MII - Medical Informatics Initiative

Motivation:

The aim of the medical informatics initiative is to ensure that, in future, each doctor, patient and researcher has access to the information they require – while simultaneously allowing individuals to maintain control over their personal data.

This will lead to more precise diagnostics, and better treatment decisions. It will yield new insights for research and medicine. And it will improve patient care and help combat diseases more effectively. Specifically, the initiative is about harnessing the flood of data generated every single day in healthcare and research environments – to the benefit of individual patients, to better understand illnesses, and to tailor treatments to the needs of the individual.

The goal is to establish a way to exchange research and care data across university hospitals. If it proves successful – with the help of funding from BMBF – it will open up entirely new horizons. The solutions that will be developed are expected to create added value across the health system.

Description:

The medical informatics initiative was created to close the gap between research and healthcare. All of Germany’s university hospitals have joined forces with research institutions, businesses, health insurers, and patient advocacy groups to create a framework that harnesses research findings to the direct benefit of patients. The German Federal Ministry of Education and Research (BMBF) is investing around 160 million euros in the programme through 2021. The digitisation of medicine is creating new opportunities for patient care and research; BMBF launched its medical informatics initiative to make the most of this transformation. In the initiative’s first phase, university hospitals and partner organisations will establish and link data integration centres. These centres will allow research and healthcare data to be aggregated and integrated across multiple entities and sites. At the same time, innovative IT solutions for specific medical applications will be developed to demonstrate the benefits of high-tech digital healthcare services and infrastructures.

Participating university hospitals and their partners have formed consortia. These are tasked with developing strategies for shared data use and exchange. They will subsequently establish the data integration centres, and create IT solutions for concrete use cases.

These activities are coordinated by a national steering committee (NSG), to ensure the interoperability of IT systems and data integration centres between the consortia. In addition, a dedicated coordination office supports cross-consortia collaboration. This office is managed jointly by TMF – Technology, Methods and Infrastructure for Networked Medical Research, MFT (Medizinischer Fakultätentag – an association of German medical faculties), and VUD (Verband der Universtitätsklinika Deutschlands, which represents 33 university hospitals in Germany).

Web page: https://www.medizininformatik-initiative.de/en

Funding codes:
  • BMBF
Funding details:
No funding details specified

Related items

SMITH - Smart Medical Information Technology for Healthcare
No description specified

Programme: MII - Medical Informatics Initiative

Public web page: https://www.smith.care/

Start date: 1st Jan 2018

POLAR - Polypharmacy, Drug Interactions, Risks

The aim of the project is to use methods and processes of the Medical Informatics Initiative (MII) to contribute to the detection of health risks in patients with polypharmacy. Polypharmacy occurs especially in elderly patients with multimorbidity. Polypharmacy associated with an increased risk for medication errors and drug-drug or drug-disease interactions, which either reduce or intensify the desired effect of individual active substances or lead to undesired adverse drug effects (ADE). In the ...

Programme: MII - Medical Informatics Initiative

Public web page: https://www.medizininformatik-initiative.de/en/POLAR

FHIR Testdata
POLAR - Polypharmacy, Drug Interactions, Risks

Die Testdaten

  • sind von klinischen Experten frei erfunden (manuell, synthetisch) und haben keinen Bezug zu realen Personen
  • sind über ein an der Universität Leipzig entwickeltes Werkzeug aus Zuarbeiten verschiedener Expertengruppen aus einem MS Excel Format heraus erzeugt worden
  • stehen in der Form als HL7® FHIR® Bundles im json Format zur freien Verwendung;
  • sind für die direkte Übernahme in einen FHIR Server geeignet
  • entsprechen weitestgehend dem Kerndatensatz der MII zum Stand 9.11.2020 ...

Submitter: Frank A. Meineke

Investigation: Testdata

Resources: FHIR Testdata UKB, FHIR Testdata UKE, FHIR Testdata UKFAU, FHIR Testdata UKFR, FHIR Testdata UKSH

Study type: Not specified

PhenoMan Evaluation with Synthetic FHIR Data
SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

We evaluated if the PhenoMan returns correct/complete result sets and if it is working with real data. To simulate a FHIR health data store with real data we used Synthea(TM) to generate a large data set and imported it into a HAPI FHIR JPA Server. Based on the synthetic data set we developed ten example queries with different structure and complexity with PhenoMan and SQL. We compared the results of the queries in means of execution time and equality of results.

The detailed steps of the evaluation ...

