Mathematica experts are partnering with the Centers for Medicare & Medicaid Services (CMS) and states to strengthen Medicaid and the Children’s Health Insurance Program (CHIP) while managing the COVID-19 pandemic and opioid epidemic. At this year’s National Association of Medicaid Directors (NAMD) conference from November 9–11, Mathematica experts will be at their virtual booth and available for scheduled meet and greets each day to discuss how we are supporting states as they transform care delivery and quality, modernize analytics and programs, and improve COVID-19 monitoring and after-action planning.
“State Medicaid and CMS staff are working hard to use data to address new demands arising from COVID-19 and the transition to value-based care. This work continues to improve the quality and affordability of health care provided to millions of Medicaid and CHIP beneficiaries,” said Jonathan Morse, senior vice president and managing director of Health Program Improvement. “We look forward to meeting virtually with state Medicaid directors at the NAMD fall conference to discuss how our work with CMS and states can help meet these new challenges and opportunities.”
In close partnership with CMS staff and states, Mathematica has developed a suite of tools and technical assistance that can help states as they assess their needs in the following areas.
Monitor data quality to improve the usefulness of Medicaid data
We have extensive experience reviewing and improving the quality of Medicaid data and have created online data tools in partnership with CMS, such as the DQ (Data Quality) Atlas, which gives users accurate, extensive information on the quality of program data on enrollment, claims, expenditures, and service use.
Manage the COVID-19 pandemic and opioid epidemic and better prepare for future public health crises
Mathematica is improving states’ ability to monitor the impacts of COVID-19 by using Transformed Medicaid Statistical Information System (T-MSIS) data to assess program outcomes and develop metrics to monitor substance use disorders (SUD). We developed the SUD Data Book, which reports on the prevalence of SUD and opioid use disorder, categories of services states provide, and use of services. In other work, we support states to address the opioid epidemic through their 1115 demonstrations, including strategies for providing housing supports and care coordination services under Medicaid.
Identify approaches to design, test, and scale new Medicaid policies in a way that matches state Medicaid objectives with section 1115 demonstration opportunities
Mathematica supports CMS oversight of Medicaid 1115 demonstrations by developing tools and providing technical assistance that help CMS and states implement, monitor, and evaluate section 1115 Medicaid demonstrations.
Measure the performance of Medicaid programs to increase transparency and drive improvement
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We have assisted CMS in developing the Medicaid and CHIP (MAC) Scorecard to increase public transparency of state programs and shed light on variation across states. States can leverage technical assistance from Mathematica to improve their use and understanding of the MAC Scorecard and jump-start program improvement in areas such as state and federal alignment, beneficiary health outcomes, and program administration.
Identify and use quality measures to monitor health outcomes
Mathematica leverages its expertise in health care quality measures to provide technical assistance and analytic support to CMS, states, and state quality partners (including managed care plans and providers) to improve the collection, reporting, and use of quality measures in Medicaid and CHIP. Mathematica also convenes quality improvement learning collaboratives to help states and their quality partners improve performance.
Balance expenditures for and monitor the performance of long-term services and supports (LTSS)
Mathematica helps states track their progress toward the goal of rebalancing their LTSS systems by increasing home and community-based services. We also give stakeholders a better understanding of Medicaid LTSS spending across different service categories and populations and contribute to improving data quality and completeness in annual LTSS reports.