• Ila D Mapp, Leslie L Davis, and Heidi Krowchuk.
• Ila D. Mapp, MSN(c), RN, CCRN, is clinical nurse II in the Adult Specialty Critical Care Team at the University of North Carolina Hospitals, Chapel Hill. Leslie L. Davis, PhD, RN, ANP-BC, FAANP, FAHA, is assistant professor of nursing at the University of North Carolina at Greensboro, School of Nursing. Heidi Krowchuk, PhD, RN, FAAN, is associate professor of nursing at the University of North Carolina at Greensboro, School of Nursing.
• Dimens Crit Care Nurs. 2013 Nov 1;32(6):300-9.

AbstractResearchers have found that patients exhibit physiological changes up to 8 hours prior to an arrest event. Deaths have been attributed to a lack of observation, lack of documentation of observations, inability of a caregiver to recognize early signs of deterioration, and lack of communication between healthcare providers. This integrative review examines early warning scoring systems and their effectiveness in predicting a patient's potential for deterioration and considers whether these scoring systems prevent unplanned intensive care unit admissions and/or death. Three databases (MEDLINE, CINAHL [Cumulative Index to Nursing and Allied Health Literature], and the Cochrane Collaboration) were searched to identify the instruments and clinical support systems available to assist healthcare personnel in recognizing early clinical deterioration. Key search words included modified early warning score, early warning score, early warning systems, deteriorating patient, patients at risk, shock index, track and trigger systems, and failure to rescue. Two prior literature reviews examined early warning scoring systems and their effects on patient outcomes; however, the most recent one reviewed only articles published before 2007. This review examined studies of early warning systems and the incorporation of clinical support published from 2007 to 2012. Nine studies fitting the search criteria were included in this review. Early warning scoring systems that interface with electronic medical records and are supplemented with decision aides (algorithms) and clinical support systems produce an effective screening system for early identification of deteriorating patients. This multifaceted approach decreases unplanned intensive care unit admissions and hospital mortality.

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