Description: This session explores the far-reaching changes to how clinical data will be sourced, processed and consumed in many payer use cases including risk adjustment, quality measurement, care management, claims adjudication, prior authorizations, and other payer functions. Robust, interoperable data exchange is a prerequisite for value-based care. Clinical data will be increasingly accessible to augment administrative (claims) data via standardized Fast Health Interoperability Resources (FHIR, pronounced 'fire'), at a fraction of the cost of a accessing a traditional medical record and in real-time. On May 1, 2020, HHS issued a final rule implementing interoperability and the patient access provisions of the 21st Century Cures Act of 2016, although enforcement has been delayed into 2021 because of the COVID-19 pandemic. The new regulations promote, “HHS’s vision and strategy for achieving a health information ecosystem within which all individuals, their personal representatives, their health care providers, and their payers are able to send, receive, find, and use electronic health information in a manner that is appropriate, secure, timely, and reliable to support the health and wellness of individuals through informed, shared decision-making, as well as to support consumer choice of payers and providers.”Once enforcement begins, CMS and the Office of the National Coordinator for Health Information Technology (ONC), have the authority to mandate adoption of interoperability requirements, and also penalize payers and providers for non-compliance or the delay and withholding of data.This ‘digital transformation’ of the clinical data ecosystem has far-reaching implications for enabling technologies including Natural Language Processing (NLP) and entire segments of services and vendors. It will eliminate many departmental barriers, duplication and error sources for health plans and impact every department and the underlying economics of delivering and managing care.

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: As the insurance industry continues to evolve due to a pandemic and rapidly changing economic and regulatory conditions, the role of data scientists and actuaries has become increasingly important. In an interview with the Atidot data science and actuarial team, we discuss what it is like to work at an InsurTech, how data scientists and actuaries can collaborate, and look at some concrete technical examples of where the innovation is having an impact. This article explores what collaboration can look like and how the role of data science and actuary may evolve in the InsurTech industry in the future.

Description: This article is a brief overview of what digital health is, how it is regulated, and who some of the big unicorns are.

Description: Navigate complexities of retirement financing considering longevity's impact. Use these tools to help differentiate longevity from life expectancy and avoid outliving financial resources.

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: Data is an essential component of financial analysis. In this session, the presenters will discuss data governance/management framework and how it can be applied to US GAAP LDTI and VM-51 regulations. This session will also discuss the important relationship between actuaries and IT and how they can work together towards best practices for extracting, managing and using data needed for various actuarial models. Real life case studies relevant for valuation actuaries (e.g. data needs for LDTI and VM-51) will also be presented and examined, highlighting best practices as well as challenges and pitfalls for setting up and governing data processes along with areas for where good communication and strong relationships are important to success.

Description: How the speed of change is accelerating and how we could react to this as a profession.

Description: Big data, predictive analytics, machine learning and AI will likely transform the insurance market and the actuarial profession. The actuarial profession is seeing changes many markets, including health and property and casualty. This article describes these trends and provides an introduction into what companies and the Society of Actuaries (SOA) are doing to adapt and capitalize on these trends.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.