Automated identification of adverse events related to central venous catheters.

Methods for surveillance of adverse events (AEs) in clinical settings are limited by cost, technology, and appropriate data availability. In this study, two methods for semi-automated review of text records within the Veterans Administration database are utilized to identify AEs related to the placement of central venous catheters (CVCs): a Natural Language Processing program and a phrase-matching algorithm. A sample of manually reviewed records were then compared to the results of both methods to assess sensitivity and specificity.

Evaluation of SNOMED coverage of Veterans Health Administration terms.

Veterans Health Administration (VHA) is now evaluating use of SNOMED-CT. This paper reports the first phase of this evaluation, which examines the coverage of SNOMED-CT for problem list entries. Clinician expressions in VA problem lists are quite diverse compared to the content of the current VA terminology Lexicon.