Real-world data, grounded in genuine community understanding

Why the industry keeps returning to the same locations

The logic of returning to proven site networks is sound: experienced teams, established infrastructure, and existing participant databases. In an environment where timelines are under pressure and feasibility risk is real, familiarity is a rational choice. But familiarity compounds over time.

Each trial that returns to the same fixed network reinforces the same catchment. The same communities are approached, and the same demographics appear in the data. Meanwhile, the populations carrying the highest burden of disease, often those outside established research infrastructure, remain consistently out of frame.

The ambition to reach underserved communities is genuine and growing across the industry. But it points to a structural limitation. Most research networks are anchored to fixed locations established years, sometimes decades, ago. And fixed locations have fixed reach.

Even fixed sites embedded in community settings serve only the population around their address. Beyond that, participation depends on travel - as time, cost, and disruption accumulate across the life of a trial.

These do not reach the coastal communities where prevalence is significantly above the national average, or the suburban areas where eligible populations are concentrated but research has never arrived.

“The reach of any network is ultimately determined by its footprint.”

Data-driven site selection

EMS Healthcare’s model begins differently. With over 6,000 geo-locations across the UK and national agreements with major supermarkets, there are no constraints on where a trial can go. Every study begins with the same questions: where does this research need to be for this indication, population and protocol. And where will participation be genuinely sustainable across the life of the trial?

The answers are powered by LASER. EMS Healthcare’s location intelligence tool, LASER, draws on almost 30 million real-world data points to identify optimal placement before a site is confirmed:

• Disease prevalence: where the target population actually lives, not where research has historically taken place

• Travel patterns: the distances participants can realistically sustain across repeated visits

• Demographic profiles: alignment between local populations and protocol criteria

• Social determinants of health: the structural conditions that support or erode long-term engagement

But LASER is not just a mapping tool. It is built on 26 years of operational experience supporting UK communities, and the insights that accumulate only through that depth of presence:

How participants in different communities access healthcare. When they attend appointments, and when they do not. The design decisions that make a research site feel familiar rather than clinical. The patterns of engagement, trust, and behaviour that vary meaningfully, and that no dataset alone can fully capture.

“Real-world data is only powerful when it is grounded in genuine community understanding.”

That combination of real-world data at scale, grounded in genuine community understanding, is what makes LASER’s site placement decisions reliable in practice, not just optimal in theory.

Placed with precision, present for the duration

For some trials, particularly those requiring continuous geographic expansion or rolling participant recruitment, a moving model is appropriate. EMS Healthcare’s infrastructure supports that.

For most trials, LASER identifies the right location or set of locations, and those sites remain for the duration of the study.

Participants return to the same environment, the same clinical staff, and the same setting that has become familiar to them. That consistency, whether it be across a six month or a three year protocol, is one of the factors that supports retention in long-duration studies where other models struggle. It also strengthens the relationship between research teams and the community, supporting not only the current trial but future access as well.

The compounding effect of getting location right

When placement is led by evidence rather than infrastructure, barriers reduce and the entire trial dynamic shifts.

• Recruitment accelerates because sites are located within the communities where eligible participants live.

• Screen failure rates decrease because population-to-protocol matching happens before recruitment begins.

• Retention improves as travel is reduced and participation becomes more convenient.

• Resulting in a dataset that is more representative.

Join the conversation

Each month, InSites draws on over two decades of experience supporting communities across the UK: what has worked, what we have learned, and what we are seeing in an evolving research landscape.

InSites Issue 4 is written by Cassie Kendrew, Chief Operating Officer at EMS Healthcare.

Subscribe to InSites on LinkedIn.