A Data Pipeline for Enhancing Quality of MAUDE-Based Studies.

The increasing use of MAUDE reports in patient safety research highlights the importance of understanding the processing and dissemination of open-access MAUDE data. However, the absence of a structured data pipeline undermines the reproducibility and transparency of studies relying on MAUDE data. In response, we conducted a comprehensive analysis of a recent study on endoscopic clips, assessing methodologies and results. We advocate for implementing an extract, transform, and load (ETL) pipeline, utilizing openFDA and integrating keyword search strategies and data visualization techniques. This approach aims to enhance the quality of MAUDE-based studies, ensuring their reproducibility and transparency. Moreover, ETL serves as a cornerstone in data engineering, enabling real-time data management and quality assurance, thus promoting the sustainability and collaboration of MAUDE-based patient safety research.