Automatic Analysis of Electronic Discharge Letters as a Means to Evaluate the Continuity of Information and of Patient Care
||Automatic Analysis of Electronic Discharge Letters as a Means to Evaluate the Continuity of Information and of Patient Care
||ELPUB2009. Rethinking Electronic Publishing: Innovation in Communication Paradigms and Technologies - Proceedings of the 13th International Conference on Electronic Publishing held in Milano, Italy 10-12 June 2009 / Edited by: Susanna Mornati and Turid Hedlund. ISBN 978-88-6134-326-6, 2009, pp. 607-612
||Joint Commission International standard 3.2 on Access to Care and Continuity of Care states that discharge letters should contain information about follow-up instructions of doctors to patients. We developed a text mining system to analyze a collection of 413 discharge letters of heart failure patients and checked their compliance with standard 3.2. We built a domain-specific ontology and a thesaurus and mined the collection with CASOS AutoMap. After validation, the system sensitivity was 0.484; specificity was 0.834; positive predictive value was 0.555; negative predictive value was 0.790. Improving these results requires more powerful natural language processing tools, but text mining seems a promising way to evaluate the continuity of information and of care.
||Text Mining; Continuity of Care; Discharge Letters
||file.pdf (218,505 bytes)
Post discussion ...
These pages are best viewed with any standards compliant browser (e.g. Mozilla).