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Research Program Mobile Emergency Triage (MET) research is about creating a methodological framework for anytime and anywhere decision support (A3Support) for ED triage decision-making. We define the triage as an Emergency Department (ED) activity that extends beyond the initial assessment and categorization typically completed by a triage nurse to include the initial assessment and management decisions made by the emergency physician (EP). The triage decision making process involves gathering and evaluating information about a patient (history, physical examination and investigations), and applying medical knowledge to decide on a course of definitive management. This may include further investigations and/or several therapeutic options. The triage disposition may result in discharging the patient with non-serious complaints, or may involve diagnostic tests, specialty consultations, and interim management, which may lead to a definitive diagnosis.
The use and role of A3Support is best illustrated by the following scenario: It is another busy evening in the ED. The EP is summoned to see a young boy who has just arrived, suffering from a severe asthma exacerbation. The CDSS, being instructed about the EP’s task, searches for the boy’s admission record and requests it from the hospital’s patient record system. Since the patient’s registration has identified his problem as asthma, the DSS invokes the appropriate asthma decision model and clinical pathway on the EP’s mobile device. The patient’s condition is assessed and recorded, a first round of medications is proposed, and the system indicates that admission to hospital will likely be needed, based on his severity. Rather than wait through several hours of treatment to see if the patient will fail discharge and require admission, the EP initiates the admission process. The nurse is instructed to reassess the child in one hour, using her desktop computer to update the DSS with the patient’s status. In the meantime, the EP starts to evaluate a new patient. During his absence, the DSS has monitored the laboratory system in the background for results, retrieved them, and automatically included this new data for the next recommendation. The system now presents the EP with a revised triage recommendation regarding the severity of asthma exacerbation confirming the need for hospital admission. As the EP’s shift is now over, he transfers care of the patient to his colleague. The patient’s data and suggested recommendation become available on the receiving physician’s handheld to facilitate continuity of care. Our long-term goal is to create methodological and applied medical informatics solutions that take full advantage of the wealth of information that will be available through Electronic Health Records (EHR) initiative. In that sense we are looking beyond the EHR and aim at providing the methodologies for using this repository of information in clinical decision support systems (CDSS) for evidence-based decision-making. |
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