*Aparna Higgins (Ananya Health Innovations) Aparna Higgins, MA, is a Policy Fellow at the Duke-Margolis Center for Health Policy where she is engaged in policy research on the next generation of performance measurement and value-based payment. At the Margolis Center, she is leading a collaborative effort to implement patient-centered outcomes measurement for use in alternative payment models (APMs) and public reporting. She also participates in the Center’s work on implementing reliable methods for collecting real-world evidence, including evidence related to clinical and patient-driven outcomes that are relevant to quality improvement.
Ms. Higgins is also Founder and CEO of Ananya Health Innovations, Inc., where she provides strategic advisory services in the design and implementation of value-based care models. Her role includes serving as a strategic advisor to the Centers for Medicare and Medicaid Services (CMS) on accelerating payment reform. She currently serves as a member of the National Steering Committee and chairs the Policy Committee for an ongoing effort focused on wide-scale adoption of patient-reported outcome measures in the US.
Previously, Ms. Higgins was Senior Vice President, Private Market Innovations and Center for Policy and Research at America’s Health Insurance Plans (AHIP), where she led organizational efforts in payment and delivery system reform, performance measurement, and healthcare analytics. Her experience spans several large-scale strategic initiatives focused on measurement, including leading and establishing (in partnership with CMS) the Core Quality Measures Collaborative, a multi-stakeholder effort to align and standardize measures across public and private sectors; leading a multi-plan effort to aggregate data across health plans for physician performance measurement using a common measure set and measurement methods; and co-leading the design of the Medicare Hospital Value-based Purchasing program and Report to Congress which included the selection of measures and development of a performance assessment model.