Find My Bed: An AI Navigator for Babies Requiring Immediate Hospital Transfers

Every year, ~15,000 newborns in Canada who are critically ill are admitted to 31 Level 3 neonatal intensive care units (NICU). These newborns are at a high risk of death and illness. Over 65% of these newborns are not followed before birth in a hospital with a Level 3 NICU and need to be transferred either prior to birth (ie the pregnant mother) or after birth to a hospital with a Level 3 NICU. This transfer process is time-sensitive and requires the doctor to find a bed in the unit. This process can take up to 35 minutes, and there is a chance that the decision made may not be the optimal one.

To improve the process, we propose to develop Artificial Intelligence driven Decision Support Application that will help identify the most appropriate hospital for the transfer. This will be done through collaboration with experts and stakeholders. The project includes experts in neonatal health, nursing, process optimization, and national networks, as well as stakeholders such as the Ministry of Health. The expected outcome is to improve the efficiency of decision-making and better distribute admissions of critically ill newborns, which can have a significant impact on the overall system.

Faculty Supervisor:

Haruna Isah

Student:

Partner:

Korah Limited

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Sheridan College Institute of Technology and Advanced Learning

Program: