- Modernizing the Medicaid program environment will require investments in data analytics and a greater reliance on meaningful quality measures, says CMS Administrator Seema Verma in a new blog post.
As spending on healthcare in general – and Medicaid in particular – continues to rise, providers and regulators will need to continue to create more effective partnerships around raising quality and cutting costs, Verma stated.
“As program costs have continued to rise, we have failed to deliver a level of transparency and accountability for achieving positive outcomes commiserate with our significant investment,” she wrote.
“But this is finally beginning to change. Over the last several years, CMS has collaborated with states to improve how we collect and use data to modernize and measure the Medicaid and CHIP program.”
“Through strong data and systems, CMS and states can drive toward better health outcomes and improve program integrity, performance, and financial management in Medicaid and CHIP.”
Data will form the foundation of a modern, efficient, and flexible Medicaid ecosystem that can accurately identify opportunities to improve the quality of care.
Verma cited CMS’s work with industry stakeholders to develop two core sets of quality measures that can be used to assess the quality of services for both pediatric and adult Medicaid and CHIP beneficiaries.
“These core sets are tools states can use to monitor and improve the quality of health care provided to Medicaid and CHIP enrollees,” she explained.
However, reporting on these measures is voluntary, and not all states have undertaken the challenge of collecting data on these quality measures.
“CMS recognizes that quality reporting can present a significant administrative burden for both states and providers, and has taken steps to reduce this burden through our Meaningful Measures initiative,” Verma said.
“In the future, we hope to leverage existing and more automated data reporting systems to generate these Medicaid measures on behalf of states, thereby reducing reporting burden while also improving data consistency, comparability, and comprehensiveness.”
CMS hopes to increase the number of states reporting on a uniform group of measures that may help to improve the quality of care for some of the nation’s most vulnerable beneficiaries. Collecting more data through quality measures is a key first step for fostering transparency in pricing, outcomes, and performance.
“Ultimately, this move toward greater transparency will start an important conversation about how and when states should be held accountable for the outcomes their programs,” Verma asserted.
CMS is helping to accelerate the integration of data analytics into quality assessments by offering states the ability to share their data through the Transformed Medicaid Statistical Information System (T-MSIS), an updated method of gathering datasets from state-level programs.
“T-MSIS modernizes and enhances the way states submit operational data about beneficiaries, providers, claims, and encounters,” said Verma. “It is the foundation of a national analytic data infrastructure to support programmatic and policy improvements and program integrity efforts and will help advance reporting on outcomes. It also enhances the ability to identify potential fraud and improve program efficiency.”
“I am pleased to say that all states, the District of Columbia, and Puerto Rico are now successfully submitting T-MSIS data, marking a significant and exciting milestone in the history of the Medicaid program.”
Streamlining the Medicaid data collection process will allow CMS to take the next steps towards analyzing quality data on a continuous basis, she added.
“CMS’ ongoing goal is to use advanced analytics and other innovative solutions to both improve T-MSIS data and maximize its potential for performance measurement, health care quality improvement, and program integrity, all while reducing state reporting burden.”
“I appreciate our continued partnership with states. Programs as important as Medicaid and CHIP require robust, timely, and accurate data in order to ensure the highest financial and program performance, support policy analysis and ongoing improvement, identify potential fraud or waste, and enable data-driven decision making.”