CMS quality measures are collected and reported with the goal of creating patient care that is effective, safe, patient-centered, equitable, and timely. CMS has recently begun to link these measures to value-based incentive payments for providers. Therefore, it is important to assess the impact of the measures. CMS currently produces a triennial impact report with an assessment of the measures. GNS will now substantially advance the process by using REFS™, its big data analytics platform, and cloud-based supercomputing to analyze the causal relationships between measures and outcomes.
GNS will link data generated by provider reports of quality measures with real world patient outcome data. Using a high-throughput, data-driven computational approach, REFS™ will perform trillions of calculations to identify causal and predictive relationships between measures and outcomes, explore links between measures, define important patient subpopulations, and identify gaps where new measures are needed to determine the quality of patient care.
"This collaboration is a perfect example of how REFS™ can use real world outcomes data to determine how to provide high quality healthcare across conditions, settings, and populations," said Carol McCall, Chief Strategy Officer at GNS. "Evaluating these quality measures is a significant challenge, given the size and complexity of the data. However, this is a very important challenge. REFS™ can support CMS by addressing this complexity, in order to create quality standards that have a meaningful impact on patient care."
About GNS Healthcare
GNS Healthcare is a big data analytics company that has developed a scalable approach for the discovery of what works in healthcare, and for whom. Our analytics solutions are being applied across the healthcare industry: from pharmaceutical and biotechnology companies, health plans and hospitals, to integrated delivery systems, pharmacy benefits managers, and accountable care organizations. REFS™ is GNS Healthcare's scalable, supercomputer-enabled machine learning framework for discovering new knowledge directly from data. REFS™ automates the discovery and extraction of causal network models from observational data and uses high-throughput simulations to generate new knowledge.
Health Services Advisory Group, Inc., (HSAG) has functioned for more than 30 years as a team of highly skilled professionals working to form one of the most successful health care quality improvement and quality review organizations in the nation. It is the mission of this team to be a positive force in health care by providing quality expertise to those who deliver care and helpful information to those who receive health care services. HSAG now serves over 20 percent of the Medicare population nationwide as a quality improvement organization (QIO). HSAG is also involved with Medicaid programs in more than a dozen states where it is responsible for assuring the quality, access, timeliness, and appropriateness of care for approximately 45 percent of the nation's Medicaid recipients.
About CMS Quality Measures
Quality health care is a high priority for the President, the Department of Health and Human Services (HHS), and the Centers for Medicare & Medicaid Services (CMS). Developing quality measures, collecting the data for the measures, and then calculating the results is one way of assessing the quality of health care provided. CMS uses quality measures in its various quality initiatives that include quality improvement, pay for reporting, pay for performance, and public reporting.