Human-Centered Design as a Research-to-TA Bridge: A Real Operating Model to Stop Public Health TA from Falling Short

By Joshua DeLung, VP, Population Health, Altarum

Some federally funded public health research stops about three steps short of where it needs to go. The findings are published. Maybe a webinar happens. A toolkit lands on a website. A report goes to Congress. And then the people who were supposed to act on the insights — state agencies, healthcare providers, tribal health programs, or community-based grantees — are left to figure out the rest on their own.

That last mile is where the value is. And it’s where too few federal investments are falling short by only addressing one-off data gathering for the sake of reporting.

The fix isn’t more research. It’s a research-to-technical-assistance (TA) model: insights designed from day one with an implementation pathway, a technology wrapper, and a delivery system built for the humans who will use them.

Here’s what that looks like in practice:

1. Human-Centered Design as the standard: Literature reviews and surveys are helpful tools, but starting with mixed-methods, human-centered design work that applies methodologies such as interviews, workflow mapping, experience journey analysis, and co-design sessions with the people doing the work gets to faster insights that drive measurable change. Government needs partners who don’t just create reports and dashboards, but also who provide actionable recommendations with time-boxed, mission-aligned, outcomes-focused implementation plans included.
2. TA as a full lifecycle: From there, TA must be treated as a natural follow-up to the research that’s baked into the project from the start. And it needs to follow a lifecycle, not just produce one-off deliverables. It can start with training and coaching. But agencies also need measurable dissemination strategies that bring targeted engagement and ongoing feedback loops to keep growing impact and understanding what strategies and tactics work best to achieve the mission. On-the-ground TA recipients need implementation playbooks and communications — in their language, on their channels, and at a pace that aligns to their size and budget. Finally, continuous measurement and workload prioritization methodologies ensure agency program teams build their own capacity over time rather than creating permanent dependency on outside consultants.
3. Technology and artificial intelligence (AI) as the accelerator: Used responsibly, AI accelerates every stage of this work: synthesizing qualitative data at scale, surfacing workflow patterns across many journey maps, personalizing TA content to a specific grantee’s context, generating plain-language translations of dense findings in minutes instead of months, and tracking implementation fidelity against outcome measures in near real time. TA centers do need to consider the risks of AI, including bias, hallucination, privacy, and cultural impacts. That’s exactly why this work demands humans in the loop plus security and governance built in from the start. Other technology platforms and tools, such as cloud-based TA trackers, domain-specific calculators, risk assessment tools, and live help features, can also drive meaningful improvements to TA outcomes. But without a plan for tech-forward, HCD-led research and TA approaches, public health investments risk missing out on considerable returns for improving health at the scale that’s now possible. They also risk building the wrong technology products and resources for TA recipients and wasting hundreds of thousands of dollars on deliverables that no one adopts.

Public health agencies will succeed more often at delivering effective TA when they design co-created public health solutions that include not just one-off research reports, but also TA and outreach products that are contextualized by an HCD lens and enhanced by appropriate technology with human controls in place. By crafting statements of work within future requests for proposals to cover these three important points, public health can begin to close the evidence-to-action gap that exists today.