MIRACOLIX-Tools

Informatics for Integrating Biology and the Bedside (i2b2) is a project sponsored in the USA by the National Institutes of Health (NIH), which has been run as the National Center for Biomedical Computing (NCBC) since 2004 as part of the NIH Roadmap for Medical Research. i2b2 is an extensible open source tool suite that is now successfully used in numerous international research networks, either as a single implementation for hospital-based data integration or as a node in a research network.

Within the MIRACUM DIC, i2b2 is provided as a platform for feasibility studies, cohort identification and support in patient recruitment.

TranSMART is a translational research platform. As a database with integrated analysis tools, it can be used to analyze both clinical and genomic data. It is an open source data warehouse that stores large amounts of data so that it can be shared for translational research. The platform offers, among other things, more than 30 predefined workflows for the analysis and graphical representation of study data and is convincing in its application due to its graphical user interface.

For more information on tranSMART:

• MIRACUM tranSMART Website [in German]

The open source tool cBioPortal is another translational research platform for interactive exploration of multidimensional cancer genomics datasets. Developed by Memorial Sloan Kettering Cancer Centers (MSKCC), cBioPortal provides a web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal’s intuitive web interface provides access to complex genomic profiles without the need for bioinformatics skills.

OHDSI is a global open-science community with the aim of transferring available observation data (e.g. diagnoses, procedures, laboratory values, measurements, medication) from a patient treatment into a standardized format and thus being able to use them internationally for research. The core component of the OHDSI software framework is the OMOP Common Data Model, which serves as the data basis. Data is stored in a standardized format and vocabulary such as SNOMED, LOINC or RxNorm. The OHDSI Community provides a large portfolio of open source components for characterizing cohorts, but also for evaluation, analysis and prediction.

In everyday medical practice, diverse imaging procedures are producing ever-increasing numbers of different medical images, volume data sets and image sequences at a wide variety of locations. In order to be able to answer well-founded questions for patient care or research background on the basis of the images, the demands on the quality of the data and often the need for examples for comparisons are very high. Since most image data is not only extremely heterogeneous, but also very distributed in terms of its storage location, experiments at the University Hospital often cannot benefit from the data treasure of other locations.

The XNAT project focuses on enabling scientists to archive and exchange image and video (meta-)data. At the same time, tools for automatic quality control as well as for the preparation of the data are provided to ensure centralized analysis in connection with the other systems and repositories.

Thus, research questions can now be answered holistically and in the best possible way, taking into account all existing (patient) data.

More information on XNAT:

• What is XNAT (YouTube Video)
• Marcus DS et al. – The Extensible Neuoimaging Archive Toolkit

In order to use clinical data for research purposes from medical departments, hospitals and other medical facilities, research applications must be submitted and checked by various committees before data can be made accessible for researchers.

This application process is still not harmonized. To overcome this, the Medical Informatics Group as part of MIRACUM is currently developing a tool that assists and simplifies the process of project proposal management named ProSkive. The entire application process can be tracked and scientists can easily apply for biomaterial or clinical data via a web interface. Thus, by using innovative methods and technologies, all steps from project proposal to project closure are comprehensible for all parties involved and easily adaptable to different needs. By December 2020, six releases of ProSkive have been distributed to the MIRACUM partner sites.

More information on ProSkive

• ProSkive Website

The E-PIX® (Enterprise Identifier Cross-Referencing) Service allows a precise management of person-identifying data (PII) including linkage of patient’s records in central and federated scenarios. It follows the principles of a master patient index in order to identify and match persons from single or federated study sites. This identity-management includes the correction of synonym errors – when data of one person are stored in at least two independent patient records. The probabilistic record linkage process is performed using demographic information (e.g. first name, surname, birthdate) and/or local identifiers (e.g. insurance or hospital case number). In addition, Privacy Preserving Record Linkage (PPRL) based on bloom filters is supported. E-PIX® is applied at a large number of MII-sites and is provided by the Trusted Third Party of University Medicine Greifswald under open-source license (AGPLv3).