Submitter: Christoph Beger

Investigation: Ontology-based Phenotyping

Resources: PhenoMan Evaluation - Synthetic FHIR Data

Study type: Not specified

Ontological Modelling of Basic Eligibility Criteria
SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group
No description specified

Submitter: Alexandr Uciteli

Investigation: Ontology-based Phenotyping

Resources: Basic Eligibility Criteria of an Example Blood Pressure Study

Study type: Not specified

Ontological Modelling of Type 2 Diabetes Mellitus (T2DM) Phenotype
SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group
No description specified

Submitter: Alexandr Uciteli

Investigation: Ontology-based Phenotyping

Resources: Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan)

Study type: Not specified

FHIR Testdata UKSH
POLAR - Polypharmacy, Drug Interactions, Risks

Autoren bzw. Ansprechpartner für diesen Datensatz sind: Universitätsklinikum Schleswig-Holstein, Campus Kiel: Prof. Ingolf Cascorbi, Dr. Ruwen Böhm, Felix Rottmann, Dr. Claudia Bulin

Submitter: Frank A. Meineke

Resource type: Experimental Assay Type

Technology type: Technology Type

Investigation: Testdata

Study: FHIR Testdata

FHIR Testdata UKFAU
POLAR - Polypharmacy, Drug Interactions, Risks

Autoren bzw. Ansprechpartner für diesen Datensatz sind: Universität Erlangen-Nürnberg: Prof. Fromm, Prof. Maas, Pauline Dürr, Melanie Then, Wahram Andrikyan

Submitter: Frank A. Meineke

Resource type: Experimental Assay Type

Technology type: Technology Type

Investigation: Testdata

Study: FHIR Testdata

FHIR Testdata UKFR
POLAR - Polypharmacy, Drug Interactions, Risks

Autoren bzw. Ansprechpartner für diesen Datensatz sind: Universität Freiburg: Thomas Maulhardt, Prof. Martin Boeker

Submitter: Frank A. Meineke

Resource type: Experimental Assay Type

Technology type: Technology Type

Investigation: Testdata

Study: FHIR Testdata

FHIR Testdata UKB
POLAR - Polypharmacy, Drug Interactions, Risks

Autoren bzw. Ansprechpartner für diesen Datensatz sind: Universität Bonn: Anna Böhmer, Prof. Ulrich Jaehde Universitätsklinikum Bonn: Katharina Karsten Dafonte, Dr. med. Martin Coenen, Prof. Hartmann Bonn: Fr. Karsten Dafonte, Dr. med. Coenen, Prof. Hartmann

Submitter: Frank A. Meineke

Resource type: Experimental Assay Type

Technology type: Technology Type

Investigation: Testdata

Study: FHIR Testdata

FHIR Testdata UKE
POLAR - Polypharmacy, Drug Interactions, Risks

Autoren bzw. Ansprechpartner für diesen Datensatz sind: Universitätsklinikum Hamburg-Eppendorf: Dr. Jan Gewehr, Dr. Friederike Salman, Yvonne Lemke, Norman Freier, Dr. Steffen Härterich

Submitter: Frank A. Meineke

Resource type: Experimental Assay Type

Technology type: Technology Type

Investigation: Testdata

Study: FHIR Testdata

PhenoMan Evaluation - Synthetic FHIR Data
SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

This assay bundles all synthetic FHIR data of the PhenoMan evaluation. The data arised from a subset of a Synthea(TM) generated data set. We truncated some resource types like Encounter and Provider to reduce the size of the data set and to speed up the import in a FHIR health data store.

Submitter: Christoph Beger

Resource type: Result Dataset of Clinical Study

Technology type: Technology Type

Investigation: Ontology-based Phenotyping

Study: PhenoMan Evaluation with Synthetic FHIR Data

Basic Eligibility Criteria of an Example Blood Pressure Study
SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group
No description specified

Submitter: Alexandr Uciteli

Biological problem addressed: Model Analysis Type

Investigation: Ontology-based Phenotyping

Study: Ontological Modelling of Basic Eligibility Crit...

Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan)
SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

We modelled the algorithm for determining Type 2 Diabetes Mellitus (T2DM) cases presented by PheKB.org using Phenotype Manager (PhenoMan).

Submitter: Alexandr Uciteli

Biological problem addressed: Model Analysis Type

Investigation: Ontology-based Phenotyping

Study: Ontological Modelling of Type 2 Diabetes Mellit...

Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas.
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles … are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.

Authors: A. Uciteli, C. Beger, J. Wagner, A. Kiel, F. A. Meineke, S. Staubert, M. Lobe, R. Hansel, J. Schuster, T. Kirsten, H. Herre

Date Published: 24th May 2021

Publication Type: Journal article

Ontological modelling and FHIR Search based representation of basic eligibility criteria
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Planning clinical studies to check medical hypotheses requires the specification of eligibility criteria in order to identify potential study participants. Electronically available patient data allows … to support the recruitment of patients for studies. The Smart Medical Information Technology for Healthcare (SMITH) consortium aims to establish data integration centres to enable the innovative use of available healthcare data for research and treatment optimization. The data from the electronic health record of patients in the participating hospitals is integrated into a Health Data Storage based on the Fast Healthcare Interoperability Resources standard (FHIR), developed by HL7. In SMITH, FHIR Search is used to query the integrated data. An investigation has shown the advantages and disadvantages of using FHIR Search for specifying eligibility criteria. This paper presents an approach for modelling eligibility criteria as well as for generating and executing FHIR Search queries. Our solution is based on the Phenotype Manager, a general ontological phenotyping framework to model and calculate phenotypes using the Core Ontology of Phenotypes.

