This paper describes the process and methodology of designing and developing a mobile support system to triage abdominal pain in the emergency room (ER) of a hospital. Application of rough sets ...theory and fuzzy measures to data collected at Children's Hospital of Eastern Ontario allowed us to identify the most relevant clinical symptoms and signs while evaluating an abdominal pain patient. This information was used to develop a multilevel
clinical algorithm that forms the reasoning module of a clinical support system. We describe a client system called Mobile Emergency Triage (MET) that is installed on Palm handheld and that can be used to triage a child irrespective of the available information. We present MET's functions allowing for the electronic data capture and wireless data transfer.
The acute scrotum is a clinical condition in boys and adolescent males that is normally first assessed in the Emergency Department of a hospital. We used data from the patients' charts and applied ...knowledge discovery technique based on rough set theory to develop a clinical decision algorithm for iriaging patients with this condition. As demonstrated by a limited retrospective evaluation, the algorithm supports early triage decisions on the basis of readily available information, resulting in good triage accuracy. In order to make the algorithm usable in clinical practice, to integrate it with the workflow, and to make it available at the point of care, we implemented it as an application in the mobile clinical decision support environment called MET (Mobile Emergency Triage). MET uses ontologies to represent domains of various acute presentations and triage support functionalities, and renders specific applications on demand from these ontologies.
The paper describes design and implementation of a mobile clinical triage support system for the evaluation of acute appendicitis in childhood. The MET (mobile emergency triage) system was developed ...according to the general principles of client server architecture, with mobile clients running on palm handhelds. Decision model implemented in MET follows the principles of evidence based medicine based on retrospective data. We applied a hybrid methodological approach involving fuzzy measures and rough set theory to develop this model. In a randomized retrospective trial, the triage recommendation of the MET system had a sensitivity of 86.7% and a specificity of 85.7%. MET is a fully functional mobile clinical triage support system that provides triage recommendation at the point of care, irrespective of the completeness of the clinical information. It also allows for data capture and interaction with the hospital's information system. Given mobility of MET and its easy to use features, we are proposing a system that can both support evidence based emergency room patient care, and at the same time, streamline the bedside triage of a child with abdominal pain.
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