More information on E-PIX®:

• E-PIX® Website
• Hampf C et al. – Assessment of scalability and performance of the record linkage tool E-PIX^® in managing multi-million patients in research projects at a large university hospital in Germany
• Live-Demo

In order to ensure and support transparent data integration and decision making for Molecular Tumor Boards (MTBs) across the MIRACUM sites, we have developed the MIRACUM-Pipe.

As part of the MIRACOLIX tool box, the MIRACUM site Frankfurt develops the components to implement a consortium-wide federated search. This is a connector component for federated searches (CC-FS) on the one hand, and a corresponding querybroker component on the other hand. The querybroker is linked with ProSkive as well as different graphical querybuilders. Currently, OHDSI ATLAS and i2b2 are provided, but thanks to a generic approach, other querybuilders can be connected with reasonable effort. Unlike the centrally deployed querybroker, the CC-FS instances are integrated at the MIRACUM partner sites and are connected to the data management systems on site. Depending on the query schema, CC-FS relays the query to the responsible data management system and gathers the results to make them available in the consortium – given the appropriate consent. The MIRACUM Federated Authentication Service (FAS) is used to authenticate the components.

In clinical research, in addition to medical data that are available in standard terminologies (e.g., ICD10, OPS), data that are not standardized (e.g., laboratory analytes) are also required. To enable interchangeability or joint analysis of these data, these data must be mapped to a standard (e.g. in the case of laboratory data, to LOINC).

However, manual mapping is a very time-consuming task. Matching such codes requires not only fundamental terminological knowledge, but also good knowledge of the conditions at the respective site and requires constant exchange of information with colleagues. Manual maintenance of code lists is not expedient.

For this reason, a semi-automatic approach for the creation of such mappings was developed within the framework of MIRACUM. The MIRACUM Mapper is a generic tool that allows collaborative and asynchronous creation and editing of mappings. In its first application, approximately 10,000 laboratory codes were mapped to the LOINC standard.

Health Discovery is a text mining and machine learning platform from Averbis GmbH, a German company specialised for knowledge and content technologies in the biomedical field. Health Discovery processes large amounts of clinical narratives, analyses their textual content and produces a structured output consisting of of codes (e.g. ICD-10, TNM) in context (e.g. negation). It is based on the Apache UIMA (Unstructured Information Management Architecture) framework, which allows the addition of custom extraction components, as well as the use of external terminologies. Due to its REST interface, Health Discovery can easily be integrated in existing information architectures. In MIRACUM, Averbis Health supports the data integration centres to acquire coded information from textual sources in clinical information systems.

The MIRACUM consortium requires a central meta data repository (M-MDR) to tackle interoperability challenges and support data harmonization processes within the network. This central M-MDR includes all core data sets defined through the german Medical Informatics Initiative (MII) as well as the consortium and will continuously be extended depending on current use cases. Researchers can utilize these harmonized data sets to define queries for data inquiries. Consequently, the M-MDR represents a major component for federated searches across institutional boundaries. Furthermore, the meta data repository can be used to assist different tasks, like ETL (extract, transform, load) processes or data quality reports. In conclusion, data integration and data exchange across partner sites shall be simplified with the support of the central M-MDR.

The commercial wiki software Confluence from Atlassian is used as a cross-site collaboration platform in the MIRACUM consortium. This is used in particular to organize and document joint work meetings and to create reports collaboratively.
Confluence Webseite

The MIRACUM GitLab Repo was set up for joint software development within the consortium. This ensures the version management of software projects.
GitLab Webseite

The open source software Zulip is used for communication within the consortium. This offers the possibility of exchanging information on specific topics asynchronously and across sites. In addition, it can be used as a chat tool of an individual site for internal communication.
Zulip Webseite