Balancing Nursing Workload by Constraint Programming

• Published in: Integration of AI and OR Techniques in Constraint Programming Vol. 9676; pp. 294 - 302
• Main Author: Pesant, Gilles
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 01.01.2016; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Achieve Domain Consistency; Generalized Assignment Problem; Mathematical theory of computation; Mean Workload; Spread Constraint; Staffing Configurations
• ISBN: 3319339532; 9783319339535
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-33954-2_21

Nursing workload in hospitals has an impact on the quality of care and on job satisfaction. Understandably there has been much recent research on improving the staffing and nurse-patient assignment decisions in increasingly realistic settings. On a version of the nurse-patient assignment problem given a fixed staffing of neonatal intensive care units, constraint programming (CP) was shown to perform better than competing optimization methods. In this paper we take advantage of recent improvements to the CP approach to solve the integrated problem of staffing and nurse-patient assignment. We then consider a more difficult but also more realistic version of the problem in which patients are categorized into a small number of types and the workload associated with each type is nurse-dependent.