Description: Identifying and submitting all appropriate ICD-9 diagnosis codes to CMS will result in a higher risk score for the member and increased payments to Medicare Advantage plans. Milliman's HCC prevalence study illustrates the significant variations in HCC prevalence rates by age/gender, geography, and population type and will assist plans in benchmarking the effectiveness of their own diagnosis code capture efforts.

Description: Mindful data visualizations show the end users the end way in how to analyze and interpret your data. More importantly, they can then use this data they see to drive decisions and modeling going forward.

Description: This paper is a proof of a conjecture that appeared in a letter to the Editor of The Actuary. From the Actuarial Research Clearing House 1991 Vol.

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

Description: Presented at May 1985 Spring Meeting. This session discussed: What measures should be used in setting objectives and evaluating performance for companies and product lines, What variations are appropriate for stock and mutual companies and for United States and Canadian companies.

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.