Autodok

Almost all acute hospital settings use observation protocols ranked by patient severity to ensure that potential deterioration is identified in time. To achieve this, the departments utilise advanced patient monitors for tracking the state of admitted patients. These monitors are typically capable of continuously tracking and reporting vital values at a much higher rate than documented in clinical knowledge management systems.

Previous research has shown that most patients are not monitored closely enough, while a subset of patients are monitored more than required by clinical protocols. The latter situation, which also applies to patients who are continuously monitored, are poorly represented by spot-based registrations. The former situation complicates clinical assessment and prediction.

AIM

In the AutoDok project, the Patient Deterioration Warning System is extended with functionality for handling clinical documentation for patients who are extensively monitored and patients who lack monitoring during periods of their admission. Furthermore, the AutoDok project will explore integration with the EPJ SYD system through the Medical Device Information Collection (MDIC) platform.

This is a PhD project by Thomas Schmidt and is anchored at the Centre for Clinical Artificial Intelligence (CAI-X).

PARTNERS

Partners on the project are the Emergency Department at Odense University Hospital and the Maersk Mc-Kinney Moller Institute at the University of Southern Denmark.

EXTERNAL FUNDING

The project is funded by the Innovation Fund of the Region of Southern Denmark.