How AI Is Transforming SCAN’s Case Management
SCAN Health Plan is redefining how care coordinators work. By deploying artificial intelligence across its case management operations, SCAN now pulls a member’s complete history in just five minutes — a process that once took two hours. This shift marks a significant step forward in how Medicare Advantage payers use technology to improve both staff efficiency and member outcomes.
The results follow SCAN’s appointment of its first-ever chief AI officer, Aman Bhandari, PhD. Together with Corinne Stroum, SCAN’s senior director of emerging technologies, Bhandari is shaping a forward-looking AI strategy designed to scale alongside the plan’s growing membership.
The Problem: Time-Consuming Document Reviews
A Growing Membership Created Growing Pressure
Before AI integration, case managers and care coordinators faced a daily struggle. Gathering member information meant navigating multiple disconnected systems — a slow and exhausting process. Furthermore, as SCAN’s membership expanded rapidly, the burden on these teams grew sharply.
“When we grew, these were the teams that got hit the hardest,” said Stroum. “They had to maintain their turnaround time, their throughput, and their high quality of service — while managing a membership growth of over a third.”
The Human Cost of Manual Data Retrieval
Beyond the time investment, manual reviews pulled care coordinators away from what matters most — talking to patients. Staff spent valuable hours reading through documents instead of engaging directly with members who needed support. This imbalance created both operational inefficiency and a risk to care quality.
The Solution: AI-Powered Member History Retrieval
From Two Hours to Five Minutes
SCAN addressed this challenge by deploying AI tools to aggregate member data across systems in near real-time. Today, a case manager can access a member’s preferences, medical history, and risk profile within minutes. Consequently, staff spend far more time in meaningful conversations with patients.
Stroum described a common scenario that illustrates the difference. “If I have a panel of 150 members and one of them is hospitalized, I want to quickly catch up on everything we know about this member — their preferences, their history, their risks — and then I want to talk to that member,” she said. “We want to give that employee more time with the member than reading documents.”
Streamlined Workflows Across Multiple Systems
AI now connects data from disparate platforms, surfacing the right information at the right time. This streamlined retrieval process allows care teams to act faster and more decisively. Moreover, it reduces the cognitive load on coordinators managing large and complex caseloads.
Employee Response and Early Results
The rollout has generated strong internal support. Stroum noted that AI-driven document aggregation has become a major organizational focus — and the feedback has been overwhelmingly positive, earning “rave reviews” from frontline employees. Staff who once dreaded lengthy review sessions now begin their shifts with a clearer, more manageable workflow.
What Makes a Strong Health Plan AI Leader
Balancing Optimism With Skepticism
As the organization’s first chief AI officer, Bhandari offered a candid view of the mindset required for effective AI leadership in healthcare. “You have to simultaneously be the most optimistic person in the room, but also the most skeptical,” he said.
He explained that building a prototype is relatively straightforward. Scaling it to an enterprise-grade, safe, and ethical solution, however, demands significant investment and rigor. Accordingly, leaders must resist the temptation to over-promise on early-stage results.
Positioning AI Leadership Strategically
Notably, Bhandari’s role sits within SCAN’s people and transformation function — under Chief People and Transformation Officer Lindsay Crawley-Herbert — rather than within a technology team. This placement reflects a deliberate philosophy: AI transformation is fundamentally a people challenge, not just a technical one.
“The people part is the hard part,” Bhandari said plainly.
Building an AI-Driven Culture at SCAN
An Improv Mindset for Change Management
Stroum emphasized that cultural readiness is as critical as technical capability. She advocates for what she calls an “improv mindset” — treating every idea as worth exploring. This approach keeps employees engaged and invested in the transformation process.
“Historically, they might have waited for some top-down push that something needed to change,” she said. “That is a unique role of AI leadership — to be open to lots of new ideas and opportunities, and to give them space.”
From Top-Down to Bottom-Up Innovation
Instead of mandating change, SCAN’s AI leadership invites it. By creating an environment where staff feel safe to suggest improvements, the organization builds broader buy-in. Additionally, this model helps surface practical, ground-level insights that executives might otherwise miss.
Key Takeaways for Health Plan Leaders
SCAN’s AI journey offers several lessons for other payers navigating similar challenges. First, targeted automation of high-friction workflows — like document retrieval — delivers measurable ROI quickly. Second, effective AI leadership requires both technical credibility and people-first thinking. Third, cultural change must accompany technical deployment for results to stick.
As Medicare Advantage plans face rising membership and tighter operational margins, AI tools that free up care coordinators for direct member engagement represent a clear competitive advantage. SCAN’s early results prove the model works.
