Description: 2021 Life Meeting - Session 5F: Premium Leakage - How Outdated Claims Systems are Losing You Money 8.31.21 Recording

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: Risk adjustment in government regulated health plans has been around for over two decades. Yet the strategies for promoting risk score accuracy haven't varied much during that time. Most health plans, physician groups, and vendors promote chart reviews and/or in-home assessments as the primary vehicle for collecting data not perceived to be present in the routine claims submission and adjudication stream. We know that most organizations trying to coalesce encounter data from multiple sources often fail to ensure that all relevant data is ultimately submitted to CMS or a state Medicaid agency. Crucial data, often with significant financial value, frequently gets lost in the data pipeline, somewhere between the provider's billing system and the health plan and/or its vendors. Because 837-formatted data is difficult to read, it complicates payers and vendor’s abilities to track encounter data so that every service delivered to patients is credited to the applicable risk adjustment formula. It is incumbent upon successful risk-adjusted entities to be able to track encounter data, identify processes and/or vendors which may be mangling or losing data, in order to ensure that risk scores are sufficiently accurate to be compliant with plan sponsor requirements and to ensure appropriate revenue to the health plan or provider group.

Description: The famous 80/20 rule in data science states that only 20% of your time working with data is spent driving insightful business analytics. The rest of your time is spent trying to query, clean and organize your data. Even with this knowledge, the majority of actuarial training/focus is on the 20 percent. This session takes a different approach, focusing solely on speeding up your work on the other 80 percent. Practical examples will be part of a code walkthrough in R.

Description: Actuarial models and modeling processes continue to grow in complexity, accelerated by the changes in U.S. Statutory, U.S. GAAP and IFRS reporting requirements in the past few years. Modeling and valuation teams are expanding their toolkits beyond the traditional vendor-maintained actuarial software and the MS Office suite of tools. Companies have started to use a variety of tools to improve model dev and valuation processes, including: - Data management - Automation and workflow - Reporting and analytics

Description: Stochastic modeling requirements are resulting in more 'run time' and less 'analysis time'. An expensive solution is leveraging cloud infrastructures and robust computing grids. The presenters will explore the use of cluster modeling and present case studies showcasing this automatable and robust technique, which could allow actuaries to recover the time lost to 'run time'. Developing automatable and clustered models requires robust governance practices to ensure credibility of results.

Description: Data science, predictive analytics and AI are certainly the buzzwords these days. They are heavily used and developed in underwriting and marketing but for most actuaries, they might/may as well be science fiction. The presenters will demonstrate how a normal actuary can utilize data science techniques in their daily job function without forming an official data science team within a company. It can be done in a gradual fashion so that normal business is not disrupted and improvements are made over time. The usage of data science techniques will include demonstrations of the following areas: - Regression analysis - Economic scenario generator - Experience study - Data quality checks - Inforce compression for explicit hedging

Description: Actuarial Process Optimization (APO) is a technology-focused methodology for bringing together actuarial and technology teams to critically examine and optimize actuarial processes, specifically targeting processes that are most time consuming and have the highest risk of failure. From claims analytics to valuation and experience analysis, modern technology can help actuaries optimize their time and focus their attention on higher value tasks. In this session, we will explore opportunities for APO in the Health insurance industry and demonstrate how technology can be used to improve the actuarial process using an agile and targeted approach.

Description: 2021 ImpACT Conference - Session 10E: Azure Synapse for Actuaries | Solvency II Use Case 10.28.21 Recording