Triage support at the point of care: Methodologies for ubiquitous systems in the emergency department

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The emergence of ubiquitous computing and increased access to electronic patient-specific information and evidence-based knowledge have created new opportunities for how clinical decision support can be provided at the point of care. Our goal is to study and develop a novel computing and decision support paradigm, using the Emergency Department triage of pediatric scrotal pain and pediatric asthma exacerbations as the clinical modalities that could benefit from this type of support. A specific hypothesis is that a ubiquitous support model can only be successfully implemented if the decision support system is designed to fit the Emergency Department workflow and needs of a diverse group of clinical users. The specific aims are: 1) To create a general ontological model of the triage support functionality for pediatric emergencies (using two presentations as examples). Based on existing retrospective chart data, we will develop a common "language" to represent basic concepts, and the relationships among them, including support requirements; 2) To create a ubiquitous decision support framework for the asthma exacerbation and scrotal pain triage support. Drawing from the ontology-driven design, we will develop a decision support system to provide clinicians with secure support functionality at the point of care; 3) To evaluate the decision model and decision support system in the Emergency Department setting. We will design and conduct a pilot evaluation trial of our theoretical solution in order to estimate its performance, analyze its fit with the workflow, and assess acceptance by clinicians. Key themes to be studied by our multidisciplinary team include knowledge representation, clinical decision support, data mining, and workflow alignment. LAY ABSTRACT: An increasing amount of complex information is available to doctors as they assess and treat patients. Patient care and health care delivery may be improved by bringing this information and computer-generated advice to the bedside. We want to help doctors make better decisions by building a portable decision support system for childhood emergencies (using asthma and scrotal pain as the case studies). Advances of this research can be used for other clinical problems and settings.