(Vienna, 06-03-2023) MedUni Vienna's Department of Anaesthesia, General Intensive Care Medicine and Pain Therapy is the first hospital in Austria to become a certified Data Partner with the EHDEN project. This highlights the clinic's position as a leading institution in the field of data science and big data.
Healthcare data is for the most part inaccessible for research. In the few cases where access does exist, the use of the data is often associated with great expense. Especially due to the incompatible format, connecting several data sources is complicated or completely impossible. To resolve precisely this problem, standardised formats have been developed that make it possible to process data from other hospitals and countries. As part of the EHDEN project, numerous European health institutions are transforming their databases into a uniform, open format called "OMOP CDM". This enables simplified, multicentre research on the international level. A European Union project "DARWIN EU" also relies on institutions with "OMOP CDM" databases to research already approved medicines for efficacy and side effects.
At the University Hospital for Anaesthesia, General Intensive Care Medicine and Pain Therapy, vital signs, medication, examinations and treatments from the operating theatre, recovery room and intensive care unit have been digitally recorded for several years. With the inclusion of more than 350,000 patients, this database is one of the largest such databases in the world. As part of the EHDEN project, the "Data Working Group" led by Oliver Kimberger from the University Department of Anaesthesia, General Intensive Care Medicine and Pain Therapy has now converted this database to the "OMOP CDM" format. The still new working group has already been able to publish many research results in the field of data analysis and Big Data in top journals.
The work on this pioneering project was carried out jointly with the IT4Science team at ITSC, led by Thomas Wrba, and the Ludwig Boltzmann Institute Digital Health and Patient Safety.
The working group is also looking to start a new project. Instead of every 15 seconds, curve data will be recorded 200 times per second. This will make it possible to record about 1GB of high-quality, high-resolution raw data per operating theatre or intensive care bed every day. Using newer methods from signal processing and machine learning, the team hopes to gain new insights into the prediction of adverse events in the operating theatre and intensive care units. In contrast to the transformation of existing data, new infrastructure will first be created to record and process the resulting data volumes.