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A Patient-Centric Nurse Scheduling Algorithm

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Abstract

This paper introduces a new approach to the well-studied nurse scheduling problem. Nurse scheduling problem involves multiple inter-related parameters concerning nurse and patients, which makes the problem too complex. As a result, many of the traditional NSPs are forced to consider only the nurse-respective parameters for generating the schedules. In this paper, we have considered patient recovery as the ultimate objective of nurse scheduling. To achieve this, we have considered patient’s needs and priorities besides the nurse skills, and environment (e.g. logistic) parameters as basic constraints. This paper aims to minimize soft constraints as well as to improve patient’s satisfaction and quality of service of nurse assignment. We have defined a number of hard and soft constraints based on patient’s requirements, ailments, preferences for a particular nurse, nurse’s skill parameters, penalty, demands on duties, matching quotient with patient’s requirements, location, etc. The assignment of nurses to patients for a particular shift depend on the relation between patient’s need and the skill factor of the nurse, besides, of course, the availability factor of the nurse. This helps in achieving efficiency of the overall solution, besides properly supporting qualitative issues. In this regards, two objective functions are devised here to maximize the nurse’s rewards and minimize the scheduling computational cost. The resulting algorithm has been tested on real-case scenarios of a nursing centre, providing evidence of the actual advantages of the proposed solution.

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Correspondence to Paramita Sarkar.

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This article is part of the topical collection “Next-Generation Digital Transformation through Intelligent Computing” guest edited by P. N. Suganthan, Paramartha Dutta, Jyotsna Kumar Mandal and Somnath Mukhopadhyay.

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Sarkar, P., Chaki, R. & Cortesi, A. A Patient-Centric Nurse Scheduling Algorithm. SN COMPUT. SCI. 3, 7 (2022). https://doi.org/10.1007/s42979-021-00820-4

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