Authors: A. Uciteli, C. Beger, J. Wagner, T. Kirsten, F. A. Meineke, S. Staubert, M. Lobe, H. Herre

Date Published: 26th Apr 2021

Publication Type: Journal article

Integration of allergy documentation into an interoperable archiving and communication platform to improve patient care and clinical research at the Jena University Hospital
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

As part of the digitalization strategy for medical documentation, we introduced a vendor-neutral archive (VNA) at the Jena University Hospital. The VNA provides data based on interoperable formats for … all clinical systems and for communication with other actors as well as for secondary data use. HL7 FHIR is used as a standard for structuring individual data. Using the example of allergy documentation, the paper describes objectives, work status, and experiences from several sub-projects currently being pursued in Jena to establish FHIR. Challenges in information modelling, semantic annotation, connection of clinical sub-systems and integration of FHIR resources in archiving structures and processes are discussed and the necessary cooperation for profiling technical standards is indicated.

Authors: Henner M. Kruse, Alexander Helhorn, Lo An Phan-Vogtmann, Julia Palm, Eric Thomas, Andreas Iffland, Andrew Heidel, Susanne Müller, Kutaiba Saleh, Karsten Krohn, Martin Specht, Michael Hartmann, Katrin Farker, Cord Spreckelsen, Andreas Henkel, Andre Scherag, Danny Ammon

Date Published: 26th Apr 2021

Publication Type: Journal article

Ontological representation, classification and data-driven computing of phenotypes.
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and … epidemiological studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term 'phenotype' has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimisation. In the context of a methodological use case 'phenotype pipeline' (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. RESULTS: In this article, we present a Core Ontology of Phenotypes (COP) and the software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model, classify and compute phenotypes from already available data. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated with selected phenotypes including SOFA score, socio-economic status, body surface area and WHO BMI classification based on available medical data. CONCLUSIONS: We developed a novel ontology-based method to model phenotypes of living beings with the aim of automated phenotype reasoning based on available data. This new approach can be used in clinical context, e.g., for supporting the diagnostic process, evaluating risk factors, and recruiting appropriate participants for clinical and epidemiological studies.

Authors: A. Uciteli, C. Beger, T. Kirsten, F. A. Meineke, H. Herre

Date Published: 21st Dec 2020

Publication Type: Journal article

Medical Information Extraction in the Age of Deep Learning
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: Udo Hahn, Michel Oleynik

Date Published: 21st Aug 2020

Publication Type: Journal article

Effect size estimates from umbrella designs: Handling patients with a positive test result for multiple biomarkers using random or pragmatic subtrial allocation
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: Miriam Kesselmeier, Norbert Benda, André Scherag

Date Published: 14th Aug 2020

Publication Type: Journal article

What Makes a Top-Performing Precision Medicine Search Engine?
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: Jimmy Huang, Yi Chang, Xueqi Cheng, Jaap Kamps, Vanessa Murdock, Ji-Rong Wen, Yiqun Liu, Erik Faessler, Michel Oleynik, Udo Hahn

Date Published: 25th Jul 2020

Publication Type: InProceedings

GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

The lack of publicly available text corpora is a major obstacle for progress in clinical natural language processing, for non-English speaking countries in particular. In this work, we present GGPONC … (German Guideline Program in Oncology NLP Corpus), a freely distributable German language corpus based on clinical practice guidelines in the field of oncology. The corpus is one of the largest corpora of German medical text to date. It does not contain any patient-related data and can therefore be used without data protection restrictions. Moreover, it is the first corpus for the German language covering diverse conditions in a large medical subfield. In addition to the textual sources, we provide a large variety of metadata, such as literature references and evidence levels. By applying and evaluating existing medical information extraction pipelines for German text, we are able to draw comparisons for the use of medical language to other medical text corpora.

Authors: F. Borchert, C. Lohr, L. Modersohn, T. Langer, M. Follmann, J. P. Sachs, U. Hahn, M. P. Schapranow

Date Published: 13th Jul 2020

Publication Type: Misc

Problems in FAIRifying Medical Datasets.
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Despite their young age, the FAIR principles are recognised as important guidelines for research data management. Their generic design, however, leaves much room for interpretation in domain-specific … application. Based on practical experience in the operation of a data repository, this article addresses problems in FAIR provisioning of medical data for research purposes in the use case of the Leipzig Health Atlas project and shows necessary future developments.

