• Vitaly Herasevich, Daryl J Kor, Arun Subramanian, and Brian W Pickering.
• Division of Critical Care Medicine, Department of Anesthesiology, Mayo Clinic, Rochester, MN 55905, USA. Herasevich.vitaly@mayo.edu
• J Clin Monit Comput. 2013 Aug 1;27(4):443-8.

AbstractThe intensive care unit (ICU) environment is rich in both medical device and electronic medical record (EMR) data. The ICU patient population is particularly vulnerable to medical error or delayed medical intervention both of which are associated with excess morbidity, mortality and cost. The development and deployment of smart alarms, computerized decision support systems (DSS) and "sniffers" within ICU clinical information systems has the potential to improve the safety and outcomes of critically ill hospitalized patients. However, the current generations of alerts, run largely through bedside monitors, are far from ideal and rarely support the clinician in the early recognition of complex physiologic syndromes or deviations from expected care pathways. False alerts and alert fatigue remain prevalent. In the coming era of widespread EMR implementation novel medical informatics methods may be adaptable to the development of next generation, rule-based DSS.

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