Milos Hauskrecht receives the Homer R. Warner Award during the American Medical Informatics Association meeting in Washington DC

Milos Hauskrecht, an associate professor of Computer Science, University of Pittsburgh, has received the Homer R. Warner Award during the closing ceremony of the Anual Americal Medical Informatics Association meeting in Washington DC in November 2010 for his work on the conditional outlier-based clinical alerting methodology.

The award is named for Homer R. Warner, MD, PhD, a pioneer in the field of informatics and the founder of the Department of Biomedical Informatics at the University of Utah. This awarded is presented to the paper that best describes approaches to improving computerized information acquisition, knowledge data acquisition and management, and experimental results documenting the value of these approaches.

M. Hauskrecht, M. Valko, I.Batal, G. Clermont, S. Visweswaran, G. Cooper. Conditional Outlier Detection for Clinical Alerting, Annual American Medical Informatics Association (AMIA) Symposium , November 2010 [Homer Warner Award]

Abstract We develop and evaluate a data-driven approach for detecting unusual (anomalous) patient management actions using past patient cases stored in an electronic health record (EHR) system. Our hypothesis is that patient-management actions that are unusual with respect to past patients may be due to a potential error and that it is worthwhile to raise an alert if such a condition is encountered. We evaluate this hypothesis using data obtained from the electronic health records of 4,486 post-cardiac surgical patients. We base the evaluation on the opinions of a panel of experts. The results support that anomaly-based alerting can have reasonably low false alert rates and that stronger anomalies are correlated with higher alert rates.