Authors: M. Lobe, F. Matthies, S. Staubert, F. A. Meineke, A. Winter

Date Published: 16th Jun 2020

Publication Type: Journal article

An Evolutionary Approach to the Annotation of Discharge Summaries.
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

We here describe the evolution of annotation guidelines for major clinical named entities, namely Diagnosis, Findings and Symptoms, on a corpus of approximately 1,000 German discharge letters. Due to … their intrinsic opaqueness and complexity, clinical annotation tasks require continuous guideline tuning, beginning from the initial definition of crucial entities and the subsequent iterative evolution of guidelines based on empirical evidence. We describe rationales for adaptation, with focus on several metrical criteria and task-centered clinical constraints.

Authors: C. Lohr, L. Modersohn, J. Hellrich, T. Kolditz, U. Hahn

Date Published: 16th Jun 2020

Publication Type: Journal article

FHIR Testdata UKFAU
POLAR - Polypharmacy, Drug Interactions, Risks

HL7® FHIR® Ressourcen im JSON Format

Creator: Frank A. Meineke

Submitter: Frank A. Meineke

Data file type: Clinical Data

Download
FHIR Testdata UKB
POLAR - Polypharmacy, Drug Interactions, Risks

HL7® FHIR® Ressourcen im JSON Format

Creator: Frank A. Meineke

Submitter: Frank A. Meineke

Data file type: Clinical Data

Download
FHIR Testdata UKSH
POLAR - Polypharmacy, Drug Interactions, Risks

HL7® FHIR® Ressourcen im JSON Format

Creator: Frank A. Meineke

Submitter: Frank A. Meineke

Data file type: Clinical Data

Download
FHIR Testdata UKFR
POLAR - Polypharmacy, Drug Interactions, Risks

HL7® FHIR® Ressourcen im JSON Format

Creator: Frank A. Meineke

Submitter: Frank A. Meineke

Data file type: Clinical Data

Download
FHIR Testdata UKE
POLAR - Polypharmacy, Drug Interactions, Risks

HL7® FHIR® Ressourcen im JSON Format

Creator: Frank A. Meineke

Submitter: Frank A. Meineke

Data file type: Clinical Data

Download
T2DM Ontology
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

T2DM Phenotype Algorithm Specification Ontology (PASO) developed using PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
T2DM Tabular Representation
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

The tabular representation of the T2DM phenotype algorithm generated by PhenoMan using the T2DM ontology

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
Eligibility Criteria Ontology for an Example Blood Pressure Study
Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare
No description specified

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
T2DM Case 5 Reasoner Report
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
T2DM Case 4 Reasoner Report
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
Ontological Modelling and Reasoning of Phenotypes
LHA - Leipzig Health Atlas, SMITH - Smart Medical Information Technology for Healthcare, Onto-Med Research Group

Presentation on JOWO/ODLS 2019 in Graz

Creators: Alexandr Uciteli, Christoph Beger

Submitter: Christoph Beger

Download
Danny Ammon

Projects: SMITH - Smart Medical Information Technology for Healthcare, POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: Universitätsklinikum Jena

https://orcid.org/0000-0001-8960-7316
Wahram Andrikyan

Projects: POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: Friedrich-Alexander Universität Erlangen-Nürnberg

Christoph Beger adminproject_administratorasset_housekeeper

Projects: LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare, COVID-19 Leipzig, LIFE Child, LIFE - Leipzig Research Center for Civilization Diseases, Project Test Demonstrator

Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universitätsklinikum Leipzig, AöR, invalid

https://orcid.org/0000-0002-1166-0368
Claudia Bulin

Projects: POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: University Medical Center Schleswig-Holstein

Ruwen Böhm

Projects: POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: University Medical Center Schleswig-Holstein

Anna Böhmer

Projects: POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: Universität Bonn

Ingolf Cascorbi

Projects: POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: University Medical Center Schleswig-Holstein

Martin Coenen

Projects: POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: Universitätsklinikum Bonn, AöR

Philipp Daumke

Projects: SMITH - Smart Medical Information Technology for Healthcare

Institutions: Averbis GmbH Freiburg

Armin de Greiff

Projects: SMITH - Smart Medical Information Technology for Healthcare

Institutions: Universitätsklinikum Essen

Joint Ontology Workshops (JOWO) 2019

The Joint Ontology WOrkshops (JOWO) is a venue of workshops that, together, address a wide spectrum of topics related to ontology research, ranging from Cognitive Science to Knowledge Representation, Natural Language Processing, Artificial Intelligence, Logic, Philosophy, and Linguistics.

Start Date: 23rd Sep 2019

End Date: 25th Sep 2019

Event Website: https://www.iaoa.org/jowo/2019/

Country:  Austria

City: Graz

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Health Atlas

The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields.

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