955: Medicaid Modernization with Leidos

SUMMER JOHNSON: 

This is the award-winning Public Health Review Morning Edition for Friday, July 25, 2025. I'm Summer Johnson. Now, today's news from the Association of State and Territorial Health Officials.

KRIS MORK: 

Medicaid modernization has been going on for about the last 10 years, really motivated by a desire for increased modularity, reduced vendor lock-in, improved interoperability, and central to that vision has been the adoption of a data mesh, where we're de-emphasizing data ownership in favor of a model of federated data stewardship.

JOHNSON: 

This morning, we have a special episode that highlights the intersection of data modernization and Medicaid. Dr. Kris Mork is chief data officer for Leidos' health and civil sector. Mork joins us this morning to explain how it all comes together. Leidos is a member of ASTHO's Innovation Advisory Council, which is a new multi-sector collaborative of private sector partners that keep ASTHO's membership and leadership informed and nimble on emerging topics that affect public health. Mork explains the importance of balancing the need for data accessibility and stewardship within Medicaid systems and how a data mesh could support those needs.

MORK: 

When we think we own something and we try to guard that thing jealously, but when we're stewards, it's easier to accept that multiple people, or in this case, multiple modules, may need to access the data, and the data mesh organizes Medicaid data by domain in a way that enables scalability without sacrificing interoperability, and using that mesh promotes the creation of reusable data, usually based on HL7 or FHIR, and all of this in accordance with CMS expectations for interoperability. And by explicitly federating those governance decisions, a data mesh is going to improve data quality and trust, and disparate modules are now expected to validate their data in anticipation of sharing to generate faster, more actionable insights for the Medicaid agency, and possibly via standard BI tools, machine learning, or, as is increasingly the case in a conversation I've had with you all before, using AI tools.

JOHNSON:

Mork says some of the same trends in the world of Medicaid are also playing out in public health.

MORK: 

Over the last few years, we've observed a growing interest in centralized infrastructure, multi-tenant systems within public health, where multi-tenancy is a way to share that infrastructure while keeping the data within the system separate and secure. Those approaches were incredibly valuable during a public health crisis because they support the rapid system deployment across jurisdictions. So, an example of a centralized system would be HHS Protect, which we used for COVID-19. And an example of a multi-tenant system is biosense for syndromic surveillance, where we're allowing individual states to store their data centrally in a system managed by CDC, while still controlling access and analytics at the state level, where it belongs. Similarly, the National Health Safety Network is a multi-tenant system living on a centralized cloud allows independent healthcare entities to share the platform, preserving strict data security rules on these centralized multi-tenant systems, reduce redundancy. They lower costs. They simplify maintenance through the use of shared services and centralized upgrades. This trend has, however, largely run its course. HHS is emphasizing state-led innovation and accountability.

JOHNSON: 

And what does this really mean for public health?

MORK: 

At this point, federally sponsored multi-tenant systems are likely infeasible for public health. First, there's the operational and governance complexities that make a one-size-fits-all federal platform impractical. Second, there are differences in state policies, workflows, data needs, all that need to be accommodated in a shared system, but there are relatively straightforward technical solutions to those challenges. The final challenge is that funding is highly uncertain. States need to assume that they're going to be operating independently as they determine how to fund their modernization activities. We think that Medicaid modernization provides an avenue for public health modernization by upgrading their Medicaid systems. States are deploying flexible, modular platforms tailored to their local requirements. These are cloud-based, AP- enabled, standards-compliant, and central to a modernized Medicaid system, it's a common platform for data messaging, data management, security, shared capabilities that are required by all of the Medicaid modules. And this platform enables secure data sharing. States can then create interoperable environments within and across agencies to include Medicaid, public health, child welfare, and others.

JOHNSON: 

Mork mentions an example from Leidos' ongoing work with North Dakota.

MORK: 

In North Dakota, where the enterprise systems integrator responsible for transitioning the state's legacy Medicaid systems to a modular, integrated, and secure system, imagine expanding the system to support plug-and-play modules tracking specific chronic conditions, diabetes, asthma, heart disease, hauling that relevant data from Medicaid or adding capabilities like patient risk stratification, case management, clinical decision support. This kind of system would allow states to track chronic disease quickly without a full system overhaul. They can conduct joint interventions by Medicaid and public health entities and bridge that gap between clinical and population health systems.

JOHNSON: 

Finally, Mork shares some steps that public health authorities can take to benefit from the investment in Medicaid modernization.

MORK: 

First, public health agencies should work closely with Medicaid agencies to ensure public health systems are interoperable with modernized Medicaid platforms, for example, using FHIR standards and API-based data exchange, launching pilot programs with Medicaid managed care plans, housing authorities, community health organizations. Second, public health agencies should participate in or help lead efforts to create shared governance models with Medicaid and other state agencies covering privacy data sharing agreements, standardized reporting, addressing public health challenges related to chronic disease requires access to comprehensive and accurate longitudinal data across these systems, and third, explicitly prioritizing chronic disease reporting in health IT planning, including embedding data elements for diabetes, hypertension, asthma, similar conditions in health information exchange as well as chronic disease metrics and Medicaid managed care dashboards. These are important because chronic conditions drive the majority of healthcare spending, and using Medicaid data to proactively manage these conditions likely to improve outcomes and reduce costs.

JOHNSON: 

More information on Leidos' work in this area is in the show notes.

That'll do it for today. We're back Monday morning with more ASTHO news and information. I'm Summer Johnson. You're listening to the award-winning Public Health Review Morning Edition. Have a great weekend.