Data-driven identification of unusual clinical actions in the ICU
Hauskrecht M, Visweswaran S, Cooper GF, Clermont G. Data-driven identification of unusual clinical actions in the ICU. In: Proceedings of the Annual Symposium of the American Medical Informatics Association (2013).
Developing methods to identify unusual clinical actions may be useful in the development of automated clinical alerting systems. We developed and evaluated a data-driven approach for identifying clinical actions such as omissions of medication orders or laboratory orders in the intensive care unit (ICU) that are unusual with respect to past patient care. We generated 250 medication-omission alerts and 150 laboratory-omission alerts using a database of 24,658 ICU patient admissions. These alerts were evaluated by a group of intensive care physicians. Overall, the true positive alert rate was 0.52, which we view as quite promising.