EEG Reports and Big Data: Why a Structured Database Is Key

In the era of big data, unstructured clinical reports represent a barrier to information mining. EEGs reported in free text are difficult to leverage for research or population analysis. Structuring reports according to defined fields and standardized classifications opens the door to generating databases that can be used for clinical follow-up, quality audits, and multicenter studies.

Creating a well-organized database allows for answering epidemiological questions, assessing the frequency of abnormal patterns by age group, comparing results between hospitals, and even applying artificial intelligence algorithms that learn to identify relevant patterns. This is only possible when data is coded in a structured and consistent manner, which requires standardization from the moment the report is captured.

In this context, SIMPLEEG represents a tool that not only improves clinical workflow but also acts as a generator of data ready for scientific analysis. This opens up new possibilities for participating in collaborative research, publishing high-quality observational studies, and contributing to the advancement of knowledge in neurophysiology and epilepsy.