Page 34 - KNJIGA SAŽETAKA

INOVACIJE I IZAZOVI U OBRAZOVANJU I SESTRINSKOJ SKRBI - KNJIGA SAŽETAKA

Optimising the Allocation of Students to Work Shifts

Using Artificial Intelligence

The assignment of students to work shifts is crucial for the efficient functioning of different
sectors, but especially for areas where people need to be constantly present and cared for, such
as nursing. Traditional scheduling methods based on manual work or simple algorithms often
do not make full use of available resources or meet the needs of particular groups of students
according to their specific skills and preferred school schedules.
At Jesenice General Hospital, the management decided to implement advanced artificial
intelligence methods to optimise the scheduling process. The central idea is the concept of a
flexibility matrix, which allows for a systematic analysis of the need to integrate additional
human resources in standard hospital wards according to various factors such as skills acquired,
availability and student preferences.
Using machine learning algorithms and data analysis, the system can identify patterns and
trends to better understand the needs for human resource integration according to the skills
acquired and the groups identified. For example, it can identify three main groups of students
according to their acquired skills: those with basic level, intermediate level and advanced level
skills.
This more precise classification makes it possible to allocate students more efficiently to work
shifts that are appropriate to their abilities and needs, while ensuring that the necessary tasks
and responsibilities are appropriately distributed among the different work groups. This not
only improves productivity and efficiency, but also increases staff satisfaction and improves
the quality of health services needed by patients.
In addition, this approach allows better use of available resources, which can lead to cost
reduction and better use of time. Over time, the system can continue to effectively adapt
deployments to changing needs and workplace dynamics, allowing for sustainable and flexible
deployment of human resources in the face of a long-lived society and nursing staff shortages.

Key words: pupils, students, nursing care, hospital wards, artificial intelligence, work plan

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