Educational and training materials are under development, tailored to the training programmes. The aim is to develop interactive clinical changing electronic teaching courses for each specialty participating in simulation-based team training. Effects of simulation-based team training in the management of acute stroke
This project started as a quality improvement project at Stavanger University hospital aiming to reduce the time to treatment in patients with acute stroke. Efficient standard operating procedure, efficient team coordination, and communication is vital to keep treatment times as low as possible. We used in-situ simulation-based team training as a key part of our quality improvement project. A key part of simulation-based training in addition to recreating scenarios is debriefing the scenario. So far, the door-to-needle time has reduced from 30 to 13 minutes. (Collaboration partner: Laerdal Medical AS) Technical skill set training
A technical skill set training is being developed for interventional radiologists at Stavanger University Hospital. The simulator is a portable, virtual reality simulator (Mentice VIST® G5 Simulator) including a wide variety of training scenarios. The technical reopening rate, the intervention time, and the clinical outcome of patients treated in the clinical setting are being monitored. Main focus of the cost-effective analyses will be how incurring costs through simulation training are mirrored by savings due to better patient outcome, less occurring complications, shorter hospital stay and generally reduced morbidity and mortality. Stroke finder - Medfield
A multicentre technology development project on suspected stroke patients which will use microwave technology to differentiate hemorrhage from infarction in the acute phase. The measurement data will be evaluated for the presence of signal artifacts. The overall aim of this project is to evaluate the usability and develop diagnostic ability of Strokefinder MD100 to differentiate patients with hemorrhagic stroke (HS) and ischemic stroke (IS) /stroke mimics (SM) in the acute phase. The measurement data from patients will be used to generate a mathematical classification algorithm.
Facial recognition - ResQ Biometrics AS
Use facial recognition to detect early warning signes of stroke. There are two main different facial palsys: peripheral facial palsy and central facial palsy. The latter is tightly linked to stroke. By using mobile technology we plan to develop an algorithm able to detect central facial palsy.