Healthcare payers are navigating one of the most disruptive periods in recent memory. Rising medical costs, Medicare redetermination, and mounting regulatory pressure are compressing margins and forcing health plans to confront a question many have long deferred: What is data actually worth?

For Tom MacDougall, former Chief Information and Technology Officer at L.A. Care Health Plan, the answer is no longer abstract. Data, he argues, has become mission-critical, not as a reporting tool, but as a strategic and operational foundation for the healthcare enterprise.

In the first of a two-part interview, MacDougall speaks with Robert Lutton, Vice President at Sandhill Consultants, about what it takes to transform data culture inside a health plan, why real-time clinical data is replacing the old claims-driven model, and how AI can be deployed responsibly in one of the most regulated industries in the world.

Data as a strategic asset, not a compliance exercise

For much of the healthcare industry’s history, data was treated as something to be managed for auditors, not mined for insight. MacDougall says that it is changing rapidly.

“Considering data as an asset is absolutely necessary now for health plans to utilize it from strategic and operational perspectives to drive down costs. It has changed the perception and value of data,” he adds.

He also draws a pointed comparison to other industries, where data has long commanded strategic priority. In healthcare, he notes that recognition has arrived later and under pressure. The shift is less philosophical than existential: health plans that fail to leverage data effectively risk being outmaneuvered on cost, quality, and member outcomes.

The implication for data leaders is clear. The old framing, data as a compliance checkbox, is giving way to a new mandate: curate it, own it, and use it to drive downstream value.

Beyond claims data: Moving closer to the point of care

Healthcare’s foundational data layer has long been the claims stream, which is reliable in some respects but inherently delayed and often incomplete. MacDougall describes a fundamental shift in how LA Care Health Plan thinks about the data it collects and when it collects it.

“We’re moving closer to the point of care. Instead of waiting one or two months, depending on the nature of the claim stream, interoperability and related initiatives are enabling us to deliver services with far greater precision and timeliness at the moment they’re needed,” he says.

The goal, as he describes it, is proximity: to the member, the provider, and the moment of clinical decision-making.

“Before it was sit, wait, and chase. Now we’re trying to get ahead of it,” MacDougall explains.

Continuous validation: Building a living clinical data repository

The aspiration for a single, unified patient record has been a fixture of healthcare IT strategy for years. MacDougall outlines how LA Care Health Plan approached this challenge not by chasing a static ideal but by building a system designed for continuous accuracy.

“We’ve adopted what we call a continuous validation approach where we shape our data daily,” he says. “We’re rolling out a clinical data repository that captures member and provider interactions within the hospital setting. That data will then be used to validate information both upstream and downstream, helping ensure optimally accurate data at any given point within the value stream.”

Responsible AI in a highly regulated environment

When asked what it would take for AI systems to be truly reliable in this audit-ready environment in healthcare, MacDougall describes a framework.

“We’re making sure humans remain in the loop at every stage. Whenever AI is involved in rendering decisions within the tools we develop, we apply a rigorous framework that embeds human oversight throughout the UAT and QA processes. The goal is to ensure the outputs are accurate, reliable, and free from bias,” he says.

On the technical side, LA Care Health Plan is deploying Retrieval-Augmented Generation (RAG) to ground large language models in its own internal documentation and processes.

The human-in-the-loop requirement is particularly non-negotiable when it comes to decisions that could affect a member’s health outcome, says MacDougall.

“Any decision involving a denial of service or anything that could impact a member’s health outcome always includes human oversight. Depending on the level of care involved, a physician or care nurse reviews and validates the decision to ensure the AI-driven recommendation is appropriate and aligned with patient needs,” he concludes.

CDO Magazine appreciates Tom MacDougall for sharing his insights with our global community.