Niclas Johansson1, Carl Spindler1, John Valik1, Veronica Vicente2. 1. Karolinska Institutet, Department of Medicine, Solna, Infectious Diseases Unit, Karolinska University Hospital, Stockholm, Sweden; Department of Infectious Diseases, Karolinska University Hospital Solna, Stockholm, Sweden. 2. Karolinska Institutet, Department of Clinical Science and Education and Section of Emergency Medicine, Södersjukhuset and Academic EMS, Stockholm, Sweden; Ambulanssjukvården i Storstockholm (AISAB, Ambulance Medical Service in Stockholm), Sweden. Electronic address: veronica.vicente@ki.se.
Abstract
OBJECTIVE: To develop and validate a pre-hospital decision support system (DSS) for the emergency medical services (EMS), enabling the identification and steering of patients with critical infectious conditions (i.e., severe respiratory tract infections, severe central nervous system (CNS) infections, and sepsis) to a specialized emergency department (ED) for infectious diseases. METHODS: The development process involved four consecutive steps. The first step was gathering data from the electronic patient care record system (ePCR) on patients transported by the EMS, in order to identify retrospectively appropriate patient categories for steering. The second step was to let a group of medical experts give advice and suggestions for further development of the DSS. The third and fourth steps were the evaluation and validation, respectively, of the whole pre-hospital DSS in a pilot study. RESULTS: A pre-hospital decision support tool (DST) was developed for three medical conditions: severe respiratory infection, severe CNS infection, and sepsis. The pilot study included 72 patients, of whom 60% were triaged to a highly specialized emergency department (ED-Spec) with an attending infectious disease physician (ID physician). The results demonstrated that the pre-hospital emergency nurses (PENs) adhered to the DST in 66 of 72 patient cases (91.6%). For those patients steered to the ED-Spec, the assessment made by PENs and the ID physician at the ED was concordant in 94% of cases. CONCLUSIONS: The development of a specific DSS aiming to identify patients with three different severe infectious diseases appears to give accurate decision support to PENs when steering patients to the optimal level of care.
OBJECTIVE: To develop and validate a pre-hospital decision support system (DSS) for the emergency medical services (EMS), enabling the identification and steering of patients with critical infectious conditions (i.e., severe respiratory tract infections, severe central nervous system (CNS) infections, and sepsis) to a specialized emergency department (ED) for infectious diseases. METHODS: The development process involved four consecutive steps. The first step was gathering data from the electronic patient care record system (ePCR) on patients transported by the EMS, in order to identify retrospectively appropriate patient categories for steering. The second step was to let a group of medical experts give advice and suggestions for further development of the DSS. The third and fourth steps were the evaluation and validation, respectively, of the whole pre-hospital DSS in a pilot study. RESULTS: A pre-hospital decision support tool (DST) was developed for three medical conditions: severe respiratory infection, severe CNS infection, and sepsis. The pilot study included 72 patients, of whom 60% were triaged to a highly specialized emergency department (ED-Spec) with an attending infectious disease physician (ID physician). The results demonstrated that the pre-hospital emergency nurses (PENs) adhered to the DST in 66 of 72 patient cases (91.6%). For those patients steered to the ED-Spec, the assessment made by PENs and the ID physician at the ED was concordant in 94% of cases. CONCLUSIONS: The development of a specific DSS aiming to identify patients with three different severe infectious diseases appears to give accurate decision support to PENs when steering patients to the optimal level of care.