Clinical research is at a crossroads. Increasing trial complexity, site-level resource constraints, and fragmented technology have made high-quality data capture harder than ever. Clinical teams often spend hours manually transcribing near-duplicate patient information from the electronic medical record (EMR) into electronic data capture (EDC) systems—creating unnecessary burden and costly audits.

eSource—capturing trial data electronically at the point of care—has emerged as a potential solution. But despite industry momentum, it remains inconsistently defined and poorly implemented. Most EHR-to-EDC integrations add complexity rather than reducing it.

It’s time to move beyond basic integrations. A smarter, site-centric eSource model can reduce manual work, accelerate data flow, and better support research teams where it matters most: in the day-to-day conduct of trials.

Why Current EHR-to-EDC Approaches Fall Short

Many existing EHR-to-EDC solutions do little more than connect systems, acting as mere data pipes rather than intelligent interfaces. This superficial integration often fails to genuinely reduce site burden or streamline data capture, leaving a significant gap in efficiency. The result is a patchwork process that continues to rely heavily on manual data entry, creating considerable workflow friction and limiting sites' control over their own valuable data. This approach falls short of providing a truly integrated and efficient solution.

Some of the most common challenges facing both providers and trial sponsors include:

• Technical Variability and Mismatched Formats: While structured data can often be mapped to CRFs, it’s frequently incomplete or sparsely populated—forcing teams to rely on unstructured documents instead. But unstructured data presents its own challenges, with inconsistent formats and high cognitive load required to interpret and translate clinical narratives into structured fields. Together, these gaps drive up manual effort and hinder efficiency.
  
  
• Limited Visibility into Available Data: While users can technically view data available for transfer, it's often presented in a format that differs from both the EHR and the EDC. This disconnect increases cognitive load, slows review, and leads to continued reliance on manual verification.
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• Manual Burden and Fragmented Workflows: Users still select data manually and complete forms in the EDC, resulting in disjointed workflows and limited efficiency gains.
  
  
• Workflow Misalignment: Clinician documentation isn’t designed for trials, so critical structured data is often missing—forcing coordinators to fill gaps manually.
  
  
• Rigid Forms and Vendor Constraints: Limited flexibility to adapt direct data capture forms or workflows to site needs means users work around rigid templates with little vendor support.
  
  
• Mapping Burden on Sites: Many solutions require providers to define and maintain mappings from the EHR to the EDC themselves. This creates added complexity, slows implementation, and increases reliance on internal technical resources, diminishing efficiency gains.

Together, these factors mean that EHR-to-EDC solutions often fall short of their promise, creating frustration for sites and sponsors alike.

What Sites and Sponsors Really Need from eSource

What providers and sponsors actually need goes far beyond a technical connection—a new model for how data moves from clinical care into research, without compromising workflows, compliance, or control.

A modern approach to eSource must be:

• Site-Centric: Instead of requiring sites to adapt to rigid sponsor systems, next-gen eSource should align with real-world clinical workflows—integrating with site tools and workflows through technology, processes, or people to minimize disruption and reduce burden.
  
  
• Streamlined and Simplified: Modern eSource should reduce systems and interfaces where possible by enabling direct data capture, EHR integration, and single sign-on
  
  
• Designed for Rapid Verification: A modern eSource solution should surface all relevant source data—whether from the EHR or paper—directly within the application. With intuitive tools for importing and verifying both structured and unstructured data, sites can complete source verification faster and with greater confidence.
  
  
• Flexible with Real-Time Visibility: EHR-to-EDC solutions should support a range of study designs and site workflows while tailoring data capture to protocol needs. Visibility into what’s complete, missing, or pending ensures teams stay aligned and trials stay on track.
  
  
• Intelligent and Scalable: Technologies like LLMs can identify and extract relevant data from EHRs, flag discrepancies, and pre-populate forms—reducing manual effort while improving data quality and speed. Agentic AI workflows that leverage memory to self-learn and improve over time also enable faster expansion to additional eCRFs over time, increasing scalability without added burden.
  
  
• Compliance-Ready Without the Overhead: Next generation eSource must include built-in traceability, source verification, and audit trails. Sites shouldn’t have to sacrifice compliance to gain speed.

Ultimately, the goal isn’t just to transfer data faster—it’s to make clinical research feel less like a bolt-on to care delivery and more like an integrated part of the patient journey.

Meeting Research Workflow Efficiency and Data Quality Demands with eSource Casebook

In response to demands for automated data capture, improved efficiency, and seamless data transfer to EDC systems, Paradigm Health launched eSource Casebook, an EHR-integrated application that extracts structured and unstructured data from the EHR, enables auto-population of electronic case report forms (eCRFs), and seamlessly pushes properly formatted information to EDCs.

By automating data entry, aligning with site workflows, and streamlining the transfer of high-quality data to sponsors, eSource Casebook reduces manual burden, improves accuracy, and enhances collaboration between sites and sponsors. 

Learn more about eSource Casebook here.