In the SMITH medical informatics consortium, more than 300 clinical, epidemiological and systems medicine employees are working to link research and healthcare systematically for the first time. For this purpose, the data generated daily in routine care are processed with the patients' consent and made available to medical research in a standardized form. This enables researchers to better understand and analyse healthcare processes. Patients benefit from reliable research results, more precise diagnoses and better treatments.
The prerequisites for linking healthcare data with research data are new technical interfaces between healthcare and biomedical research at clinical sites. To this end, the 19 consortium partners are jointly establishing a data architecture that enables interoperable data use from patient care and research across the boundaries of institutions and sites. Within this framework, the university hospitals participating in the consortium have established sustainable data integration centers (DIC) in Aachen, Bonn, Essen, Halle, Hamburg, Jena and Leipzig. The network partners Ruhr University Bochum, the Düsseldorf University Hospital and the University Medical Center Rostock are preparing to establish a DIC.
The consortium demonstrates the functionality and added value of intelligent and responsible data use through one methodological use case and two clinical use cases in the areas of intensive care and infectious medicine.
SMITH is one of four consortia of the Medical Informatics Initiative (MII) funded by the Federal Ministry of Education and Research (BMBF) and is supported by the BMBF in the development and networking phase from 2018 to 2022.
SMITH at a glance:
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1 methodical use case to support clinical evaluation projects
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2 clinical use cases for targeted care in intensive and infectious medicine
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19 partners from science and industry -
Partners include 9 German university hospitals, 4 Universities, 4 industrial partners and 2 non-university research institutions
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Over 300 project members
- Approx. EUR 55 million total funding volume (2018 – 2022)
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Approx. EUR 55 million total funding volume (2018 – 2022)
Die MII baut seit 2018 Dateninfrastrukturen an den Universitätskliniken auf. Anhand vielfältiger Anwendungsfälle – von der Intensiv- bis zur Krebsmedizin – demonstrierten die MII-Partner bereits den Mehrwert ihrer IT-Lösungen in der Praxis. Im Fokus der Ausbau- und Erweiterungsphase (2023-2026) steht eine erweiterte Zusammenarbeit zwischen den Universitätskliniken und deren Kooperation mit neuen Partnern, insbesondere auch aus der regionalen Versorgung.
Data integration centres
Seven of the ten university medical sites participating in the consortium have established a Data Integration Center (DIC) so far, and three network partners are preparing the structure. The centers enable the cross-institutional and cross-site use of digital health data from patient care and biomedical research.
The DIC act as intermediaries in advising on the use of data, organizing corresponding projects and facilitating the provision of data. To this end, they establish interoperable directories with quality-assured, internationally harmonized data and metadata. These are made available anonymously via trustees. Data protection and data security have the highest priority.
The Data Integration Centers are established with identical functionality. All centers are embedded at university medical sites with access to patient data. Within the scope of their work with clinical and research data, the DIC contribute to the establishment of a research-compatible electronic patient record for the German health care system.
The added value of this data use is demonstrated by the consortium in one methodological and two clinical use cases.
Use cases
Methodological Use Case: PheP – Phenotyping Pipeline supporting Clinical Evaluation Projects
In the methodological Use Case Phenotyping Pipeline, PheP for short, SMITH develops innovative data analytical methods that automatically extract medical information from electronic patient records. Evaluation projects and calculations on existing data lead to ever new patient-related information and to a differentiated characterization of human attributes, so-called phenotypes. The rich data pool enables long-term optimization of clinical research and patient care.
SMITH demonstrates the procedure in two clinical use cases.
Clinical Use Case 1: ASIC - Algorithmic Surveillance in Intensive Care
With the ASIC Use Case, the consortium promotes the improvement of patient care by using already existing clinical routine data. This will be shown using the example of the therapy of patients with Acute Respiratory Distress Syndrome (ARDS), a disease from which about 40 percent of all affected patients still die today. The ASIC App developed for this purpose functions as an early warning system by alerting doctors to potential ARDS before the patient's condition threatens to become critical.
