Reimbursement Systems of the Future: Opportunities for Using Artificial Intelligence in Claim Payment
Health insurance reimbursement rules were built for fee for service medicine and have relied on the same data sources and human-generated algorithms for the last 30 years - processed claims, retrospective cost reports, and expert advisory committees. And, while ACOs and bundled payment systems are a step towards value-based care, they still relay on traditional approaches. This session will explain how real-time outcomes, patient satisfaction and productivity data along with machine learning can be used to redesign claims systems' methodology so that they fully align with the value of precision-based medicine. 

Value-Based Reimbursement: Beauty and the Beast
Replacing fee-for-service reimbursement with value-orientated payment models will not occur in a meaningful manner without replacing the legacy data sets in health plans and care delivery organizations. Medical claims and utilization data are transactional and retrospective; social determinants and consumer data are absent. These constraints limit our creativity in designing value-based payments. This session will explore the interdependencies between value-orientated payment methods and data models oriented around measuring value creation.