Description: While there are many approaches currently being taken to transform health care, to be successful, we know that leading and planning for quality improvement is a science. Data is the common denominator as healthcare organizations establish best-practices, and ultimately overcome unintended variation through strong analytic systems. Health care leaders require specialized data analysis education and training to hone their skills in understanding and managing clinical variation. The problem with unexplained variation in healthcare is that it negatively impacts clinical outcomes, increases the cost of care, and diminishes value for patients. In this session, Dr. Ted James (BIDMC and Harvard Medical School Faculty) will explain how actuaries can offer practical solutions that provide insights into variations in clinical practice that cannot be explained by differences in medical conditions or patient preferences.

Description: The MACRA/QPP Provider Revenue Model is designed to provide an estimate of the revenue impact of the QPP (MIPS, AAPM) on a provider group or ACO, based on the required inputs and scenarios.

Description: The MACRA/QPP Payer Revenue Model is designed to provide Health Plans an estimate of the expected claim cost increase/decrease due to MACRA.

Description: Early in his career, Ehren Nagel, FSA, MAAA, scoured through podcasts and articles about predictive analytics, long suspecting this was a field with potential for him.

Description: In the current value-based care marketplace, there are various reimbursement models that tie payments for care delivery to the quality of the care provided. The purpose is clear – change reimbursement to focus on value by rewarding better outcomes and lower spending. However, implementation it is complex, and many challenges emerge during this transition for both providers and payers.Providers often lack sophisticated actuarial capabilities or clear understanding of the connection between finance and clinical operations. For these reasons, they enter risk arrangements without knowing how to strategically manage and mitigate risks and fully transfer the reimbursement changes into clinical decisions. For payers, a truly viable value-based payment model that rewards the most valuable providers needs a multidisciplinary approach and a solid financial model. Such a model also requires transparency and a clear transitional road map for providers to encourage participation and collaboration. In this session, we will discuss lessons learned through case studies of working with both providers and payers on value-based care issues. We will illustrate the current state of the complex financial structures by presenting examples of value-based financial models, feasibility analyses, and strategies to design a payment model beneficial to both providers and payers. We will also explore the clinical collaboration necessary to make it all work, as well as present some best practice strategies to facilitate strong payer-provider collaboration.

Description: Yi-Ling Lin, FSA, MAAA, FCA, started the SOA’s Predictive Analytics Certificate Program to keep pace with the impact big data and predictive modeling is having on the health care industry

Description: Discussion and Opinion on how randomness affects measurement of provider contracting risk-sharing agreements

Description: The SOA is pleased to make available a research report providing insight and considerations for the actuarial profession in assessing the potential risk and opportunities of MACRA to both provider and payer organizations.

Description: The SOA is pleased to make available a research report providing insight and considerations for the actuarial profession in assessing the potential risk and opportunities of MACRA to both provider and payer organizations.

Description: What is the difference between a Single-Payer and Universal Health Care System, and how could the U.S. implement a system that would reduce the growth of medical costs while increasing quality.