What is WARD?

The Wireless Assessment of Respiratory and circulatory Distress (WARD) project creates an innovative clinical support system and was founded in 2016 as the first continuous and wireless monitoring system of vital signs with real-time AI-interpretation in Denmark. The WARD project integrates inputs from patient monitoring devices with intelligent algorithms to yield high-quality patient observation with real-time alarms triggered by patient vital sign deterioration.

Intended for use in several patient settings where the advantages and benefits of continuous monitoring may be fundamental. The WARD system has been tested as monitoring in postoperative high-risk patients, in patients hospitalized with COPD, in patients admitted with COVID-19 infection and lately with patients at home after being discharged.

WARD allows doctors and nursed to follow patients’ acute medical disease progression or postoperative course. The generation of real-time alarms will immediately alert relevant health care staff to allow initiation of treatment much earlier. Our well-designed, easy-to-use, and simple user interface offers health care professionals a valuable tool for overviewing current and historical vital signs.

Daily routines of manual patient monitoring can be fundamentally changed to 24/7 observation of peripheral oxygen saturation, heart rate, respiration rate, blood pressure, etc. with alarms of important deviations. This may allow more efficient use of resources and the ability to give attention to the patients in special needs while at the same time keeping an eye on the remaining patients.

Aim

The WARD project will define, develop and implement the next generation monitoring system for high-risk patients, proving that it reduces complications and health care expenses.

WARD Clinical Support System increase the quality of patient observation through continuous and wireless monitoring of patient vital signs. Combining innovative technology with evidence-based algorithms, we allow earlier and more frequent detection of patient deterioration through predictive AI-algorithms delivered in a user-friendly App.