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This system automatically augments a patient's Electronic Health Record (EHR) with pertinent information from NLM resources. The software runs as background agents, both at a hospital and at NLM. The hospital uses our APIs to integrate the search setup and to display and store results in their existing EHR system. For clinical settings that have no means to use the API, a Web-based interface allows information requests to be manually entered. The InfoBot API integrated with the NIH Clinical Center’s EMR system, CRIS, is in daily use through the Evidence-Based Practice tab in CRIS since July 2009. Information provided to a medical institution is customized according to the institution's requirements. The requirements define the EMR fields that are provided to InfoBot and the knowledge sources to be mined for information provided by InfoBot. Each set of requirements for a specific clinical task and user group is called a Ruleset. Medical institutions can define as many rulesets as are needed to support their daily practice with evidence.

Jao CS, Fung KW, Demner-Fushman D. Identifying indications for drugs in drug package inserts. AMIA Annual Symposium Proceedings 2010. November 2010
Bodenreider O, Demner-Fushman D. Investigating drug classes in biomedical terminologies from the perspective of clinical decision support. AMIA Annu Symp Proc. 2010 Nov 13;2010:56-60.
Demner-Fushman D, Chapman WW, McDonald CJ. What can natural language processing do for clinical decision support? J Biomed Inform. 2009 Oct;42(5):760-72. doi: 10.1016/j.jbi.2009.08.007. Epub 2009 Aug 13.
Demner-Fushman D, Seckman C, Fisher C, Hauser SE, Clayton J, Thoma GR. A prototype system to support evidence-based practice AMIA Annu Symp Proc. 2008 Nov 6:151-5.