SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research.

Egli, Adrian; Battegay, Manuel; Büchler, Andrea C; Bühlmann, Peter; Calandra, Thierry; Eckert, Philippe; Furrer, Hansjakob; Greub, Gilbert; Jakob, Stephan M.; Kaiser, Laurent; Leib, Stephen L.; Marsch, Stephan; Meinshausen, Nicolai; Pagani, Jean-Luc; Pugin, Jerome; Rätsch, Gunnar; Schrenzel, Jacques; Schüpbach, Reto; Siegemund, Martin; Zamboni, Nicola; ... (2020). SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research. Studies in health technology and informatics, 270, pp. 1163-1167. IOS Press 10.3233/SHTI200346

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Sepsis is a highly heterogenous syndrome with variable causes and outcomes. As part of the SPHN/PHRT funding program, we aim to build a highly interoperable, interconnected network for data collection, exchange and analysis of patients on intensive care units in order to predict sepsis onset and mortality earlier. All five University Hospitals, Universities, the Swiss Institute of Bioinformatics and ETH Zurich are involved in this multi-disciplinary project. With two prospective clinical observational studies, we test our infrastructure setup and improve the framework gradually and generate relevant data for research.

Item Type:

Journal Article (Further Contribution)

Division/Institute:

04 Faculty of Medicine > Service Sector > Institute for Infectious Diseases
04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > Clinic of Intensive Care
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Infectiology

UniBE Contributor:

Furrer, Hansjakob, Jakob, Stephan, Leib, Stephen

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

0926-9630

Publisher:

IOS Press

Language:

English

Submitter:

Annelies Luginbühl

Date Deposited:

06 Jul 2020 15:20

Last Modified:

05 Dec 2022 15:39

Publisher DOI:

10.3233/SHTI200346

PubMed ID:

32570564

Uncontrolled Keywords:

-omics biomarkers SPHN big data data exchange diagnostics digital biomarker interconnected interoperability machine learning personalized health sepsis

BORIS DOI:

10.7892/boris.144947

URI:

https://boris.unibe.ch/id/eprint/144947

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