Pharma leaders have invested in more data, better analytics, and tools designed to expand patient visibility. Yet new survey findings highlight a persistent challenge: identifying the right patients early enough to influence enrollment, treatment, and engagement decisions.
That timing gap matters because claims, electronic health records (EHRs), analytics platforms, and site intelligence tools can provide valuable insight into patient populations and study performance, but that insight doesn’t always arrive when teams are best positioned to act on it.
A recent IMO Health survey of senior pharmaceutical and biotechnology leaders across clinical development, clinical operations, medical affairs, and commercial functions points to a clear disconnect between the capabilities organizations want and what they can execute today.
Across the findings, four themes stood out: earlier patient identification, limited real-time visibility, implementation friction, and growing reliance on hybrid data and recruitment models.
Here is a closer look at each challenge:
1. Earlier patient identification remains the central challenge
Half of respondents identified finding eligible patients earlier as their most significant challenge, while 47% recognized determining patient eligibility as the greatest barrier preventing activation.
That distinction is important, as the broader challenge comes from helping study teams, sites, and commercial teams recognize relevant patients soon enough to engage them, whether for clinical trial participation, guideline-based treatment, patient support, or appropriate therapy initiation.
Traditional data sources often provide visibility after a diagnosis, encounter, prescribing decision, or treatment milestone has already occurred. For teams managing increasingly complex protocols, specialty therapies, and precision medicine programs, that delay can increase dependence on retrospective searches and manual review.
In other words, the market’s constraint is shifting from data availability to clinical timing.
2. Real-time visibility is still the exception
The demand for earlier identification is closely tied to another gap identified in the survey: access to real-time information.
Real-time patient visibility ranked as the most desired capability, selected by 38% of respondents. Yet only 6% reported having that capability today. Most organizations continue to rely on periodic reporting or downstream information to understand patient populations and clinical activity.
The effects extend well beyond recruitment. Limited visibility can influence site selection, patient identification, study activation, therapy adoption, guideline implementation, and a team’s ability to respond as clinical activity evolves.
Historical data remains essential for understanding patterns and informing strategies. But its limitations become more apparent when teams need to act. Whether the goal is to identify trial candidates, recognize a treatment-ready patient, evaluate a site opportunity, or respond to changing clinical activity, retrospective visibility alone may not provide enough lead time.
Respondents’ priorities reinforce this shift. In addition to real-time patient visibility, leaders emphasized earlier identification, EHR workflow integration, improved site and patient visibility, and reduced dependence on manual chart review.
3. Execution, not strategy, is where progress slows
Of course, recognizing the need for earlier insight is only part of the equation. Putting that insight into practice across diverse sites, systems, and workflows remains a major hurdle.
Many organizations understand what better patient identification should look like, but many struggle to implement it across sites, systems, and workflows.
Nearly one-third of respondents identified execution or site quality as the primary operational breakdown. A similar percentage reported limited EHR integration, while 21% said they had no EHR integration at all. Another 32% characterized implementation as highly manual.
These findings echo a separate clinical site survey recently covered by Fierce Biotech. In that research, 59% of sites said recruitment inefficiencies resulted in fewer eligible patients being enrolled. More than a quarter spent over 20 hours each week reviewing referrals, and 52% used at least four tools during pre-screening. Nearly seven in 10 respondents said recruitment workload reduced the time available for patient care or study quality.
Together, these surveys reveal a broader operational problem: Transforming clinical insight into timely action. That could mean identifying eligible trial participants, recognizing treatment-ready patients, or engaging providers before opportunities are lost.
When sites are forced to interpret complex eligibility criteria manually, search across disconnected systems, and review large numbers of poorly matched patients, enrollment slows and study teams lose confidence in execution.
4. Hybrid approaches are becoming standard
To address these limitations, many organizations are moving toward models that bring multiple types of data and insight together.
The survey showed that organizations are moving away from single-source strategies, with 32% of respondents reporting the use of hybrid approaches that combine elements such as EHR data, workflow-driven identification, and historical information.
That shift makes sense because each source contributes something different. Claims and historical datasets provide scale and longitudinal context. EHR data adds clinical depth. Workflow-based approaches create an opportunity to identify and act on relevant patients closer to the clinical encounter.
But combining sources does not always make this information usable. Hybrid approaches require data to be normalized and clinically consistent across sources. Without a common terminology foundation, organizations can struggle to reconcile different codes, descriptions, data structures, and expressions of the same clinical concept.
As a result, competitive advantage is becoming less about possessing the largest dataset and more about connecting historical intelligence with precise, workflow-ready clinical context.
From more data to earlier action
Taken as a whole, the survey findings point to a market at an inflection point.
Life sciences organizations have already invested heavily in data, analytics, and reporting. Now, the focus is shifting to whether they can turn that information into action earlier in the patient journey – without adding more complexity for sites and care teams.
IMO Health helps bridge the gap between retrospective insight and real-time action by translating complex clinical criteria into precise, standardized clinical logic that can be deployed across diverse EHR environments.
This foundation can support several use cases, from identifying eligible trial participants and supporting guideline-based care to enabling precision commercial engagement and generating more clinically meaningful real-world evidence.
Across each use case, the goal is the same: help organizations recognize relevant patients sooner, reduce manual effort, and make clinical insight usable at the point where action can still influence the study.
Because in clinical research, having the right data matters. Having it at the right time may matter even more.
