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1.
J Biomed Inform ; 53: 162-73, 2015 Feb.
Article in English | MEDLINE | ID: mdl-25463966

ABSTRACT

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 participating hospitals and ten pharmaceutical companies located in seven European countries. Proof-of-concept demonstrators have been built and evaluated for the protocol feasibility and patient recruitment scenarios. The specifications of the clinical trial execution and the adverse event reporting scenarios have been documented and reviewed. CONCLUSIONS: Through a combination of a consortium that brings collectively many years of experience from previous relevant EU projects and of the global conduct of clinical trials, of an approach to ethics that engages many important stakeholders across Europe to ensure acceptability, of a robust iterative design methodology for the platform services that is anchored on requirements of an underlying Service Oriented Architecture that has been designed to be scalable and adaptable, EHR4CR could be well placed to deliver a sound, useful and well accepted pan-European solution for the reuse of hospital EHR data to support clinical research studies.


Subject(s)
Biomedical Research/organization & administration , Computer Communication Networks , Computer Systems , Electronic Health Records , Workflow , Algorithms , Cardiovascular Diseases/physiopathology , Clinical Trials as Topic , Equipment Design , Europe , Hospitals , Humans , Information Storage and Retrieval , Medical Informatics , Neoplasms/physiopathology
2.
J Biomed Inform ; 44 Suppl 1: S94-S102, 2011 Dec.
Article in English | MEDLINE | ID: mdl-21888989

ABSTRACT

BACKGROUND: There are different approaches for repurposing clinical data collected in the Electronic Healthcare Record (EHR) for use in clinical research. Semantic integration of "siloed" applications across domain boundaries is the raison d'être of the standards-based profiles developed by the Integrating the Healthcare Enterprise (IHE) initiative - an initiative by healthcare professionals and industry promoting the coordinated use of established standards such as DICOM and HL7 to address specific clinical needs in support of optimal patient care. In particular, the combination of two IHE profiles - the integration profile "Retrieve Form for Data Capture" (RFD), and the IHE content profile "Clinical Research Document" (CRD) - offers a straightforward approach to repurposing EHR data by enabling the pre-population of the case report forms (eCRF) used for clinical research data capture by Clinical Data Management Systems (CDMS) with previously collected EHR data. OBJECTIVE: Implement an alternative solution of the RFD-CRD integration profile centered around two approaches: (i) Use of the EHR as the single-source data-entry and persistence point in order to ensure that all the clinical data for a given patient could be found in a single source irrespective of the data collection context, i.e. patient care or clinical research; and (ii) Maximize the automatic pre-population process through the use of a semantic interoperability services that identify duplicate or semantically-equivalent eCRF/EHR data elements as they were collected in the EHR context. METHODS: The RE-USE architecture and associated profiles are focused on defining a set of scalable, standards-based, IHE-compliant profiles that can enable single-source data collection/entry and cross-system data reuse through semantic integration. Specifically, data reuse is realized through the semantic mapping of data collection fields in electronic Case Report Forms (eCRFs) to data elements previously defined as part of patient care-centric templates in the EHR context. The approach was evaluated in the context of a multi-center clinical trial conducted in a large, multi-disciplinary hospital with an installed EHR. RESULTS: Data elements of seven eCRFs used in a multi-center clinical trial were mapped to data elements of patient care-centric templates in use in the EHR at the George Pompidou hospital. 13.4% of the data elements of the eCRFs were found to be represented in EHR templates and were therefore candidate for pre-population. During the execution phase of the clinical study, the semantic mapping architecture enabled data persisted in the EHR context as part of clinical care to be used to pre-populate eCRFS for use without secondary data entry. To ensure that the pre-populated data is viable for use in the clinical research context, all pre-populated eCRF data needs to be first approved by a trial investigator prior to being persisted in a research data store within a CDMS. CONCLUSION: Single-source data entry in the clinical care context for use in the clinical research context - a process enabled through the use of the EHR as single point of data entry, can - if demonstrated to be a viable strategy - not only significantly reduce data collection efforts while simultaneously increasing data collection accuracy secondary to elimination of transcription or double-entry errors between the two contexts but also ensure that all the clinical data for a given patient, irrespective of the data collection context, are available in the EHR for decision support and treatment planning. The RE-USE approach used mapping algorithms to identify semantic coherence between clinical care and clinical research data elements and pre-populate eCRFs. The RE-USE project utilized SNOMED International v.3.5 as its "pivot reference terminology" to support EHR-to-eCRF mapping, a decision that likely enhanced the "recall" of the mapping algorithms. The RE-USE results demonstrate the difficult challenges involved in semantic integration between the clinical care and clinical research contexts.


Subject(s)
Biomedical Research/organization & administration , Delivery of Health Care/methods , Information Storage and Retrieval/methods , Software , Humans , Medical Record Linkage , Medical Records Systems, Computerized/standards
3.
Stud Health Technol Inform ; 160(Pt 2): 1324-8, 2010.
Article in English | MEDLINE | ID: mdl-20841899

ABSTRACT

Integrating biomedical research and patient care is a challenging issue requiring interoperability solutions. During a clinical trial, clinical data are captured twice, first in the Electronic Health Record (EHR) and then in the Clinical trials Data Management System (CDMS). The aim of REUSE (Retrieving EHR Useful data for Secondary Exploitation) project is to provide a single source solution for electronic data capture to the investigators of a university hospitals involved in a multi-centric clinical trial. We first investigated the differences between the workflows of patient care and biomedical research to specify the use of EHR for clinical trials. Then we defined a semantic interoperability framework in order to enable the reuse of EHR clinical data and implemented a mediator that transforms CDISC Operational Data Model (ODM) XML into proprietary XML document templates of different EHR solutions and vice-versa. Implementing electronic data capture for biomedical research within EHR eliminates redundant data entry, thus improving data quality and processing speed. Moreover, unlike other initiatives such as IHE integration profile "Retrieve Form for Data Capture" (RFD), the REUSE approach ensures that all clinical data is kept in the EHR whatever the context of data capture is.


Subject(s)
Clinical Trials as Topic , Medical Records Systems, Computerized , Biomedical Research/organization & administration , Database Management Systems , Humans , Medical Records Systems, Computerized/standards
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