Prehospital Emergency Medical Services and the quality of medical care after arriving emergency room are the two most important things considered by the patients when the patients get injured, encountered diseases and other emergency situations, thus, Emergency Medical Technicians are not only required to have professional first aid skills but also needed to give suitable rescue treatments in the right time at the scene, and then send the emergency patient to the most appropriate hospital for continuous care. However, if the patient needs to transferred to another hospital because of the first hospital lacks physicians or equipments, it will cause the delay on the time for the patient to receive medical care, that will lead to the increasing of risk on prognosis. Therefore, decisions made by EMTs are very important, because it is closely related to the prognosis of emergency patient and the quality of emergency medical services. For the past three years, we committed to the study of pre-hospital emergency medical decision Model (NSC 99-2221-E-038-009-MY2 and 101-2221-E-038-005-). We have established an emergency decision-making model by using 11 factors of Emergency Medical Services (EMS). The AHP (Analytic Hierarchy Process, AHP) was used to calculate the weighting of the factors to complete the model’s objective function. Base on the above results, in the new project, we will continue the cooperation with the Taipei City Fire Department on data collection and modify the decision-making model, and use a variety of data mining methods to verify the correctness of the parameters. We will also try to link the emergency database we built to another database, such as National Health Insurance Research Database to strengthen the integrity of our database and use it to analyze the relationship between the existing decision model and the prognosis of emergency patients. In this two-year project, we will focus on three work items: (1)To verify and enhance the parameters of the decision-making and the objective function that we have established, (2)To analyze the related features of the decision model using current emergency medical service data and geographic model, and (3)To build a statistical model using historical data analysis for the prognosis of emergency patients. In the first year, we will use several data mining algorithms to evaluate the parameters of the decision model and try to simplify it. In addition, we will search for the potential rules inform the history emergency medical services data by using association rules, classification tree or others data mining methods. We will also use the functions of geographic information system (GIS) to analyze the relation between the locations of emergency cases and the sending hospitals. In the second year, we will integrate our historical emergency medical services database to another database (the national health insurance database) to analyze the effectiveness and find useful rules based on the decision model and the prognosis of emergency patients. We expect the results of this project will give a good reference for EMT training and policy decision-making for Taipei City Fire Department.
|Effective start/end date||8/1/13 → 7/31/14|
- Emergency Medical Service
- Decision-making Model
- Data Mining
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