Introduction The Institute for Healthcare Improvement’s (IHI) 100,000 Lives Campaign challenged hospitals to reduce adverse events by implementing Rapid Response Teams. These teams are often activated by a single provider who notices a change in one aspect of the patient’s condition. Despite increased awareness, suboptimal care of deteriorating patients is a life-threatening problem that still frequently occurs. Systems known as early warning scores (EWS) identify at-risk patients and can get needed expert help to the bedside faster. Further, EWS systems that are automatically integrated within the electronic health record (EHR) may expedite advanced care. One newer EWS that integrates physiologic parameters, lab values and nursing assessment from the EHR is the Rothman Index (RI); our objective was to critically appraise evidence for which EWS system is most effective in early prediction of adverse events (e.g. cardiac/respiratory arrest, unplanned upgrade to intensive care) in hospitalized adult inpatients in an acute care setting. Methods A literature search was conducted using CINAHL, PubMed MEDLINE, and the Cochrane Database of Systematic Reviews. Gray literature from the Institute for Healthcare Improvement (IHI) was also reviewed and an ancestry search was conducted to collect all relevant articles. Only English language, scholarly, peer-reviewed studies published after 2006 were included; exclusion criteria included duplicates and studies of pediatric, obstetrical or behavioral health patients. After evaluating and excluding studies for content, eight remaining studies were appraised for quality and strength of evidence utilizing the Johns Hopkins (JH) Critical Appraisal Tool. Keywords: scorecards, early warning score, EWS, modified early warning score, MEWS, Rothman Index, track and trigger Results Six JH Level III studies, one JH Level I systematic review, and one JH Level II quasi-experimental study reviewed demonstrated variability among EWS systems in predicting adverse events. Of the JH Level III studies, all were conducted at single sites which limits generalizability to other settings. All of the studies which used the area under receiver operating curve (AUROC) method of data analysis scoring 0.8 or greater found acceptable degree of sensitivity and specificity in the EWS systems; all systems evaluated in the eight papers incorporated the use of the electronic medical record versus manual scoring. Implications Insufficient evidence currently exists related to establishing any one EWS system as superior. This is due to a lack of research comparing the use of a single EWS system across multiple institutions. Any organization wishing to create or implement an EWS system should pilot concepts before implementing housewide. Once an EWS system is reliably validated within an organization, it should be examined in the context of how it can be used to direct resources to a patient before they deteriorate and experience an adverse event.
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