HHS - Risk Adjustment, Payment Modeling, and Validation - MRAS

The Department of Health and Human Services (HHS), in collaboration with the General Services Administration (GSA), is conducting market research to support initiatives related to Medicare Advantage and Prescription Drug Programs. The primary objective of this solicitation is to enhance the risk adjustment, payment modeling, and validation processes for these programs. This initiative aims to improve the accuracy and reliability of payments under Medicare Part C and Part D by analyzing provider data, developing robust risk adjustment models, and ensuring compliance with federal regulations.

The scope of work outlined in the Performance Work Statement (PWS) includes a comprehensive set of tasks designed to support the Centers for Medicare & Medicaid Services (CMS) in various analytical efforts. Key tasks involve assisting CMS with analyzing encounter data from the Encounter Data Processing System (EDPS), supporting risk score creation and validation, and conducting analyses to assess the impacts of risk adjustment on plan payments. These efforts are critical for maintaining accurate payment systems that reflect true healthcare costs while accommodating policy changes such as those introduced by the Inflation Reduction Act.

Additional responsibilities include aiding CMS in preparing ratebooks for Medicare Advantage (MA) plans, performing monthly validations of plan payments, and providing technical data processing support for improper payment estimates. The contractor will also engage in program management activities across multiple tasks, ensuring timely delivery of progress reports and facilitating project status meetings. Optional tasks include providing support for lawsuits or subpoenas related to these programs.

Overall, this effort is vital for optimizing payment systems within Medicare's complex framework. By leveraging advanced data analysis techniques and maintaining rigorous validation processes, HHS aims to ensure that payments under Parts C and D are both fair and reflective of actual service utilization patterns.