{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T09:00:10Z","timestamp":1790586010107,"version":"4.1.0"},"reference-count":0,"publisher":"Georg Thieme Verlag KG","funder":[{"name":"Bundesministerium f\u00fcr Forschung, Technologie und Raumfahrt","award":["01KX2121"],"award-info":[{"award-number":["01KX2121"]}],"id":[{"id":"https:\/\/ror.org\/04pz7b180","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Gesundheitswesen"],"abstract":"<jats:p>Zusammenfassung\nHintergrund: Die COVID-19-Pandemie hat deutlich gemacht, dass Universit\u00e4tskliniken \u00fcber geeignete Krisenst\u00e4be verf\u00fcgen m\u00fcssen, um die sich entwickelnde Lage antizipieren und die Ressourcenzuweisung und Personalverteilung entsprechend planen zu k\u00f6nnen. Mathematische Modellierungsstudien stellen dabei ein Werkzeug dar, welches Prognosen f\u00fcr k\u00fcnftige Entwicklungen und deren Unsicherheiten liefern kann. Ziel dieser Studie war es, die Rolle der mathematischen Modellierung in den Krisenst\u00e4ben deutscher Universit\u00e4tskliniken w\u00e4hrend der COVID-19-Pandemie zu verstehen und potenzielle Verbesserungsbereiche zu identifizieren.\nMethode: Im Rahmen des Projektes PREPARED im Netzwerk Universit\u00e4tsmedizin f\u00fchrten wir eine Befragung aller deutschen Universit\u00e4tskliniken durch und werteten die Ergebnisse deskriptiv aus.\nErgebnis: Es konnten Daten von 24 der zu diesem Zeitpunkt existierenden 36 Universit\u00e4tskliniken in Deutschland (67%) eingeschlossen werden. Alle berichteten, w\u00e4hrend der COVID-19-Pandemie \u00fcber Krisenst\u00e4be verf\u00fcgt zu haben, die speziell f\u00fcr die COVID-19-Pandemie eingerichtet worden waren und mit deren Bew\u00e4ltigung betraut waren. Von diesen 24 Universit\u00e4tskliniken nutzten 19 (79%) Ergebnisse mathematischer Modellierungsstudien, wenn sie Entscheidungen \u00fcber die Verteilung von betreibbaren Betten, Einschr\u00e4nkungen bei der elektiven Versorgung oder Personalallokation trafen. Als Basis f\u00fcr die Modellierungen wurden Daten des Robert Koch-Instituts (n=9, 38%), Daten aus dem eigenen Klinikum (n=8, 33%) und\/oder lokale\/regionale Daten (n=11, 46%) eingesetzt.\nSchlussfolgerung: Modellierungsergebnisse spielten w\u00e4hrend der COVID-19-Pandemie eine wichtige Rolle bei den Entscheidungen der Krisenst\u00e4be an Universit\u00e4tskliniken in Deutschland. Ein automatisierter Zugang zu interoperablen, verl\u00e4sslichen Daten und lokal anwendbaren Modellen sollte geschaffen werden, um die Zuverl\u00e4ssigkeit von Modellierungsergebnissen f\u00fcr zuk\u00fcnftige Krisen sicherstellen zu k\u00f6nnen.\n\u2003\nEnglische Zusammenfassung\nBackground: The COVID-19 pandemic highlighted the need for university hospitals to have crisis management teams to anticipate the developing situation and plan resource allocation and staff distribution. To this end, mathematical modelling studies are a tool that can provide forecasts for future developments and their uncertainties. This study aimed to understand the role of mathematical modelling in German university hospital crisis management teams during the COVID-19 pandemic and identify potential areas for improvement.\nMethods: As part of the project PREPARED of the Network of University Medicine, we administered questionnaires to all German university hospitals and analysed all data descriptively.\nResults: Data were obtained from 24 of the 36 university hospitals that existed in Germany at this time (67%). All of these reported having crisis management teams during the COVID-19 pandemic that had been set up specifically for the COVID-19 pandemic and were tasked with addressing the challenges of the pandemic. Of these 24 university hospitals, 19 (79%) used results from mathematical modelling studies when making decisions concerning the distribution of operational beds, restrictions on elective care, or staff allocation. Data from the Robert Koch Institute (n=9, 38%), data from the hospital itself (n=8, 33%), and\/or local\/regional data (n=11, 46%) were used as the basis for modelling.\nConclusion: Modelling results played an important role in crisis management decision making at university hospitals in Germany during the COVID-19 pandemic. Automated access to interoperable, reliable data and locally applicable models should be created to secure the validity of modelling results in future crises.