fhir4pharma: Digitalizing Clinical Trial Protocols with FHIR

Clinical trials rely heavily on the Schedule of Activities (SoAs), the detailed roadmap that dictates what data must be collected and precisely when. Traditionally, this roadmap is presented as a static, tabular chart within the study protocol. However, real-world research is rarely static. Patients miss visits, unexpected events occur, and complex study designs (like in oncology) require multiple treatment cycles and conditional branching.

Patrick Genyn, and his colleague Andrew Richardson, both from fhir4pharma, are working at the intersection of clinical care and research to solve this problem. Their paper, "Clinical Trial Schedule of Activities Specification Using Fast Healthcare Interoperability Resources Definitional Resources: Mixed Methods Study," published in JMIR Medical Informatics, introduces a robust digital methodology to represent the complex reality of clinical trials.

Mapping Complexity with Graph Methodology

The core of their innovation is a generalized graph-based methodology used to represent a managed SoA. Unlike the traditional, rigid table format, a directed graph model uses nodes (visits or activities) and edges (transitions) to define every potential path a patient might take through a study.

This graph approach is essential because it accounts for real-world scenarios that static tables ignore:

• Conditional Branching: For example, a patient no longer meets inclusion criteria later in the study or needs additional visits or procedures because of pre-existing conditions.
• Adaptive Designs: For example, complex oncology studies involving multiple treatment cycles (cycles 1, 2, 3, etc.), where what happens next depends on earlier responses.
• Deviation Management: For example, missed visits, visits outside the planned window, or withdrawal of consent.

This resulting graph representation provides the starting point for creating operational elements that account for all potential paths, ensuring consistency and accuracy in interpreting the clinical research protocol.

FHIR and the Future of Digital Clinical Research

The second part of the paper details how this graph model is translated into a FHIR-based methodology using the FHIR PlanDefinition resource. Fast Healthcare Interoperability Resources (FHIR) is the industry standard for exchanging healthcare information, and its use is critical for modernizing clinical research.

To fully represent the flexibility of the SoA graphs, the team developed two specific FHIR extensions for the PlanDefinition resource:

1. soaTimePoint: Needed for accurate SoA time point specification (e.g., when visit 2 occurs and how it relates to other visits).
2. soaTransition: Needed for accurate SoA transition specification (e.g., within visit 2, what are the potential next steps or next visits for a patient).

These extensions allow the FHIR-compliant bundles to accurately and efficiently transfer complex study schedules. This capability permits direct data capture from Electronic Health Record (EHR) systems to the clinical trial process, eliminating manual transcription, increasing accuracy, and providing early access to research data.

Accelerating Research in a Complex Environment

Digital methodologies are essential as clinical trials are becoming increasingly complex – integrating real-world data, EHR-to-EDC integration, adaptive study designs, and patient-centric workflows. Accurate, tested digital methods like this graph-based FHIR representation are necessary to streamline operations, reduce human error, and accommodate the increasing number of stakeholders involved. The approach has been tested on more than 25 study protocols, all of which could be represented without loss of information.

The authors chose to publish their paper in the JMIR Medical Informatics journal to ensure their work reaches the broad range of clinical trial stakeholders interested in cutting-edge digital health operations and interoperability. They believe this methodology provides a precise and extensible foundation for the automated integration of study protocols with electronic health records.

To learn more about how graph-based modeling and FHIR extensions are transforming the precision and complexity of clinical trial schedules, watch the video featuring Patrick Genyn and read the full research article to explore the detailed methodology.

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