B. Claerhout

There is increasing international interest in the potential for re-using routinely collected electronic hospital patient health records, for clinical research purposes. This opportunity is especially attractive to the pharmaceutical industry that invests significantly in clinical trials and recognizes the potential efficiency gains that might be made,and the possible resulting acceleration in getting new medicines to market. This paper summarizes the objectives, work plan and first year results of the Electronic Health Record for Clinical Research (EHR4CR) four-year project, sponsored through the EU Innovative Medicines Initiative. EHR4CR aims to design and demonstrate a scalable and cost-effective approach to inter-operability, or the ability for health information systems to work together within and across organizational boundaries, effectively connecting Electronic Health Record systems (EHRs) and Clinical Research. The project is developing an innovative and reliable platform th...

Post-genomic clinical trials require the participation of multiple institutions, and collecting data from several hospitals, laboratories and research facilities. This paper presents a standard-based solution to provide a uniform access endpoint to patient data involved in current clinical research. The proposed approach exploits well-established standards such as HL7 v3 or SPARQL and medical vocabularies such as SNOMED CT, LOINC and HGNC. A novel mechanism to exploit semantic normalization among HL7-based data models and biomedical ontologies has been created by using Semantic Web technologies. Different types of queries have been used for testing the semantic interoperability solution described in this paper. The execution times obtained in the tests enable the development of end user tools within a framework that requires efficient retrieval of integrated data. The proposed approach has been successfully tested by applications within the INTEGRATE and EURECA EU projects. These ap...

EHR4CR is moving towards deployment of EHR enabled clinical research in Europe. The project has Piloted IT platform services are about to be scaled up to a commercially supported service. Hospitals will be offered higher efficiency in participating in clinical research. This is an example how ICT helps pharmaceutical industry to speed up the delivery of innovative medicines to healthcare.

Objectives To describe the IMI EHR4CR project which is designing and developing, and aims to demonstrate, a scalable, widely acceptable and efficient approach to interoperability between EHR systems and clinical research systems. Methods The IMI EHR4CR project is combining and extending several previously isolated state-of-the-art technical components through a new approach to develop a platform for reusing EHR data to support medical research. This will be achieved through multiple but unified initiatives across different major disease areas (e.g. cardiovascular, cancer) and clinical research use cases (protocol feasibility, patient identification and recruitment, clinical trial execution and serious adverse event reporting), with various local and national stakeholders across several countries and therefore under various legal frameworks. Results An initial instance of the platform has been built, providing communication, security and terminology services to the eleven participati...

ABSTRACT A substantial amount of clinical trials are subject to failure because they cannot recruit sufficient patients within the foreseen time and budget. Computer assisted evaluation of eligibility criteria is envisaged to improve the recruitment process by increasing coverage (i.e. making sure no eligible patients are ‘missed’) and speeding up the eligibility scanning process; and thus eventually reduce the overall failure rate of clinical trials. In this paper a new recruitment application is presented which assists in evaluating eligibility criteria based on available clinical patient data (e.g. Electronic Health Record data). The application leverages for the querying of clinical data on a generic semantic integration platform and a new Domain Specific Language (DSL) based on the Groovy programming language.