<\/jats:p>","DOI":"10.1055\/a-2961-6456","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T08:41:24Z","timestamp":1790584884000},"source":"Crossref","is-referenced-by-count":0,"title":["Nutzungscharakteristika von infektionsdynamischen Modellierungen im Krisenmanagement von deutschen Universit\u00e4tskliniken w\u00e4hrend der COVID-19-Pandemie"],"prefix":"10.1055","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6449-5036","authenticated-orcid":false,"given":"Antonia","family":"Bartz","sequence":"additional","affiliation":[{"name":"Universit\u00e4t M\u00fcnster, NRW, Germany","place":["M\u00fcnster"],"department":["Institut f\u00fcr Epidemiologie und Sozialmedizin"]},{"name":"Universit\u00e4t M\u00fcnster, NRW, Germany","place":["M\u00fcnster"],"department":["Interdisciplinary Center for Mathematical Modeling of Infectious Disease Dynamics"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Schuppert","sequence":"additional","affiliation":[{"name":"Universit\u00e4tsklinikum Aachen, RWTH Aachen, Germany","place":["Aachen"],"department":["Institut f\u00fcr Computational Biomedicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Younes","family":"M\u00fcller","sequence":"additional","affiliation":[{"name":"Universit\u00e4tsklinikum Aachen, RWTH Aachen, Germany","place":["Aachen"],"department":["Institut f\u00fcr Computational Biomedicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenz","family":"Baum","sequence":"additional","affiliation":[{"name":"Goethe-Universit\u00e4t Frankfurt am Main, Germany","place":["Frankfurt am Main"],"department":["Professur f\u00fcr Wirtschaftsinformatik und Informationsmanagement"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oliver","family":"Hinz","sequence":"additional","affiliation":[{"name":"Goethe-Universit\u00e4t Frankfurt am Main, Germany","place":["Frankfurt am Main"],"department":["Professur f\u00fcr Wirtschaftsinformatik und Informationsmanagement"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Streissnig","sequence":"additional","affiliation":[{"name":"Medizinische Fakult\u00e4t Carl Gustav Carus, TU Dresden sowie Universit\u00e4tsklinikum Carl Gustav Carus, Germany","place":["Dresden"],"department":["Zentrum f\u00fcr Evidenzbasierte Gesundheitsversorgung (ZEGV)"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jochen","family":"Schmitt","sequence":"additional","affiliation":[{"name":"Medizinische Fakult\u00e4t Carl Gustav Carus, TU Dresden sowie Universit\u00e4tsklinikum Carl Gustav Carus, Germany","place":["Dresden"],"department":["Zentrum f\u00fcr Evidenzbasierte Gesundheitsversorgung (ZEGV)"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simone","family":"Scheithauer","sequence":"additional","affiliation":[{"name":"Universit\u00e4tsmedizin G\u00f6ttingen, Germany","place":["G\u00f6ttingen"],"department":["Institut f\u00fcr Hygiene und Infektiologie"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Veronika","family":"Jaeger","sequence":"additional","affiliation":[{"name":"Universit\u00e4t M\u00fcnster, NRW, Germany","place":["M\u00fcnster"],"department":["Institut f\u00fcr Epidemiologie und Sozialmedizin"]},{"name":"Universit\u00e4t M\u00fcnster, NRW, Germany","place":["M\u00fcnster"],"department":["Interdisciplinary Center for Mathematical Modeling of Infectious Disease Dynamics"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andr\u00e9","family":"Karch","sequence":"additional","affiliation":[{"name":"Universit\u00e4t M\u00fcnster, NRW, Germany","place":["M\u00fcnster"],"department":["Institut f\u00fcr Epidemiologie und Sozialmedizin"]},{"name":"Universit\u00e4t M\u00fcnster, NRW, Germany","place":["M\u00fcnster"],"department":["Interdisciplinary Center for Mathematical Modeling of Infectious Disease Dynamics"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","container-title":["Das Gesundheitswesen"],"original-title":[],"language":"de","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2961-6456.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T08:41:24Z","timestamp":1790584884000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2961-6456"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,20]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1055\/a-2961-6456","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["0941-3790","1439-4421"],"issn-type":[{"value":"0941-3790","type":"print"},{"value":"1439-4421","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,9,20]]},"published":{"date-parts":[[2026,9,20]]}}}