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Published on: November 9, 2016
MET system: a new approach to m-health in emergency triage
Wojtek Michalowski1, Roman Slowinski, Szymon Wilk
1School of Management, University of Ottawa, 136 Jean-Jacques Lussier St., Ottawa, K1N 6N5, Canada.
Abstract:
The MET (Mobile Emergency Triage) system is an m-health application that supports emergency triage of various types of acute pain at the point of care. The system is designed for use in the Emergency Department (ED) of a hospital and to aid physicians in disposition decisions. Given patient's condition, MET recommends a triage by consulting decision rules stored in the system's knowledge base. The rules have been created using a data mining method (based on rough set methodology) applied to data collected during a retrospective chart study and verified by the clinicians. MET is designed following the extended client-server architecture, suited for weak-connectivity conditions, where stable connection between clients and a server cannot be provided. The MET server interacts with the hospital's patient information system in order to retrieve information about patients admitted to the ED. It also stores current patients' demographic and clinical data to be exchanged with mobile clients. The MET mobile client, running on a Personal Digital Assistant (PDA), is used for collecting clinical data and supporting triage decisions. The support function runs solely on the client side, thus it can be invoked anytime and anywhere, even if there is no communication link with the server (e.g., there is no wireless network available in the ED). Due to implementation on PDAs and working in weak-connectivity conditions, the MET system is very well suited for use in the ED and fits seamlessly into the regular clinical workflow without introducing any hindrances or disruptions that are often reported when using stationary (i.e., working on desktop computers) clinical systems. The system facilitates patient-centered service and timely, high quality patient management. It provides recommendations using a limited amount of clinical data, normally available at the point of care. Furthermore, it provides a possibility for the structured evaluation of this data by an attending physician.
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