Towards achieving semantic interoperability of clinical study data with FHIR

Abstract

Background: Observational clinical studies play a pivotal role in advancing medical knowledge and patient healthcare. To lessen the prohibitive costs of conducting these studies and support evidence-based medicine, results emanating from these studies need to be shared and compared to one another. Current approaches for clinical study management have limitations that prohibit the effective sharing of clinical research data.

Methods: The objective of this paper is to present a proposal for a clinical study architecture to not only facilitate the communication of clinical study data but also its context so that the data that is being communicated can be unambiguously understood at the receiving end. Our approach is two-fold. First we outline our methodology to map clinical data from Clinical Data Interchange Standards Consortium Operational Data Model (ODM) to the Fast Healthcare Interoperable Resource (FHIR) and outline the strengths and weaknesses of this approach. Next, we propose two FHIR-based models, to capture the metadata and data from the clinical study, that not only facilitate the syntactic but also semantic interoperability of clinical study data.

Conclusions: This work shows that our proposed FHIR resources provide a good fit to semantically enrich the ODM data. By exploiting the rich information model in FHIR, we can organise clinical data in a manner that preserves its organisation but captures its context. Our implementations demonstrate that FHIR can natively manage clinical data. Furthermore, by providing links at several levels, it improves the traversal and querying of the data. The intended benefits of this approach is more efficient and effective data exchange that ultimately will allow clinicians to switch their focus back to decision-making and evidence-based medicines.

Keywords: CDISC ODM; Clinical research data; FHIR; Interoperability; Longitudinal clinical study.

Fig. 1

The ODM data model. Illustrates the logical organisation of the ODM model into the data and metadata hierarchies

Fig. 2

The FHIR data model. Depicts the metadata (red) and data (blue) FHIR resources and their links that comprise the data model to transform the clinical data from ODM to FHIR. The CarePlan and Questionnaire resources are used to capture the metadata for the study. A Patient resource is used to represent the study participant while the clinical data for this participant is contained within a ClinicalImpression resource. The study events are captured within the EpisodeOfCare resource and the Encounter resource represents one atomic event. The QuestionnaireResponse resource captures the form responses and the Observation resource illustrates those responses that are analogous to a patient’s observations. The QuestionnaireResponse resource is linked back to the Questionnaire resource

Fig. 3

Mapping the ODM data model to the FHIR resources. Illustrates how the CDISC ODM model (depicted by unshaded rectangles) is overlaid with the FHIR resources. The Metadata section, depicted on the right of the model with red rectangles to represent the FHIR resources, is mapped to the CarePlan resource at the Study and Study Event level, and to the Questionnaire resource to represent the form and its composition. The Data section is depicted on the left of the model with the FHIR resources depicted as blue rectangles. The Patient resource represents the study participant. The ClinicalImpression resource captures the clinical data for this participant and they are both linked to the ODM model at the Subject Data level. As both the EpisodeOfCare and Encounter resource correspond to study events, they are mapped at the StudyEventData level. The QuestionnaireResponse resource captures the form responses and is linked to the form data and its composition. Finally, the Observation resource is used to capture those responses that are more analogous to a patient’s observations

Fig. 4

The clinical research data model in FHIR. Illustrates the metadata (red) and data (blue) resources comprising the clinical data model for describing and capturing the research study natively in FHIR. The study plan can be described using either the ClinicalStudyPlan or PlanDefinition resource. The latter can be further defined using the ActivityDefinition resource. The Questionnaire resource provides the definition for forms within the study plan. A link to the study plan is contained within the ClinicalStudyData resource. The ClinicalStudyData resource encapsulates the clinical data comprising the research study. It facilitates links to the Patient resource, to describe the study participant. It further describes investigations that can be a QuestionnaireResponse or a series of Observation or ImagingManifest resources. The ImagingManifest resource further defines an ImagingStudy resource to describe the imaging study being conducted

Fig. 5

The ClinicalStudyPlan resource. Describes the elements comprising the ClinicalStudyPlan resource. This resource has been generated using the FHIR Build Process [45] based on the FHIR Guide to Designing Resources [46]. The build process builds the resource and generates the webpage that describes the resource, as depicted in this Figure. The table structure is defined in the Resource Definition page [47], which also provides a definition of the flags; ‘?!’ indicates that the element is a modifying element, while ‘Σ’ indicates that this element is part of the summary set. The activity element allows either the definition of detailed items or a Questionnaire resource to be specified

Fig. 6

The ClinicalStudyData resource. Describes the elements comprising the ClinicalStudyData resource. This resource has also been generated using the FHIR Build Process [45] based on the FHIR Guide to Designing Resources [46]. The table structure is defined in the Resource Definition page [47], which also provides a definition of the flags; ‘?!’ indicates that the element is a modifying element, while ‘Σ’ indicates that this element is part of the summary set. The event element describes the events occurring throughout the study. An event can be further divided into visits. Each visit defines an investigation, which can be only one of the following: a QuestionnaireResponse resource or a series of Observation or ImagingManifest resources