Automated Clinical Data Extraction to Enhance Toxicology Services and Improve Emergency Medicine Outcomes: Project STREAM (System for Toxicology Research and Emergency Medicine)
Grant ID: EMLE-295R42-2024-STAIB
Project Summary
Problem: Emergency Medicine research faces significant challenges due to outdated data collection methods, particularly when it comes to the use of clinical data. These issues lead to incomplete datasets and inaccuracies, negatively affecting research quality and patient care. Clinical Toxicology, a sub-specialty of Emergency Medicine, is an excellent example, where currently crucial clinical datasets are compromised by inconsistent practices and manual entry.
Research Question: How can we improve access to emergency care, improve the burden that toxicology patients place upon the emergency care system, and enhance data collection and efficiency in toxicology services by developing automated data extraction methods and standardized practices?
Proposed Solution: We propose the development of the STREAM, an automated clinical data extraction system designed to enhance data collection and analysis in emergency medicine.
Significance: This project addresses the enormous burden that toxicology patients place on emergency care. Toxicology is an area of emergency practice which relies on clinical information contained in databases to support the delivery of quality patient care. By improving data quality and standardizing practices, we aim to enhance research accuracy and optimize resources.
Innovation: The project introduces an innovative, cutting-edge automated tool to overcome current inefficiencies in data collection. This approach will enhance data management and research capabilities, providing a model for other clinical research areas.
Expected Impact: The project will improve the management of poisoning and toxic exposure, benefiting other emergency clinical research areas that rely on detailed data analysis. We anticipate higher-quality data, reduced manual workload, and better patient outcomes.
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