Legal assessment tool (LAT): an interactive tool to address privacy and data protection issues for data sharing.

BACKGROUND: In an unprecedented rate data in the life sciences is generated and stored in many different databases. An ever increasing part of this data is human health data and therefore falls under data protected by legal regulations. As part of the BioMedBridges project, which created infrastructures that connect more than 10 ESFRI research infrastructures (RI), the legal and ethical prerequisites of data sharing were examined employing a novel and pragmatic approach. METHODS: We employed concepts from computer science to create legal requirement clusters that enable legal interoperability between databases for the areas of data protection, data security, Intellectual Property (IP) and security of biosample data. We analysed and extracted access rules and constraints from all data providers (databases) involved in the building of data bridges covering many of Europe's most important databases. These requirement clusters were applied to five usage scenarios representing the data flow in different data bridges: Image bridge, Phenotype data bridge, Personalised medicine data bridge, Structural data bridge, and Biosample data bridge. A matrix was built to relate the important concepts from data protection regulations (e.g. pseudonymisation, identifyability, access control, consent management) with the results of the requirement clusters. An interactive user interface for querying the matrix for requirements necessary for compliant data sharing was created. RESULTS: To guide researchers without the need for legal expert knowledge through legal requirements, an interactive tool, the Legal Assessment Tool (LAT), was developed. LAT provides researchers interactively with a selection process to characterise the involved types of data and databases and provides suitable requirements and recommendations for concrete data access and sharing situations. The results provided by LAT are based on an analysis of the data access and sharing conditions for different kinds of data of major databases in Europe. CONCLUSIONS: Data sharing for research purposes must be opened for human health data and LAT is one of the means to achieve this aim. In summary, LAT provides requirements in an interactive way for compliant data access and sharing with appropriate safeguards, restrictions and responsibilities by introducing a culture of responsibility and data governance when dealing with human data.

Clinical Trial Information Mediator.

For research in biomedical sciences, cross-domain searches through several different databases are an increasingly necessary task that often becomes a time consuming and labour-intense process. This is especially the case when different domain databases have to be combined, for example combined searches in clinical trials registries, publication databases and research databases. The Clinical Trial Information Mediator (CTIM) addresses this problem and offers a novel way for the combined search in ClinicalTrials.gov, PubMed and BioSamples. CTIM was developed based on a requirements analysis and implemented using open source technology. A search engine with a graphical user interface was developed in order to search linked data in the three databases ClinicalTrials.gov, PubMed and BioSamples; thereby enabling CTIM to bridge the gap between different knowledge domains of clinical trials, publications of research results and biosamples/genetic information. CTIM was applied in three use cases demonstrating that information retrieval could be considerably improved in sense for complex queries. These use cases show that more relevant results were obtained and more associated publications and biosamples could be retrieved in comparison to a separate single search. Main advantages of CTIM are identifying related information between clinical trials and publications employing a clinical trial centred kind of search, simplified access to its databases and thus reduced search time. In addition it can be used by researchers without prior training because of the intuitive usage.

Cost-benefit assessment of using electronic health records data for clinical research versus current practices: Contribution of the Electronic Health Records for Clinical Research (EHR4CR) European Project.

INTRODUCTION: The widespread adoption of electronic health records (EHR) provides a new opportunity to improve the efficiency of clinical research. The European EHR4CR (Electronic Health Records for Clinical Research) 4-year project has developed an innovative technological platform to enable the re-use of EHR data for clinical research. The objective of this cost-benefit assessment (CBA) is to assess the value of EHR4CR solutions compared to current practices, from the perspective of sponsors of clinical trials. MATERIALS AND METHODS: A CBA model was developed using an advanced modeling approach. The costs of performing three clinical research scenarios (S) applied to a hypothetical Phase II or III oncology clinical trial workflow (reference case) were estimated under current and EHR4CR conditions, namely protocol feasibility assessment (S1), patient identification for recruitment (S2), and clinical study execution (S3). The potential benefits were calculated considering that the estimated reduction in actual person-time and costs for performing EHR4CR S1, S2, and S3 would accelerate time to market (TTM). Probabilistic sensitivity analyses using Monte Carlo simulations were conducted to manage uncertainty. RESULTS: Should the estimated efficiency gains achieved with the EHR4CR platform translate into faster TTM, the expected benefits for the global pharmaceutical oncology sector were estimated at €161.5m (S1), €45.7m (S2), €204.5m (S1+S2), €1906m (S3), and up to €2121.8m (S1+S2+S3) when the scenarios were used sequentially. CONCLUSIONS: The results suggest that optimizing clinical trial design and execution with the EHR4CR platform would generate substantial added value for pharmaceutical industry, as main sponsors of clinical trials in Europe, and beyond.

Using electronic health records for clinical research: the case of the EHR4CR project.

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.

Extension of the primary care research object model (PCROM) as clinical research information model (CRIM) for the "learning healthcare system".

BACKGROUND: Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. The EU funded project TRANSFoRm aims to create a "Learning Healthcare System" at a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy. The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches. METHODS: Workflow descriptions and corresponding data objects of two clinical use cases (Gastro-Oesophageal Reflux Disease and Type 2 Diabetes) were described in UML activity diagrams. The components of activity diagrams were mapped to information objects of PCROM (Primary Care Research Object Model) and BRIDG (Biomedical Research Integrated Domain Group) and evaluated. The class diagram of PCROM was adapted to comply with workflow descriptions. RESULTS: The suitability of PCROM, a primary care information model already used for clinical trials, to act as an information model for TRANSFoRm was evaluated and resulted in its extension with 14 new information object types, two extensions of existing objects and the introduction of two new high-ranking concepts (CARE area and ENTRY area). No PCROM component was redundant. Our result illustrates that in primary care based research an important but underestimated portion of research activity takes place in the area of care (e.g. patient consultation, screening, recruitment and response to adverse events). The newly introduced CARE area for care-related research activities accounts for this shift and includes Episode of Care and Encounter as two new basic elements. In the ENTRY area different aspects of data collection were combined, including data semantics for observations, assessment activities, intervention activities and patient reporting to enable case report form (CRF) based data collection combined with decision support. CONCLUSIONS: Research with primary care data needs an extended information model that covers research activities at the care site which are characteristic for primary care based research and the requirements of the complicated data collection processes.

Protocol feasibility workflow using an automated multi-country patient cohort system.

The Electronic Health Record for Clinical Research (EHR4CR) project aims to improve the current process of clinical trials, providing a technological platform that supports the design and execution of trials. For the protocol feasibility scenario, the system currently allows the user to create a set of in-/exclusion criteria to find patients matching these criteria across sites located in several countries. The automated multi-country patient cohort system developed in EHR4CR implies substantial changes on the current protocol feasibility process, which will be reflected in this study.