A Dynamic Scheduler for Health Care Resources in the Emergency Department of TBRHSC on exploiting Machine Learning during Diverse Situations of COVID‑19 Pandemic.
Thunder Bay Regional Health Sciences Centre (TBRHSC) is an essential healthcare facility in Northwestern Ontario. TBRHSC is currently utilizing a commercial software called AMiON for staff scheduling purposes. However, due to the overcrowding situation caused by the COVID‑19 pandemic, the Emergency Department has been facing many unusual difficulties. Nevertheless, the extra added layer of pressure because of flu season continues to persist. Since over a number of staff at TBRHSC have been quarantined under the suspicion of being asymptomatic carriers of coronavirus, scheduling becomes even more critical with a surging number of patients and a limited number of physicians. Furthermore, to limit the possible exposure of coronavirus in the hospital premises, the TBRHSC emergency department has taken the initiative to schedule staff divided into different zones (High contamination risk zone and low contamination risk zone). Therefore, to resolve all these emerging issues, we are proposing to develop a smart and adaptive scheduler that will ensure to minimize the contact between the staff of these two zones and maximize staff satisfaction. Besides, the scheduling system will allocate non-emergency department physicians on-demand in cooperation with the regular emergency department staff for further support. A total of three students will be trained under this research project. The results of the research will be disseminated through publications.
