The goal of this project is to initiate research into a novel process for improved patient care in acute and non-acute healthcare facilities. The process is based on the deployment of a smart environment enable nurses and other healthcare professionals to more effectively and efficiently monitor in-patients at risk of harm from events such as falls. The smart environment comprises a variety of sensors (vision, audio, proximity, wearable) as well as automated data processing and Artificial Intelligence and Machine Learning (AI/ML) methods, combined with a mobile interface to allow practitioners to easily and seamlessly access and interpret the data. The project will involve researchers at Queen’s, as well as end users at Scarborough Health Network (SHN), who are eager to provide the environment for this development. The first phase of the project, will deploy an initial subset of the process that will yield tangible improvements in safer healthcare delivery, the success of which will serve as a springboard for further and larger funding opportunities. Ultimately, this project will be regarded as the first step towards enabling the modernization of efficient, effective, data-driven patient monitoring in acute and non-acute healthcare facilities at a reduced cost.
Project Researchers
Michael Greenspan (PI), Xiaodan Zhu, Qingguo Li, Ali Etemad
Project Partners
Scarborough Health Network: Babak Taati, Dick Zoutman