Distributed data-driven platform for urgent decision making in cardiological ambulance control

摘要

AbstractThis paper presents ongoing research aimed at developing a data-driven platform for clinical decision support systems (DSSs) that require integration and processing of various data sources within a single solution. Resource management is developed within a framework of an urgent computing approach to address changing requirements defined by the incoming flow of patients with urgent diseases. This work presents DSS for support of ambulance and emergency medical service management for patients with acute coronary syndrome (ACS) as a working example with integration distributed streaming data sources as well as data storages (containing electrocardiography (ECG) data, electronic medical records (EMR), real-time monitoring of medical facilities, and schedules of hospitals within a network). This DSS has been developed in collaboration with the Federal Almazov North-West Medical Research Centre in Saint Petersburg.Highlights•A conceptual architecture to diverse data integration within clinical DSS was proposed.•An urgent computing platform for data processing was developed to support reactive data-driven support for decision making.•An application of DSS to support ambulance and emergency medical service within a cases of acute coronary syndrome (ACS) was described.•Experimental study was conducted to show applicability of the proposed approach and to estimate performance characteristics.