An early warning system to predict overcrowding in emergency rooms
In recent years, acute care providers have had difficulties responding to crowding situations in their acute care facilities (e.g. emergency rooms). This can threaten both quality and access to these life-saving health care facilities. The General Practitioner Post (GP-Post) and the Emergency Department (ED) of Winterswijk want to know if it is possible to develop an early warning system for (over)crowding based on their historical data (patient records) combined with external data sources, like for instance weather statistics. An early warning system for (over)crowding may possibly allow acute care organisations to alleviate their crowding problems. Such an early warning system could be built using machine learning techniques.
Goal of the Research
Identification of variables predicting (over)crowding of the acute care facility.
Development of an early warning system for overcrowding of the acute care using machine learning.
Profile of the student
Interested in novel statistical techniques, motivated to work with very large, complicated data sets. Organized. Familiar with working with R scripts.
Contact: Dr Stéphanie van den Berg, email@example.com, tel: 053 489 2422, room Cubicus B325