The Nurse Rostering Problem in COVID-19 emergency scenario
Abstract: Healthcare facilities are struggling in fighting the spread of COVID-19. While machines needed for patients such as ventilators can be built or bought, healthcare personnel is a very scarce resource that cannot be increased by hospitals in a short period. Furthermore, healthcare personnel is getting sick while taking care of infected people, increasing this shortage of qualified personnel. As a consequence, they are asked to work overtime in order to guarantee enough assistance to patients in critical conditions. This article has the scope to provide healthcare facilities with a flexible mathematical formulation for scheduling nurses' shifts in scenarios with insufficient number of nurses by introducing the possibility for nurses to work more than one shift per day. This will reduce the number of shifts with an insufficient number of nurses while minimizing stress for the healthcare personnel by defining balanced schedules. Numerical results carried on synthetic data show the effectiveness of the formulation here introduced. Finally, all the models described are implemented in Python and made available as open-source software to all those facilities struggling for this emergence in order to help them in scheduling nurses during this critical situation.
Keywords: Nurse Rostering Problem, Scheduling Problems, COVID-19, Mixed Integer Optimization, Emergency scenario.
Category 1: Applications -- OR and Management Sciences
Category 2: Applications -- OR and Management Sciences (Scheduling )
Entry Submitted: 03/31/2020
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