Achieving Semantic Interoperability in Clinical Trials

Continuous workflow is of prime importance in clinical trials. However, it is often challenged with the communication gap between different medical databases and manual processes of data acquisition and validation.

Input of data by hand on classical case report forms (CRFs) and retyping source information on Electronic Data Capture (EDC) templates is often resource-intensive and time-consuming. EDC systems are compliant with official standards and are configured for operational efficiency in trial maintenance and quality control. However, this low-level manual work impacts stakeholders at all levels and remains a challenge in the industry.

Furthermore, ambiguous data reconciliation between different medical platforms often results in errors, and slows down the pace of the trials, regardless of their size.

These operational impediments, due to limited data access, slow data acquisition, and inadequate database mapping, significantly impair the workflow and the resulting effectiveness of large-scale, multi-centered trials.

However, there is more than enough evidence to support the claim that this manual era of clinical trials is over. The emergence of novelty, interoperable systems is changing clinical trials, data management, and overall healthcare services.

The Value of Interoperability

Healthcare Information and Management Systems Society (HIMSS) defines interoperability as the ability of different information systems, devices and operating applications to coordinately connect, within and across organizational and national boundaries in order to access, exchange, and use valuable data.

Managing a clinical trial from its inception to the final eCRF implies concomitant functioning of multiple disparate applications that facilitate activities, such as trial design, site management, data management, and trial validation.

The main purpose of interoperability is to move original source data through application programming interfaces (APIs) without interfering with the authenticity of the originating source. This is achieved by intertwining different platforms on code level in order to flawlessly exchange information in real-time.

Interoperability is a prerequisite to the digital transformation of healthcare, necessary for the future of medicine. In other words, semantically integrated systems are essential for medical communication between and across sectors and researchers, and for international cooperation.

Moreover, an interoperable system enables facilities and departments across the world to receive and send their specialty-results for comparison and consultation. It is essential for improving the quality of patient care worldwide, and for the successful running of a clinical trial or comprehensive disease monitoring.

Interoperability saves countless work hours and facilitates invaluable human involvement.

Semantic Interoperability on a Large-Scale

The highest level of functional interoperability is achieved through a flawless exchange of data, which is fed through EDC forms into Clinical Trial Management Systems (CTMSs) through a standardized, semantically validated format.

Breaching the operational disparity in large-scale trials is achieved through integrating clinical trial-functions at syntactic and semantic levels. Two main functions that thrive through semantic interoperability are sourcing and streamlining of data.

Bridging the Gaps

Technologies that dictate clinical timeline depend on sourced and retrieved information, and without interoperability cannot achieve their full potential. Once the diverse medical terminology is semantically reconciled, CTMSs can offer consistency, correctness, and real-time proficiency.

In other words, semantic interoperability reassures preservation of data integrity by facilitating quality sourcing and providing operational transparency through unambiguous data cross-referencing.

In order to successfully run large-scale trials, the technologies need to correspond by using:

• eSourcing,
• Real World Evidence, and
• Software that bridges the terminology gap of disparate medical vocabularies.

Cutting-edge technological solutions, such as eSource, facilitate univocal and more compliant data sourcing at point-of-care.

Once the data is stored, it is cross-referenced to the indexes hived in Real World Data (RWD). By allowing access to RWD to various operational platforms, semantically concise communication between various global medical databases is achieved. Interoperable systems connect data indexes from multiple standards, connect it, and interpret it.

Now, developing and running large-scale clinical trials requires the use of Real-World Evidence (RWE), that is the study-relevant patient-data already stored in RWD.

Complex interoperable programs base the trial on RWE, and reference the eSourced data to the vast terminology in RDW. Developing such software burns resources and demands the knowledge of coding for cross-mapping of adequate terms.

Furthermore, relating real patient data, acquired and stored in an Electronic Health Record (EHR) to EDC systems, requires defined terminology relationships between the different databases.

Data integration and cross-mapping of clinical terms is achieved through the use of data standards in medical vocabularies that use unified, programmable languages to semantically connect etymological concepts. Furthermore, the communication between sending and receiving platforms enables the transfer of not only the data, but also its meaning.

The operating platforms need to exchange medical information, aggregate it, and store it in a manner that enables valid statistical analysis and cross referencing for clinical research epidemiological, and pharmacoeconomic purposes. In connecting terminology, no ambiguity is allowed, and explicitly specified synonyms must be clearly defined within hierarchies that determine the relationships between concepts.

In order to acquire RWE for operating large-scale clinical trials, the system needs access to RWD deposited in major systems and platforms, connected by a unified program language.

Cutting-edge interoperable software systems use some of the most comprehensive and valuable sources of terminology and real patient data, such as:

• ICD-10, a multinational reference base that provides information on diagnoses, mortality and morbidity statistics, as well as financial characteristics;
• SNOMED-CT, a database of concepts related to patient care (e-health data);
• MedDRA, a pharmacovigilance dictionary used for clinical trials and post-marketing activities;
• LOINC, a database of laboratory test results.

These multiple electronic sources are integrated with the use of unified coding language UMLS.

Future or Objective Reality

In the end, interoperable systems combine software proficiency with clinical expertise and provide streamlined transparency on every level. Maintaining workflow is the keystone of clinical trials, and the use of these systems reassures its continuity.

And the best thing is that the interoperable software is not a thing of the future, but a very attainable present reality. The more we dive into this reality, the more we empower clinical trials and provide state-of-the-art healthcare on a global scale.