EU-funded R&D project
Developing a seamless and acceptable method for reusing hospital EHR data within clinical trials
With increased use of Electronic Health Records (EHRs), hospitals generate a vast amount of electronic health data that could be of benefit to medical research. However, due to their lack of connectivity with research platforms, there has been a huge need for the manual re-entry of data within clinical trial Electronic Data Capture (EDC) systems. This also includes data cleaning and verification … with all the ensuing disadvantages and risks: human error, workload, delay to the completion of every clinical trial and for its drug reaching patients.
Hospitals perceive that 70 up to 100% of data is duplicated across their EHR and EDC systems
The EHR2EDC project (2018-2019) has demonstrated a method and technology for achieving an efficient and trustworthy trial reuse of health data from hospital EHRs.
Following patient informed consent, EHR data can now be automatically and securely transferred to the Electronic Data Capture (EDC) system for a study investigator to review and save.
The EHR2EDC solution includes a framework to ensure GDPR compliance, the assessment of the quality of hospital EHR systems and of the EHR data quality.
The data mappings required to bridge between healthcare and research standards are now open access and can be found through our resources page.
The EHR2EDC project was co-financed by EIT Health and by the pharma and clinical research industry.
Benefits
Beneficiaries such as research (industry and academic sponsored trials), hospitals and eventually patients will all see the benefits from this innovation.
Researchers
will speed up data collection and exchange to accelerate research
Patients and their clinicians
will have faster access to novel treatments
Hospitals
will be able to better use their own data to gain decision-supporting insights
Everyone
will benefit from better-quality hospital and research data and systems
Read all about the outcomes and benefits of EHR2EDC
The EHR2EDC results in a nutshell
Interoperability mapping
The first validated set of the most commonly collected data in clinical trials was mapped, Common Information Model (CIM) and HL7 Fast Health Interoperability (Resources (FHIR) based interoperability profiles developed
Regulatory
ISO Good Clinical Practice (GCP) and Regulatory compliance for regulated trials
Data governance
Principles, code of practice and Standard Operating Rules to support hospitals to conform to applicable GDPR regulations
Technical module
Tested and validated
Validation study
Multi-centric, multi-sponsor validation study (TransFAIR) successfully completed at the partner sites
TransFAIR Study: 37% of patient data transferred
Discover more about this EHR2EDC validation phase, with the results of the TransFAIR Study.
TransFAIR was a synthetic clinical study that replicated the data collection of several real clinical trials drawn from multiple pharma companies in multiple disease areas. Its goal was to prove that at least 15% of data usually manually entered could be automatically transferred under control of the investigator. It was found that 37% of the necessary data could be successfully transferred.
EHR2EDC Champion Programme: amplifying the results of phase 1
Given the positive results obtained during the 2018-2019 phase of EHR2EDC, the consortium is adding a one year extension to continue the project by means of a Champion Programme.
Objectives of the EHR2EDC Champion Programme (2020)
- Having a trial-ready version of EHR2EDC technology for supporting trials at Clinical Sites in Europe and North America
- Increased % of data recovery
- Having a common standardized oncology and cardio-vascular mapping library
- Data quality and enrichment at partner hospitals
- Certification and Quality SealSustainable governance
Challenges tackled during EHR2EDC
Interoperability
Data Governance
Data Quality
Systems Quality
Regulatory Work
Consortium
This project was possible thanks to the participation of several partners and interacting with our ecosystem.
