Department / Institute: Emergency Department

The AKTIN-Notaufnahmeregister is a standardized electronic infrastructure that makes electronically collected data from emergency admissions available for health reporting, quality assurance, and health services research. The special features of the registry are the use of routine data without additional effort for the treating staff and the decentralized infrastructure, which allows the data to be stored in the individual clinics and thus in the context of the treatment.

The aim of the AKTIN-Notaufnahmeregister is to optimize quality management in emergency departments and to improve/accelerate data availability for health reporting and health services research in acute and emergency medicine.

As part of the NUM 2.0 research project, 20 additional university and non-university emergency departments will be included in the project.
 

More information can be found on the website: https://aktin.org/

 

Department / Institute: Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School

This work package addresses all aspects related to the further development of a local (CoSurv-SmICS) as well as a central (CODEX dashboard) application designed to support in COVID-19 infection control and pandemic surveillance. Optimization of functions, deployment and usability together with a roll-out throughout the network will be fostered to facilitate COVID-19 infection control in the university medical centers of the network, allow continuous pandemic preparedness and early warning within the network, improve pandemic surveillance also at the national level by integrating relevant data from network partners and advance pandemic preparedness beyond the network. Relevant aggregated data sets, calculated in Co-Surv-SmICS, will be analyzed and made available within the NUM node.

Department / Institute: Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School

Development of an AI-based clinical decision support system that predicts severity in the case of COVID infection based on patient data. The decision support of the system is based on both clinical and OMICS data.

Department / Institute: Hannover Unified Biobank (HUB)

In order to meet the challenges of current and future pandemics as well as current research questions with high medical demands, a network is needed that can quickly focus the capabilities of university medicine on the particularly urgent and important tasks and carry out complex clinical studies itself. To this end, a Therapeutic Intervention Platform (NAPKON-TIP) is to be established based on the recruitment network successfully established in the National Pandemic Cohort Network (NAPKON) and the NUM infrastructures, in particular the NUM Clinical Epidemiology and Studies Platform (NUKLEUS). NAPKON-TIP is designed as a platform for adaptive clinical trials to facilitate the ongoing evaluation of new therapies for efficacy and safety in stratified populations. The focus of NAPKON-TIP is on adaptive trials, the specificity of which is that the therapies and subgroups included can be adjusted as new knowledge about the efficacy and safety of the treatments, as well as population stratification within or outside the platform study, suggests.

Department/Institute: Hannover Unified Biobank

NAPKON-TIP was designed as a platform for adaptive clinical trials based on the National Pandemic Cohort Network (NAPKON). The first use case of the NAPKON-TIP infrastructure entitled "Randomized assessment of Post-COVID-Syndrome treatments (RAPID) focuses on the clinical testing of various new drugs for the treatment of Post COVID Syndrome (PCS). Several underlying mechanisms for PCS have been identified, including viral persistence and reactivation, immune dysregulation, endothelial dysfunction and chronic tissue damage. RAPID has been designed to address multiple pathophysiological therapeutic domains, but will initially focus on the first planned domain of antiviral treatment to reduce tissue damage caused by persistent inflammation. Start of the first clinical trial "RAPID-REVIVE", in which an antiviral treatment will be tested, is planned for Q2 2024. It involves 11 study centers from the NAPKON network and the infrastructure core NUKLEUS. Further interventions and domains are planned to be added as part of this adaptive platform study.

Department / Institute: Hannover Unified Biobank (HUB)

Building on the successes of NAPKON in 2020 and 2021, national collaboration will continue across the three NAPKON cohorts to fulfill the mission of establishing a national collaborative infrastructure and making relevant contributions to the understanding and long-term management of the current SARS-CoV-2 pandemic (see NAPKON). NAPKON and NUKLEUS will continue to develop close collaboration and synergies with the NUM projects COVerCHILD, COVIM, and the NAPKON Therapeutic Intervention Platform (NAPKON-TIP). The specific goals of NAPKON v2 are to consolidate infrastructure and generate new knowledge on COVID-19 and PCS (Post-COVID-19 syndrome). Data and biospecimens collected in the NAPKON cohorts will additionally be used for centrally performed multi-OMICs analyses to explore pathophysiological mechanisms of COVID-19 and signatures that predict and cause specific outcomes and phenotypes of COVID-19 and post-COVID-19 syndrome (PCS). To this end, the project was linked to the Sample Analysis for Post Covid Research in NAPKON (SAPCRiN) project (see SAPCRIN).

Department / Institute: stitute of Pathology

NATON will continue on the efforts of DEFEAT PANDEMics with regard to the consequences of the COVID-19 pandemic and will additionally maintain and further the infrastructure of a preparedness structure for future pandemics. NATON will enable and support national, multi-centre, autopsy-driven research and the development of autopsy-associated novel methods and techniques. The MHH, represented in the steering committee and as a work package leader by Prof. Jonigk of the Institute of Pathology, is substantially involved as both, a reference centre for thoracic pathology and a key centre for (3D) imaging methods on post-mortem biomaterials. In close cooperation with multiple research associations within (e.g. DZL) and outside the MHH, NATON promotes cutting-edge research on a national level. To summarize, NATON is a unique, multi-modular, Germany-wide, closely linked network that is self-supporting beyond the current pandemic and can be used for future pandemics as well as other - especially rare - diseases.

More information can be found on the website: https://www.netzwerk-universitaetsmedizin.de/projekte/defeat-pandemics

 

Department / Institute: Hannover Unified Biobank (HUB)

NUM Clinical Epidemiology and Study Platform (NUKLEUS) provides an infrastructure and specific know-how for the planning, implementation and evaluation of multicentre clinical and epidemiological studies. It offers the scientific community optimal access to infrastructures for the provision of high-quality data and biosamples. The Biosample Core Unit (BCU) is responsible for the quality of biospecimens and biospecimen associated data in NAPKON and future NUM studies. High quality biobanking, in particular the use of common standard operating procedures (SOPs) for biosample collection and processing, is an important prerequisite for multicentre studies and ensures successful and reproducible research based on the collected biosamples. The BCU is managed by Prof. Dr. Illig from the Hannover Unified Biobank (HUB) of the MHH and Dr. Anton from the HMGU in Munich. Furthermore, an audit programme was developed and implemented by the BCU to support the various university hospitals in implementing the uniform quality standards for the provision of high-quality data and biospecimens.

Department / Institute: Hannover Unified Biobank (HUB) / Rheumatology

Refugees are particularly vulnerable to infectious diseases due to the living conditions caused by displacement and mass accommodation. Due to the generally low vaccination rates and the comparatively high prevalence of certain infectious diseases (e.g. COVID 19, HIV, HBV, HCV, TB, measles, chickenpox) in the Ukrainian population, infectious medicine expertise is particularly in demand here. Specifically, a total of 2,500 refugees will undergo a structured screening and vaccination programme in the participating NUM centres in close cooperation with the health offices. This also includes children who are particularly involved in the current wave of refugees and are at risk of infectious diseases. The data collected in this context will be systematically evaluated by NUM scientists in order to better identify care needs in the group of war refugees and to be able to formulate a corresponding recommendation.

Department / Institute: Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School

Medical Data Integration Centers (MeDICs or DIZ) are being set up at all university clinics in Germany as part of the Medical Informatics Initiative (MII). These support data usage projects with their databases and make this data available in a purely structured form for queries. To do this, the patients must have given their informed consent and make their data available for research.
The currently established MeDICs have set up their IT infrastructures, services, processes, regulations and committees at the site in accordance with the recommendations and guidelines of the MII and are therefore interoperable with the higher-level MII structures. This is shown by the fact that they can be connected to the German research data portal for health (FDPG) in order to support Germany-wide feasibility queries and data usage applications.
The aim of future work must be to learn from the experiences of previous projects and to be able to act as a service provider for tasks beyond COVID-19 both as a general platform for "pandemic preparedness" and for pandemic-independent medical research.

Department / Institute: Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School

During the initial funding phase until december 2021 the IT infrastructure and central data platform „CODEX“ was set up, which allows for a fast and flexible provision and usage of COVID-19 routine data (the so-called „GECCO“ data set) of all university hospital sites in Germany. In this follow-up application, the central platform will continue its operation. Furthermore, the central platform will be enhanced to comprehend a pandemic preparedness. Thereby, NUM-RDP will integrate specific mechanisms to access pseudonymized data for different kinds of users and target groups.

