Improving patient outcomes and reducing cognitive load of clinical staff in intensive care through medical-device interoperability and an open and secure IT ecosystem

Over the decades, technical developments have resulted in a variety of different medical devices that dominate today's intensive care work environment.

Beside all the clinical capabilities and benefits these technologies provide, devices also contribute to an increasing complexity in care. Using technology stresses the cognitive strain put on healthcare providers in critical care.

Combined with a big lack of clinical staff the complexity leads to an enormous workload.To tackle these challenges the consortium consisting of four Universities and their clinics and four industrial partners plans to demonstrate the benefits in clinical outcomes and workflow efficiency through standardized, bi-directional interoperability of medical devices based on the new standard ISO/IEEE11073 SDC.

During the project SDC solutions will be provided for different use-cases to reduce the quantity of alarms around the patient bed and securely distribute them to the responsible caregiver, allowing to keep the alarms silent at the bedside. Furthermore, algorithms shall be provided to analyse the root cause and urgency of an alarm.

The latter is supposed to support in decision making whether immediate action is necessary. The IT infrastructure and algorithms will be evaluated in four different clinics.

In addition, AI-based pattern recognition will used for early detection of patient deterioration in order to prevent negative long-term outcomes and prolonged ICU stay.Key deliverable will be a Targeted Alarm System (TAS) including several IT tools on the industrial side and study reports on the effectiveness of the TAS from the clinical partners.

Realising this, a standardised IT-solution for monitoring ICU patients should be the next step after the project.

On the long run it is intended to reduce alarms at ICUs significantly, decrease stress for patients and care takers and as result enhance the quality of intensive care.

New technologies for data analytics will be developed and clinically tested to enable more reliable and individualised clinical decision support.

Positive results and developments in this ICU-centred project may also be transferred to other areas in the patient care workflow.