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.
Automatic Analysis of Electronic Discharge Letters as a Means to Evaluate the Continuity of Information and of Patient Care / S. Ballerio - In: Rethinking Electronic Publishing: Innovation in Communication Paradigms and Technologies / [a cura di] S. Mornati, T. Hedlund. - [s.l] : Edizioni Nuova Cultura, 2009. - ISBN 9788861343238. - pp. 607-612 (( Intervento presentato al 13. convegno ElPub tenutosi a Milano nel 2009.
|Titolo:||Automatic Analysis of Electronic Discharge Letters as a Means to Evaluate the Continuity of Information and of Patient Care|
|Parole Chiave:||Text mining; Continuity of care; Discharge letters|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||2009|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|