title: Wireless clinical alerts and patient outcomes in the surgical intensive care unit.
abstract: Errors in medicine have gained public interest since the Institute of Medicine published its 1999 report on this subject. Although errors of commission are frequently cited, errors of omission can be equally serious. A computerized surgical intensive care unit (SICU) information system when coupled to an event-driven alerting engine has the potential to reduce errors of omission for critical intensive care unit events. Automated alerts and patient outcomes were prospectively collected for all patients admitted to a tertiary-care SICU for a 2-year period. During the study period 3,973 patients were admitted to the SICU and received 13,608 days of care. A total of 15,066 alert pages were sent including alerts for physiologic condition (6,163), laboratory data (4,951), blood gas (3,774), drug allergy (130), and toxic drug levels (48). Admission Simplified Acute Physiology Score and Acute Physiology and Chronic Health Evaluation II score, SICU lengths of stay, and overall mortality rates were significantly higher in patients who triggered the alerting system. Patients triggering the alert paging system were 49.4 times more likely to die in the SICU compared with patients who did not generate an alert. Even after transfer to floor care the patients who triggered the alerting system were 5.7 times more likely to die in the hospital. An alert page identifies patients who will stay in the SICU longer and have a significantly higher chance of death compared with patients who do not trigger the alerting system.
authors.affiliation: Burns and Allen Research Institute, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA.
authors.forename: Kevin
authors.initials: K
authors.lastname: Major
authors.forename: M Michael
authors.initials: MM
authors.lastname: Shabot
authors.forename: Scott
authors.initials: S
authors.lastname: Cunneen
mesh_terms: D003422:Critical Care / Q000379:methods; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D011446:Prospective Studies; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D016896:Treatment Outcome