{"id":42729,"date":"2023-03-23T14:45:40","date_gmt":"2023-03-23T13:45:40","guid":{"rendered":"https:\/\/xitaso.com\/projects\/kispp-intelligente-planung-von-pflegekraeften\/"},"modified":"2026-04-07T11:39:44","modified_gmt":"2026-04-07T09:39:44","slug":"kispp","status":"publish","type":"page","link":"https:\/\/xitaso.com\/en\/projects\/kispp\/","title":{"rendered":"KISPP: Intelligent scheduling of nursing staff"},"content":{"rendered":"

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The challenge<\/h2>\n

In order to maintain care in hospitals, it is necessary to have sufficient nursing staff available. However, nursing staff planning is a complex and time-consuming process for personnel planners. The main challenges here are the shortage of nursing staff, which is expected to worsen in the coming years due to demographic change, as well as the time-consuming documentation required by legal regulations such as the so called ‘Nursing Staff Lower Limits Ordinance’\u00a0(PpUGV).[\/vc_column_text][vc_empty_space height=”30″][vc_empty_space height=”30px” el_class=”not-on-mobile”][\/vc_column_inner][vc_column_inner width=”1\/2″][vc_empty_space height=”30″ el_class=”not-on-mobile”][vc_empty_space height=”30″][vc_column_text]<\/p>\n

How we will help<\/h2>\n

The project aims to develop intelligent software for the needs-based planning and management of nursing staff deployment – the KISPP tool. XITASO will contribute and further expand its expertise in the areas of data science, software engineering and UI\/UX. Together with our partners, we want to make the nursing profession more attractive in the long term and thus tackle an important social challenge.<\/p>\n

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Technologies<\/h2>\n

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The research project on detail<\/h2>\n

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In cooperation with the University Hospital of Augsburg and the Chair for Health Care Operations and Health Information Management at the University of Augsburg, XITASO will be investigating the needs-based distribution of the nursing workload in the coming years. In our research, we are combining AI-based forecasts of future care requirements with AI-supported rescheduling in the event of special incidents, thereby significantly reducing the overload in hospitals.<\/p>\n

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The KISPP tool<\/h3>\n

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Simultaneously, we are developing a new system to improve decision making on capacities in the different nursing wards by e.g. predicting patients’ length of stay. This system, the so-called KISPP-Tool<\/strong> (AI control for customized nursing staff planning and registration), should therefore provide two central competencies:<\/p>\n

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