As part of the Medical Informatics Initiative (MII) and the Network University Medicine (NUM), the establishment of Medical Data Integration Centres is being promoted in order to convert routine medical data into a standardised format and thus make it available for secondary use, such as research. As part of these research initiatives, the University of Oldenburg has joined the HiGHmed consortium and founded the Oldenburg Data Integration Centre, MeDIC-UMO. Prof Dr Wulff represents the MeDIC-UMO as site spokesperson at national level and supports it as a scientific advisor.

Further information can be found here:

MeDIC-UMO

HiGHmed

Medical Informatics Initiative

Infections that occur in hospital (known as nosocomial infections) are a problem for both the patients affected and the healthcare staff. Among the most serious infections are bloodstream infections, in which bacteria enter the bloodstream and which, despite all medical progress, can lead to long-term damage or even death for those affected.

With the RISK-PRINCIPE project, we want to develop and provide software that supports hospital staff in individual and patient group-specific documentation and monitoring, as well as risk prediction. Our aim is to implement a user-orientated application that contributes to better targeted and possibly even new preventive measures through close cooperation with clinicians. As a result, the risks derived from the data can be better taken into account, thus ensuring improved patient care.

Further information on RISK-PRINCIPE

In order to offer suitable interventions for patients with post-COVID-19 disease, it is important to understand exactly how the disease manifests itself in them and what differences there are between patients. Many of those affected suffer from fatigue, attention and memory disorders. It is still unclear how these symptoms change over shorter and longer periods of time, or how they are related to other factors.

To provide more clarity on the progression of neurocognitive symptoms after COVID-19, we are pursuing two approaches: First, we are developing a web-based app to record fluctuations in symptoms over a shorter period of time using standardised neurocognitive tests. Secondly, we are investigating the development of symptoms in data sets from long-term studies. We are also investigating how differences in progression between different patients arise and what role the social environment plays in this.

Further information on COFONI

The Interoperability Working Group, funded by the Federal Ministry of Education and Research as part of the Medical Informatics Initiative, focuses its activities on improving the use of data from patient care and research with the aim of making patient care more sustainable and viable for the future.

Further information on the AG IOP

Follow-up project to the ELISE project https://plri.de/forschung/projekte/elise

Within the framework of ELISEplus, further consistent steps are now necessary in order to generate a constant benefit from the results and to guarantee translation at various levels, including

• Translation into paediatric intensive care, Part I Prediction models
• Translation into paediatric intensive care, Part II Data quality
• Communication with and transferability to other manufacturers and locations
• Communication of results and science (open science)

The INGVER - Intersectoral Care for Vulnerable Groups project at University Medicine Oldenburg (UMO) aims to establish cross-sectoral, integrative and individualised healthcare for vulnerable groups. This is achieved through research into innovative and interdisciplinary diagnosis, treatment and care measures in the context of personalised medicine. The focus is on the development of new diagnosis and therapy concepts in the clinical area as well as the intersectoral networking and automation of care measures from prevention and rehabilitation to home
care and nursing/support in order to establish long-term coordinated and preventive treatment strategies. The project focuses on the following three vulnerable patient groups:

• High-risk babies
• Oncological patients
• Elderly people

The German openEHR Modelling Group (GoEMG) is a community for the promotion of interdisciplinary cooperation and collegial support in the context of openEHR modelling activities in Germany. The aim is to sustainably strengthen the dissemination and further development of the openEHR standard in German-speaking countries (DACH).

The openEHR Modelling Group in the HiGHmed consortium stands for innovation and collaboration in the healthcare sector and pursues the goal of developing high-quality, interoperable information models for the healthcare sector. Since the start of the modelling work in 2016/2017 - funded by the HiGHmed consortium - a structured and collaborative way of working has been established.

Based on international cooperation and with a view to future developments, the German openEHR Modelling Group (GoEMG) was founded in 2024 as a further development of the HiGHmed consortium's openEHR Modelling Group. The GoEMG benefits from long-standing international partnerships, particularly in the fields of genomics and oncology. The group is also an active member of the international Clinical Programme Board and participates in the work of the openEHR Specifications Editorial Committee.

Head: Prof. Dr Simon Schäfer, Department of Anaesthesiology, Intensive Care Medicine, Emergency Medicine and
Pain Therapy

in co-operation with Prof. Dr Nils Strodthoff, Department of AI4Health

The aim of this project is to analyse whether hypotension can be predicted better in intensive care units and operating theatres using
waveform-based AI models than using
analysis of vital data values

As part of a co-operation with the University Clinic for Anaesthesiology, Intensive Care Medicine, Emergency Medicine and Pain Therapy (Klinikum Oldenburg), a simulation centre is being created that will be available for further clinical education and university teaching as well as for research purposes.

Further information on the "Simulation Centre" project

Complications can occur during birth, which can lead to
asphyxia in the affected neonates and result in long-term neurological damage. Therapeutic hypothermia treatment has established itself as the standard treatment in these cases. To reduce the associated increased stress level, the newborns are sedated during treatment. In order to minimise the risk and consequences of possible withdrawal symptoms, the dose of sedatives to be administered must be reduced as far as possible without falling below the necessary depth of anaesthesia.

As part of the "Sedation in neonates" project, we are looking at current therapeutic approaches for neonatal asphyxia. We are investigating and evaluating the processes and outcome of a general reduction in the sedation dose in neonates with asphyxia during hypothermia therapy using EEG monitoring to measure the depth of anaesthesia.

Further information on the project "Sedation in neonates"

Further information on the profile initiative

The headache disorder migraine is a widespread disease worldwide, which can restrict the daily lives of those affected for a considerable period of time and is also sometimes accompanied by psychological symptoms such as anxiety or depression. The prevalence peak in young age groups in particular means that chronic patients suffer from the restrictions for almost their entire lives. Preventive measures for migraine sufferers receive significantly less attention compared to the common method of acute medication.

In our research, we want to further expand the investigation of non-pharmacological preventive measures, in particular the detection and avoidance of migraine triggers. To achieve this, we want to collect and analyse lifestyle factors and migraine data from sufferers by tracking them with modern technology such as smartphones or wearables (digital phenotyping). The focus of the study is on lifestyle factors that are linked to the phenomenon of technostress. Technostress occurs when people are overwhelmed by the constantly growing number of digital demands. In a time of widespread digital overconsumption, technostress is therefore not only widespread, but also one of the most pressing challenges of modern life and therefore a central reason for this study. The result of the data analysis will be a digital tool that helps migraine sufferers to avoid triggers and/or prepare for an upcoming migraine attack. The results will not only advance the field of medical Computing Science, but will also be of greater importance for psychology, public health and societal well-being.