Prevent falls

Falls in hospitals present significant health risks to patients and can often lead to further complications, extending their stay and recovery time. AI-based monitoring with Ouva seeks to mitigate this risk with multiple features designed to enhance patient safety and prevent falls.

Warns When Patients Sit Up on Bed

Utilizing AI and existing video monitoring cameras, Ouva is programmed to recognize when a patient begins to sit up in bed. This triggers an early warning providing nursing staff with the opportunity to assist and prevent an unattended fall.

Alerts When Patients Leave the Bed

Once a patient fully departs from their bed, Ouva sends alert notifications to relevant healthcare providers. This immediate response ensures that patients are closely monitored and swiftly assisted if they attempt to move unaided.

Combat Alert Fatigue

Alert fatigue, a significant challenge in a clinical setting where alarms are frequent, may lead to important alerts being ignored or missed. Ouva addresses this issue through smart alerting, which has the capacity to suppress alerts if it detects nurses or visitors in the room. This helps to reduce the likelihood of unnecessary or redundant alerts and focuses on situations where immediate nurse intervention is vital.

Adaptable Fall Risk Triggers

Ouva can toggle fall alerts based on individual patient conditions or data sourced from the Electronic Health Record (EHR). This feature allows Ouva to evaluate each patient's unique circumstance, providing tailored and efficient care to those at a higher risk of falls. Consequently, Ouva assists in making more precise decisions and enhances the effectiveness of fall prevention efforts.

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