HEALTH SECTOR
UANL
The current workflow for documenting gastroenterology procedures presents several critical deficiencies that impact data quality, operational efficiency, and medical training:
◆ Lack of Data Integrity and Standardization: Manual reports with errors and omissions, without standardized capture of clinical information.
◆ Inaccessibility of Information: Impossibility of analyzing aggregated data due to the lack of a centralized database, limiting clinical research and analysis.
◆ Lack of Assessment Tools: Absence of an objective system to measure the quality of resident physician reports, making feedback difficult.
◆ Operational Inefficiency and Information Silos: The considerable time consumed by report writing and the disintegrated management of assets (text, images, video, audio) created fragmented information.
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The Solution
We developed a web application with a cloud-based database (AWS) that centralizes and standardizes all endoscopic reports. The solution incorporates Artificial Intelligence (AI) and configurable templates to ensure data integrity and consistency by implementing the following functions:
● Intelligent Agent: Allows physicians to perform complex database queries using natural language.
● Speech-to-Text Transcription: Streamlines medical report writing.
● Objective Assessment Module: Comparison algorithms to measure the quality of student reports.
● Integrated Asset Management: Unified management of text, images, audio, and video from the study.
Business Impact
The implementation of this solution generated a positive impact on the UANL, optimizing its operations and strengthening its capabilities:
Optimization of Clinical Time and Operational Efficiency: Significant reduction in report writing time thanks to voice-to-text transcription and terminology standardization using AI and templates, ensuring unified report classification.
Creation of a Strategic Data Asset: Consolidation of clinical information in a centralized cloud database, converting isolated data into strategic assets and laying the foundation for future advanced analytics and predictive models.
Objective and Scalable Medical Assessment: Access to an objective tool for training specialists, eliminating subjectivity and enabling systematic measurement of the quality and number of procedures performed by students. This creates a scalable feedback process based on accurate data.
Clinical Intelligence and Accelerated Research: Transformation of the database into an active source of knowledge, allowing physicians to obtain instant clinical and operational insights through natural language queries. This allows them to identify disease patterns, evaluate the effectiveness of a specific treatment, or analyze complication rates by procedure to improve the quality of care on a day-to-day basis.
