit from specific programs that best meet the patient's need. They are also dramatically increasing the use of these programs by guiding plan members through the maze of offerings to match them with the programs that will be most beneficial to them. Employers are making these third party programs available to their members and Medicare Plans are using these new tools to identify emerging health risks for early intervention and more accurate risk scoring. This session will explore some examples of these programs, how they are being effectively integrated into the operations of health plans and how the results of these programs are being measured.The speakers will be:Raj Behal, MD, MPH,Chief Quality Officer, One Medical. Raj leads the quality and safety, value and innovation, and data science teams at One Medical. One Medical is changing the way primary care is delivered with a concierge approach with technology seamlessly woven into their offering. This includes booking appointments on line, virtual face to face care, accessible medical records and health reminders.Mylea Charval,Ph.D., CEO and Founder, Savonix. Savonix is a next generation cognitive assessment platform that brings clinical, evidence-based, and all mobile digital assessment of cognitive and emotional function. These capabilities are critical for early identification of the onset of dementia and for the proper risk assessment of seniors enrolled in Medicare Advantage Plans.Ed Cymerys, FSA, Advisor. Ed will serve as moderator. Over the last six years Ed has served as an advisor to a number of early stage technology companies looking to improve the way health benefits are being delivered.Dave Sotelo, FSA, MAAA, Actuarial Manager, Collective Health, Inc. Collective Health is an integrated solution that allows self-funded employers to administer their health plans, control costs, and take care of their people -- all in one place. They have effectively integrated more than 70 distinct third party solutions for self-funded employers and are rigorously assessing the impact of these programs

Description: When it comes to record linkage, the challenge is bringing together the right information from several sources. Here's how to make things match up.

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: Research report sponsored by SOA to model and compare projected costs of different proposals for a Medicare prescription drug coverage plan. 3 types of costs are studied: net benefit cost estimates per member per month, continuance table data, and projected annual costs to the government over 10 years for two selected plan designs.