Deterioration, Clinical

The ONWARD study evaluates user experiences from continuous vital sign monitoring alarms sent to the clinical staff in case of deviating vital signs at the general hospital ward. User experiences are evaluated though a 5-point likert questionnaire.

The investigators aim to build a predictive tool for Adverse Outcome of Acute Pulmonary Embolism by Artificial Intelligence System Based on CT Pulmonary Angiography.

This study collected clinical, laboratory, and CT parameters of acute patients with acute pulmonary embolism from admission to predict adverse outcomes within 30 days after admission into hospital.

Rapid response teams (RRTs) have been adopted by hospitals to provide urgent critical care to hospitalized patients who require quick intervention to prevent further deterioration. Early warning scores (EWS) serve as a method to identify patients requiring RRT assessment by analyzing routinely collected data such as vital signs and laboratory results. The Visensia Safety Index (VSI) is an EWS that uses continuous vital sign monitoring and machine learning to identify the likelihood of deterioration and can be integrated with existing hospital data infrastructure. Initial studies of the VSI have both validated the system and found that patients monitored using VSI had a shorter duration of any instability and fewer episodes of serious and persistent instability. The investigators' recent retrospective analysis at The Ottawa Hospital (TOH) identified that implementation of an EWS could have detected earlier deterioration in over half of the patients identified, potentially preventing subsequent ICU admission, severity of illness, and/or mortality. Thus, this study aims to determine the feasibility and potential impact of implementing a portable continuous monitoring system with a VSI trigger at TOH to identify patients at high risk of deterioration.