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Grant: Alliance Grants

Lakehead University

$49,724.00

A Dynamic Scheduler for Health Care Resources in the Emergency Department of TBRHSC on exploiting Machine Learning during Diverse Situations of COVID-19 Pandemic._x000d_ _x000d_

FY 2020-21

Summary
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.
Program
Alliance Grants
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
554162-2020
Name nom
Choudhury, Salimur
Department département
Computer Science
Organization id
25
Institution établissement
Lakehead University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2020
Award amount
49724
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2713
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Algorithms
Research subject fr
Algorithmes
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
A Dynamic Scheduler for Health Care Resources in the Emergency Department of TBRHSC on exploiting Machine Learning during Diverse Situations of COVID-19 Pandemic._x000d_ _x000d_
Keyword
NSERC
Application summary
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.
Lakehead University - $49,724 Grant (2020-21) | Canada Spends