The agency is looking at how AI can free up manual workloads as it develops a larger artificial intelligence strategy.
The Centers for Medicare & Medicaid Services is exploring how artificial intelligence can reduce workforce burden through two new pilots focused on knowledge management and information security.
“We are taking small chunks and we are learning and piloting programs, testing out hypotheses,” Rick Lee, a CMS senior technical advisor, said. “We are extracting the most value we possibly can in small increments, building on lessons learned in the knowledge we have gleaned from each one and extending that into larger engagements.”
For CMS’ knowledge management pilot, the team made data more discoverable and created more relevant search results. AI helped train search models that could sort through large datasets and automate content curation, a challenge for larger organizations like CMS.
“Knowledge management at enterprises like CMS is a challenge. We are working with multiple content repositories, with multiple styles, without a formalized taxonomy of how that data can be understood by a machine,” Lee said.
CMS is leveraging AI to free up workloads and manage content in an iterative process. Within this process, AI creates workflows then that workflow is sent to human teams for validation, which will then train the models to continually improve search functions.
For the second iteration of this pilot, CMS is leveraging AI in a burden-reduction capacity, Lee said. The goal for this is to identify processes and best practices while removing obstacles in a small-scale engagement for CMS to use as it launches a