Assessing the validity and relevance of a high-frequency database to optimize the quality of care in Quebec's intensive care units using massive data science


The 99 Intensive Care Units in Quebec care for the most severely ill patients, whose mortality rate and risk of sequelae are very high. Optimizing the management of each patient and monitoring the quality of each unit would save lives and health costs.
We have developed an intensive care database (BD-SI) containing all the data recorded at high frequency by different technologies at the bedside.
The objectives of our project are:
1- To consolidate the development of the BD-SI and its integration in the CHU Sainte Justine network;
2- Demonstrate the validity of the database;
3- Implement the automatic extraction of quality criteria suggested by INESSS;
4- Demonstrate the feasibility of implementing computerized clinical decision support system on this infrastructure.
This will lead to optimized care for each critical patient, with expected gains in mortality or sequelae, to improved efficiency of critical care professionals, and to an automatic assessment of each unit quality indicators, with benchmarking capacity.