Project

KI-Para-Mi

KI-getriebener Paradigmenwechsel durch Mitarbeiter-zentrische Schicht- und Dienstplanung zur Verringerung des Pflegenotstands

KI-getriebener Paradigmenwechsel durch Mitarbeiter-zentrische Schicht- und Dienstplanung zur Verringerung des Pflegenotstands

  • Duration:

The goal of the KI-Para-Mi project is to develop an intelligent personnel planning system for flexible shift scheduling in nursing, which above all takes into account the interests of the employees. The shortage of qualified nursing personnel is a major topics that shapes public debate and political agenda around the globe. Better medical care and rising life expectancy are leading to an increased demand for skilled nursing staff. The gap between demand and actual supply of personnel is growing increasingly. In addition, the average length of stay in the nursing profession is much shorter than in other occupational fields, which places a heavy burden on the body and mind of employees in the nursing profession. Furthermore, classic rigid shift models are still in use, which do not allow flexible shift and duty scheduling. A re-scheduling of already defined shifts is usually only possible with great effort. The inflexible shift plans also make it more difficult to work part time and return to work, e.g. after parental leave, and lead to many trained specialists leaving the profession.

The digital personnel planning system of the project partner Planerio GmbH is to be extended by an AI concept. With the help of AI methods and machine learning algorithms for huge search spaces and ML-based optimization, the wishes and short-term needs of the employees are to be calculated optimally and more flexibly, based directly on the availability and preferences of users.

Partners

Planerio GmbH

Sponsors

Federal Ministry of Education and Research (BMBF)

01IS19038B

Federal Ministry of Education and Research (BMBF)

Publications about the project

Fabrizio Nunnari, Md Abdul Kadir, Daniel Sonntag

In: Andreas Holzinger, Peter Kieseberg, A. Min Tjoa, Edgar Weippl (editor). Machine Learning and Knowledge Extraction. International IFIP Cross Domain (CD) Conference for Machine Learning & Knowledge Extraction (MAKE) (CD-MAKE-2021) August 17-20 Virtual Pages 241-253 LNCS 12844 ISBN 978-3-030-84060-0 Springer International Publishing 2021.

To the publication
Abraham Ezema, Daniel Sonntag, Fabrizio Nunnari

In: Stefan Edelkamp, Elmar Rueckert, Ralf Möller (editor). KI 2021: Advances in Artificial Intelligence. German Conference on Artificial Intelligence (KI-2021) September 27-October 1 Germany Pages 179-193 ISBN 978-3-030-87626-5 Springer International Publishing 2021.

To the publication

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz