As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Case finding for epidemiologic registries still relies mainly on a manual process. In this paper, we show that retrieval information tools could be a complementary way to identify cases for a pediatric malformation registry. We developed a full-text and metadata search engine plugged to a clinical documents repository and used it to identify Epi/Hypospadia and Spina bifida cases. The queries were enriched with Snomed terminologies. We compared the performances of this prototype versus the hospital DRG database (classical method). The best precisions of prototype for identification of Spina bifida and Epi/Hypospadia were respectively 73% and 87%. The prototype overlap with the DRG system was 83% and 97%. Compared to DRG, 13 new not referenced and 2 miscoded cases were detected. This free full-text retrieval system prototype allows efficiently reusing clinical documents for case finding for an epidemiologic purpose.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.