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For decades, success in federal health technology was measured by activity: how many systems were deployed, how many transactions were processed, how closely programs matched their original requirements.

Today, agencies are under pressure to demonstrate something more difficult and more meaningful. They are being asked to show that technology investments actually improve how programs function and how people experience them.

That shift from activities to outcomes is forcing changes in how health IT programs are designed, managed and evaluated.

Moving from requirements to results

Candice Charlton, vice president and solution architect of the health market at Maximus, sees that shift most clearly at the very beginning of a program.

“It used to be we would have a set of requirements and go, ‘Here’s what it needs to do, and we’ll go do it,’ ” Charlton said during Federal Monthly Insights — Health IT 2026. “And now we get involved very early and think about what this program or this technological solution needs to do, ultimately, for the beneficiaries or the stakeholders of the system, and how we’re actually going to measure that.”

That change sounds subtle, but its implications are profound. Instead of starting with a checklist of features, agencies are being pushed to start with more fundamental questions. What problem is the system meant to address? Who is affected? What would success look like for the people relying on the technology?

That mindset can be difficult for organizations accustomed to compliance‑driven processes. Federal health IT programs operate in an environment shaped by oversight, mandates and risk management. Charlton said those constraints are real, but they can also crowd out deeper inquiry. Agencies often move quickly to define how a system should work before fully articulating why it needs to exist.

Why outcomes are harder to define in federal health IT

In many federal domains, outcomes are relatively straightforward to track. In health IT, they are not. Improvements in access, coordination or usability often show up indirectly over time and across multiple systems.

“In federal health, it is harder,” Charlton noted on the Federal Drive . “An outcome like a healthier population isn’t a metric you can just pull from a database. So we have to figure out what those proxies are that we can then back into technologically, to understand how we get to that mission and to that outcome.”

Those proxies might include whether people resolve issues more quickly, whether systems reduce unnecessary steps or whether agencies can better coordinate services. None of those indicators alone tells the full story. Together, they can signal whether health IT systems are advancing program goals rather than simply processing tasks.

Learning to accept imperfect proxy measures is part of the necessary mindset shift. Outcomes‑based approaches require agencies to revisit assumptions, refine measurements and adjust systems over time rather than declare success at deployment.

Designing systems around people, not transactions

Outcome‑oriented thinking also challenges long‑standing design patterns in federal health IT. Many legacy platforms were built around encounters and transactions. They captured diagnoses, claims and procedures effectively, but they were not designed to reflect the broader needs or goals of the people using them.

That limitation has become more visible as agencies adopt “whole health” policies that emphasize wellbeing rather than isolated medical events. While the policy direction is clear, Charlton explained that the technology has been slower to follow. Systems were not originally designed to integrate services, data and workflows across a person’s full interaction with government programs.

Bridging that gap requires interoperability and careful governance. It also requires patience. Agencies must modernize without disrupting existing services or compromising privacy, which often means layering new capabilities onto older systems rather than replacing them outright.

Constraints as tools, not obstacles

Charlton said mandates and standards, often experienced by agencies as barriers to innovation, can also serve as enablers. Shared expectations about data standards and system behavior reduce guesswork and make integration more predictable.

That structure allows agencies to experiment in more controlled ways. Rather than launching large, monolithic systems, many health IT programs rely on pilots, modular development and incremental rollouts. New ideas are tested in lower‑risk environments and expanded only after early results are understood.

This approach reflects the reality that federal health IT carries significant responsibility. Moving deliberately is part of maintaining public trust.

Where artificial intelligence fits responsibly

Artificial intelligence is frequently presented as a solution to complexity. Charlton cautioned against using it as a starting point.

“To me, AI earns its place in federal health architecture when it removes friction from the critical path of the person who’s trying to get the benefit that they need,” she said. “If we don’t have the underlying pieces correct, we’re just going to speed up what’s already wrong.”

That perspective has led many agencies to focus AI adoption on administrative workflows and known bottlenecks rather than high‑stakes functions. AI is most effective, Charlton said, when it supports processes that already work and improves efficiency without changing intent.

Leadership, trust and the road ahead

Ultimately, the move toward outcomes‑based federal health IT is a leadership challenge as much as a technical one. Agency leaders must decide when to test new approaches, how to measure success and how to communicate progress without overstating results.

Charlton said trust builds when agencies focus on clear problems, demonstrate learning through pilots and remain transparent about trade‑offs. Over time, those practices create room for innovation without undermining confidence.

Looking ahead, Charlton expects that today’s tools and approaches will look early and incomplete in hindsight. Federal health IT is still at the beginning of a long transformation.

The systems may become more intuitive, more connected and more responsive, but the real marker of success will remain the same. Technology will matter most when it supports outcomes that people can actually feel as well as measure, Charlton said.

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