A decision support system for scheduling the shifts of physicians during COVID-19 pandemic


GÜLER M. G. , GEÇİCİ E.

Computers and Industrial Engineering, cilt.150, 2020 (SCI Expanded İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 150
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.cie.2020.106874
  • Dergi Adı: Computers and Industrial Engineering

Özet

© 2020 Elsevier LtdThe rapidly spreading COVID-19 pandemic has affected many people worldwide. Due to the high infectivity, countries make calls to stay at home or take measures such as lockdowns to ensure that people are least affected by the virus. Meanwhile, infected people are getting treatments: people who are slightly affected are quarantined at home, and those who are heavily affected are treated in hospitals. Hence there is an excessive increase in the hospital workload. This causes physical fatigue in healthcare professionals. Along with the increasing workload, the fear of being infected and infecting the environment causes psychological problems in healthcare professionals. It is important to protect healthcare professionals and provide them with suitable working conditions. For this reason, besides the provision of protective equipment such as gloves, overalls, mask, and glasses that are necessary for the protection of healthcare workers from the virus, healthcare services should also be planned very carefully. One of the critical issues is planning the shift schedules of the physicians. In this study, we handle the preparation of a physician shift schedule of a hospital in Turkey during the COVID-19 pandemic. The hospital has established three new COVID-19 related departments and the aim is to provide continuous service in the new departments while maintaining the workload in the existing departments. We propose a mixed integer programming (MIP) model to address the shift scheduling problem and transform it into a decision support system (DSS). The resulting schedules minimize the exposure of the physicians to the virus with a balanced workload while maintaining the healthcare service in all departments.