Abstract
BackgroundA huge amount of clinical data is daily generated and it is usually filed in clinical reports as natural language. Data extraction and further analysis requires reading and manual review of each report, which is a time consuming process. With the aim to test folksonomy to quickly obtain and analyze the information contained in medial reports we set up this study. Methods and objectivesWe have used folksonomy to quickly obtain and analyse data from 1631 discharge clinical reports from Nephrology Department of Hospital del Mar, without the need to create an structured database. ResultsAfter posing some questions related to daily clinical practice (hypoglycaemic drugs used in diabetic patients, antihypertensive drugs and the use of renin angiotensin blockers during hospitalisation in the nephrology department and data related to emotional environment of patients with chronic kidney disease) this tool has allowed the conversion of unstructured information in natural language into a structured pool of data for its further analysis. ConclusionsFolksonomy allows the conversion of the information contained in clinical reports as natural language into a pool of structured data which can be further easily analysed without the need of the classical manual review of the reports.
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