EMDAI: Developing a machine-learning based decision support tool for Emergency Medical Dispatch

The Emergency Medical Dispatch (EMD) centers in Uppsala, Västmanland and Sörmland counties in Sweden provide a range of healthcare services to callers beyond only ambulances, including mobile primary care teams, referrals to nursing advice lines and primary care centers, and alternative forms of transport to the hospital. An effective decision support system capable of helping dispatch nurses to differentiate among an increasingly elderly patient population with multiple comorbidities is critical to safely steering callers to the appropriate level of care. In a two year project funded by the Swedish Innovation Agency (Vinnova), predictive models based on data currently collected by the EMD center are being developed. The goal of the project is to investigate whether a decision support tool based on machine learning can result in more accurate decisions and improved patient outcomes among callers who’s condition does not call for an emergency ambulance response.

Using trigger tools to identify triage errors by ambulance dispatch nurses in Sweden: an observational study


Picture of project leader Douglas Spangler
Douglas Spangler

Douglas Spangler, PI

E-mail: douglas.spangler@pubcare.uu.se