Clinical Use Case 2: HELP – Guideline-based Use of Antibiotics in Infectious Medicine
The HELP Use Case focuses on the guideline-based and recommended use of antibiotics for early and targeted control of certain bacterial infections. The main focus lies on the support of infectiology in normal and intensive care units using the HELP App developed for this purpose. This provides medical staff with rapid information and recommendations for responsible antibiotic therapy in staphylococcal bloodstream infections.
Data usage concept
Data is used locally via the Data Integration Centers (DIC), which have access to the Hospital Information Systems (HIS) and thus to the use of patient data. The patient data is individually analyzed and commented on in the hospital. This data can only be accessed by authorized employees of the Data Integration Centers via the locally operating HIS system. Research into patient data is only possible with the patient's consent. In this respect, the Data Integration Centers set up an independent trustee office.
Measures to strengthen medical informatics
- Conception of coordinated, joint training, advanced training and continuing education modules
- Offers for curricula in the area of "Master of Science" (M.Sc.) medical informatics and in the postgraduate area
- Establishment of a professorship for Medical Informatics at the University Hospital Bonn
- Establishment of a professorship for Data Science at the Essen University Hospital
- Establishment of a professorship for Biomedical Data Science at the University Hospital Halle
- Establishment of a professorship for Applied Medical Informatics at the University Medical Center Hamburg-Eppendorf
- Establishment of a professorship for Medical Informatics at the Jena University Hospital
- Establishment of a professorship for Medical Data Science at the Leipzig University
- Establishment of junior research groups in connection with the establishment of professorships
Concept phase
The aim of the SMITH Consortium is to develop an innovative structure for cross-institutional networking and the exchange of research and care data between the funded sites and beyond the consortium.
The project proposal envisages that cooperating generic Data Integration Centers (DIC) will be established at the locations. The DICs will ensure the transfer of data from primary systems and the consolidation and preparation of data. A further task is to ensure data protection and data quality.
For the practical demonstration of the data exchange, methodological and clinical use cases have been conceptually developed to prove the effectiveness of the Data Integration Centers. Thus, a concept for a methodical Phenotyping Platform was developed, whose task is to build a new data set for specific human attributes, so-called phenotypes, from patient-related information. This rich data set will enable the support of clinical evaluation projects and in the long run a patient-centered care. In addition, the concept development for clinical use cases in the fields of intensive care and infectious medicine was performed.
In addition, a joint training, further education and continuing education module was designed for the locations, which offers similar and modular curricula in the "Master of Science" medical informatics area and in the postgraduate area. The project proposal was approved by the Federal Ministry of Education and Research (BMBF) in July 2017. Since 2018, the SMITH-Consortium is in the building and networking phase.
The aim of the SMITH Consortium is to develop an innovative structure for cross-institutional networking and the exchange of research and care data between the funded sites and beyond the consortium.
The project proposal envisages that cooperating generic Data Integration Centers (DIC) will be established at the locations. The DICs will ensure the transfer of data from primary systems and the consolidation and preparation of data. A further task is to ensure data protection and data quality.
For the practical demonstration of the data exchange, methodological and clinical use cases have been conceptually developed to prove the effectiveness of the Data Integration Centers. Thus, a concept for a methodical Phenotyping Platform was developed, whose task is to build a new data set for specific human attributes, so-called phenotypes, from patient-related information. This rich data set will enable the support of clinical evaluation projects and in the long run a patient-centered care. In addition, the concept development for clinical use cases in the fields of intensive care and infectious medicine was performed.
In addition, a joint training, further education and continuing education module was designed for the locations, which offers similar and modular curricula in the "Master of Science" medical informatics area and in the postgraduate area. The project proposal was approved by the Federal Ministry of Education and Research (BMBF) in July 2017. Since 2018, the SMITH-Consortium is in the building and networking phase.