Department / Institute: Comprehensive Cancer Center Hannover

In the context of a pandemic and comparable healthcare crises, there is a significant increase in decision-making uncertainties and decision-making conflicts, which are also relevant from an ethical perspective. The relevant ethical challenges can affect all levels of healthcare, individual and organizational decision-makers, numerous professional groups and other stakeholders. An example relating to research is ethical considerations of benefits and harms in view of existing evidence gaps and urgent research needs. A second example relating to clinical-ethical decision-making is prioritization decisions when resources are scarce and the associated moral burdens. While some of the ethical research questions are specific to pandemic crisis situations (e.g. restrictions on civil liberties in the context of lockdown or so-called challenge trials), other topics, such as ensuring trust in health policy and the health system in the course of a crisis, go far beyond ethical questions beyond the context of a pandemic.

Ethics is an overarching research and preparedness topic in PREPARED.

More information can be found on the website: https://www.mhh.de/ccc/forschungsprogramm

 

 

Department / Institute: Department of Medical Psychology

The HygSupport sub-project in Work Package 10 "Human resources" of NUM-PREPARED investigates human resource management to support hygiene teams, i.e., which measures may promote infection-preventive leadership by hospital epidemiologists, infection control nurses and possibly specialized engineers. Firstly, a scoping review was conducted, which currently is under revision. All publications included in this revision reported results from surveys, primarily US-based. Training and qualification were mentioned most frequently, with recruitment and remuneration systems mentioned to a lesser extent. Further research is needed into the implementation and effectiveness of measures relating to infection prevention and control ("trials instead of surveys"). Secondly, an online survey of all senior university hospital epidemiologists in Germany was conducted in cooperation with the work package "Surveillance, infection prevention and control" (response rate 72%). Items assessed implementation of measures by hospital epidemiology during COVID-19 and future implications. Data analysis is ongoing. 

More information can be found on the website: https://www.mhh.de/medpsy

 

Department / Institute: Institute of Diagnostic and Interventional Radiology

The global challenge of the ongoing COVID-19 pandemic has demonstrated the limits of health systems to collaborate on a national and international level effectively. The radiological cooperation project RACOON was initiated in NUM (Netzwerk Universitätsmedizin) to address these challenges in the first funding phase. The second funding phase aims to further the modular development of the infrastructure driven by the results of the first funding phase within the framework of RACOON-BI. RACOON currently has more than 300 active project participants in 36 university hospitals and forms the basis for pioneering national research infrastructure design. Renowned research and development partners in RACOON include the German Cancer Research Center (DKFZ), the Technical University of Darmstadt, the Fraunhofer Institute MEVIS in Bremen, Mint Medical GmbH, and the company ImFusion. The RACOON infrastructure will support imaging-based research projects with all other cooperative subprojects in the NUM.

More information can be found on the website: https://racoon.network/

 

Department / Institute: Institute of Diagnostic and Interventional Radiology

RACOON COMBINE represents the first use case of the RACOON infrastructure and follows the same integrative and synergistic approach that characterizes RACOON. In addition to the available chest imaging data, RACOON COMBINE includes a new pediatric patient population and modalities with neuroimaging and cardiovascular imaging. Imaging biomarkers will be identified to grade COVID-19-related symptoms and reflect metabolic, cardiovascular, and pulmonary health. Conventional statistical methods and machine learning models will be evaluated for disease prediction and prognosis. RACOON-COMBINE aims to improve overall pandemic management through rapid profiling and phenotyping for new disease patterns and the applicability of new treatments. This project makes an essential contribution to the NUM by extracting high-level data that will enable close integration with other NUM projects.

More information can be found on the website: https://racoon.network/

 

Department/Institute: Institute of Diagnostic and Interventional Radiology, Department of Paediatric Radiology

The RACOON-RESCUE project aims to use the existing RACOON platform to optimize the care of paediatric non-Hodgkin's lymphoma (NHL) patients. NHL is the fourth most common malignancy in childhood and adolescence and despite an event-free survival rate of 70-90%, recurrences are associated with poor outcomes. The project is being led by the Radiology/Paediatric Radiology Department of the MHH and the Paediatric Oncology Department of the UKE Hamburg.

A key goal of A key aim of RACOON-RESCUE is to generate image-based biomarkers in order to optimise the determination of lymphoma stage, the assessment of therapy response and tumour aftercare. For this purpose, the existing NHL Berlin-Frankfurt-Münster registry will be expanded to include computed tomography and magnetic resonance imaging data in order to obtain a unique dataset of clinical and image data. This dataset will be automatically analysed using artificial intelligence to improve patient outcome predictions. The necessary quantitative and standardised image analysis workflows will be developed as part of this project.

 More information can be found on the website: https://racoon.network/