Description: Is your development team or IT staff growing tired of last-minute requests to include additional functionality? Have you strained to explain challenging actuarial topics to non-actuarial staff for implementation? Do your teams find themselves revisiting deadlines & timelines when building solutions? During this interactive panel discussion, three technologists (two software engineering managers and one data scientist) along with three actuaries will discuss real world problems and approaches using experience from previous projects. Although the challenge of running efficient software teams is not unique to actuarial science, this webcast will discuss best practices on how to organize teams to reduce friction and context switching. Presenters will also explore unique actuarial challenges and concepts including how to address standards on data quality when building software, how to build intuitive software that meets actuarial standards and how test-driven development makes it easier to meet actuarial standards of practice.

Description: Level funded products often target the small group market (2-50) and can result in many manual and tedious processes for underwriting to perform risk assessment. Learn how a carrier used technology to help automate risk assessment without the need for paper medical questionnaires, and exposed a risk engine for broker quoting to enable near real-time of pricing for risk-based products. The approach reduced labor and allowed underwriting to focus solely on fallout cases while also improving pricing consistency. Discuss broader trends in the health market for risk assessment, including new machine learning cost predictions that can be used for automation and better predictions of future costs. Discussion topics will include underwriting guidelines, business rules, risk scores, and machine learning. By attending this session, you will have a better idea of new trends in risk assessment for small groups where no claims experience is available. And, better understand business rules that are common in underwriting for flags for review as well as how risk scores and machine learning can be used during the underwriting process.

Description: Every patient leaving the hospital has personal life-context circumstances that impact their chances of successful recovery and complications can be costly. Complex care management impacts over 50 percent of health care spend, with the admitted commercial population driving 37 percent of spend or $177M per 100,000 lives and the Medicare population driving 53 percent of spend or $600 million per 100,000 lives. The stakes are high, but existing care management solutions are mostly clinical and navigation call centers provide fragmented and outdated patient management systems, and do not address individual life-context. Discharged patients therefore remain underengaged and undercompliant, leading to costly complications. Innovative technology can help enable and integrate systems and existing infrastructure to leverage evidence-based contextualized care that will enhance care management, improve efficiency, and drive a better experience and outcomes for patients. This technology helps codifies life context, dynamically stratifying and engaging members digitally and telephonically helping virtual care teams to be more effective and efficient. In a recent randomized clinical trial, this technology and approach has shown a 50 percent reduction in the total cost of care, cutting the average and total cost of readmission, increasing virtual care team impact and member engagement and trust.

Description: This session series is sponsored by Zelis Claim analytics produces valuable insights about provider cost, quality, and referral patterns. Provider networks can be created around high-value providers to improve clinical outcomes while lowering the cost of care. Programs to improve provider performance and/or incentivize members to choose high-value providers exist, but how do you bring all of this together to achieve desired outcomes? Join us to learn how to leverage provider level analytics to build and optimize a network with high-value providers at the center. Analyze the network for competitiveness and adequacy and demonstrate progress toward network cost saving goals to key stakeholders by modeling claim data for a member population. Finally, ensure the success of your network through an incentive program that shifts utilization to those high performing providers. By attending this session, you will be able to: - Build a realistic provider network with high-value providers at the center. - Evaluate the overall financial impact of network build and optimization efforts. - Learn about an innovative member incentive program.

Description: This document is a Request for Proposal (RFP) issued by the SOA Research Institute, seeking researchers to assess the impact of artificial intelligence on the insurance and healthcare industries in Asia, with specific research objectives, proposal requirements, selection process, submission guidelines, and appendix providing cost estimates.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.

Description: This session will include examples of healthcare claims and market data to be used for educational purposes to highlight trends in the insurance industry. It will also highlight opportunities to enforce existing laws around fraud and abuse, and areas for regulators and legislators to focus to address this growing problem. Finally, it will discuss recent law changes and highlight areas requiring additional regulatory intervention. Expect discussions of recent claim issues and laws in the healthcare market as well as emerging issues in healthcare. The presentation will be beneficial to healthcare professionals working for health insurers, healthcare providers, auditors, regulators and healthcare providers and will also cover professionalism related topics for actuaries.

Description: This session series is sponsored by Zelis Shifting utilization of health services to efficient and high-value providers presents an opportunity to reduce harmful cascades of wasteful spending, ultimately freeing up funds for additional high-value services that will improve quality and member satisfaction. Identifying the right providers to put at the center of networks is challenging for any health care organization. How can you objectively determine which providers are delivering the greatest value when compared to their peers? And once those providers are identified, what’s next? Join Zelis and their partner HealthCorum to review a case study on a shared services organization where they leveraged statewide multi-payer claims data to produce provider level analytics, allowing for transparency into provider practice patterns at a granular level. By attending this session, you will be able to: - Create a fair methodology to benchmark providers. - Develop metrics and scores to identify high-value providers. - Produce actionable data to be used for network optimization strategies.

Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: Discuss various analytics and use cases using payer published reimbursement contract data under federal mandate of Transparency in Coverage. These contract rates are publicly available in machine readable format (MRF) starting July 1, 2022, and refreshed monthly. By attending the session, you will have a better understanding of the state-of-art development and analytics using MRF data, including the technologies used to extract and analyze huge MRF files, validation and limitations of published rates, and their use cases.