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Identifying patients at risk (PDWS)

Patient monitoring in emergency departments typically includes basic physiological vital signs as well as assessments of pain and consciousness.

Project period

Start: 2019 
End: 2022

Automated monitoring provides a continuous stream of data that enable real-time tracking of patient state, but reliable projection of trajectory is challenged by the sparseness of data and variation in patterns. The project sought to address both the challenges of device utilisation and patient risk stratification.


The project aimed to reduce the number of unforeseen deteriorations of patients in medical emergency departments. The project’s approach was looking at how data from the information systems that hospitals already use could be utilised in novel ways through machine learning based models. Ideally, the models would be able to span the diversity of patients and medical device utilisation.

The project built on the system Patient Deterioration Warning System (PDWS), which was developed in a previous project. The PDWS is currently integrated into the emergency department’s monitoring systems. 


Thomas Schmidt

Thomas Schmidt

Associate Professor

University of Southern Denmark, Maersk Mc-Kinney Moeller Institute

(+45) 2423 7434
Amin Naemi

Amin Naemi

PhD student

University of Southern Denmark, Maersk Mc-Kinney Moller Institute

(+45) 6550 7466
Kristian Kidholm

Kristian Kidholm

Head of Research - Professor

Centre for Innovative Medical Technology (CIMT). Odense University Hospital, Dept. of Clinical Development - Innovation, Research & HTA

(+45) 6541 7960

Annmarie Lassen

Professor, Chief Physician

Odense University Hospital, The Emergency Department

(+45) 6541 5048