Data Analytics to Improve Medicaid Care and Costs
As the healthcare industry shifts to value-based care and fine-tunes their efforts to lower unnecessary costs, Medicaid state agencies have looked to major players in the healthcare data analytics space. This leap is of course not easy for many of these state entities but the Mississippi Division of Medicaid (Mississippi DOM) offers a shining example of how to successfully leverage data analytics to improve care while reducing costs. Several other state Medicaid agencies have already tapped on Mississippi DOM for insights and best practices for adopting a similar initiative. I predict that we’ll see many other states making the leap into big data in 2015 to align their payments with quality and value.
Mississippi Division of Medicaid Taps Data Analytics
Before 2013, Mississippi DOM was struggling to manage its 2.1 million potential Medicaid patients’ records and identities. To bring more cohesion to a fragmented patient identification system and improve patient safety, Mississippi DOM brought on a data analytics expert to help deploy a clinical Master Patient Index (MPI) in 2013. By leveraging powerful analytics and advanced algorithms, the Mississippi DOM staff successfully matched 91% of all 2.1 million Medicaid beneficiaries’ data throughout the state.
Leveraging analytics, Medicaid providers were able to create a single-identifier for each of Mississippi’s 800,000 active Medicaid beneficiaries. This process allowed administrators to easily manage patient records and ensured that providers were viewing the right longitudinal record during a clinical visit. During the initial implementation, over 8 years’ worth of data (plus lifetime events, such as amputations) were sorted, matched and created into single identities within Medicaid’s records. This process – which consisted of several iterations – took just under a year to develop, refine and implement.
As Mississippi DOM began to implement its population health management program and MPI, it experienced some challenges that shaped the initial implementation of the program.
The first challenge was developing a system that would be able to handle the immense amount of data that would be analyzed at any given time. Mississippi DOM needed to build a modern infrastructure on top of their legacy systems in order to manage 2.1 million identities, which could include between 600,000 and 800,000 active identities in any given month. This is a challenge that the industry will continue to face and overcome as the vast amount of data created on a daily basis continues to increase.
A second obstacle was around leadership obtaining buy-in from the various stakeholder groups across the state. Other providers were required to agree to work with Mississippi DOM to create this globally harmonized MPI system, by integrating and synchronizing local and regional MPI systems. This proved to be a major challenge, and unifying the existing MPIs with the robust MPI that Mississippi DOM has developed has yet to be completed. The reality is that each provider has an MPI that is at a different stage of its lifecycle and these systems will need to work together to build the robust state-wide MPI Mississippi DOM leadership envisions.
After overcoming external and internal challenges, Mississippi DOM achieved a 91 percent confidence rate in automated matching due to the complex algorithm developed by the technology provider.
Mississippi DOM is now looking towards the next phase of the project: harmonizing the Medicaid clinical MPI with external stakeholders to support clinical data exchange. Updates will be announced in the coming year.