Prognostic Accuracy of the Hamilton Early Warning Score (HEWS) Among Hospitalized Patients Assessed by a Rapid Response Team
CCCF ePoster library. Fernando S. Nov 9, 2018; 233427; 102
Dr. Shannon Fernando
Dr. Shannon Fernando
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Rate & Comment (0)

Introduction: Patients admitted to hospital wards are at risk of future deterioration. Rapid Response Teams (RRTs) respond to hospitalized patients with deterioration, and help determine subsequent management, including Intensive Care Unit (ICU) admission. In order to optimize disposition, RRTs must appropriately identify patients at risk of adverse clinical outcomes.     


Objectives: We sought to evaluate the prognostic accuracy of the Hamilton Early Warning Score (HEWS) for prediction of in-hospital mortality and ICU admission among hospitalized patients. The prognostic accuracy of HEWS was compared to the National Early Warning Score 2 (NEWS2). We secondarily evaluated the accuracy of HEWS in a subgroup of RRT patients with suspected infection.


Methods: We utilized prospectively collected registry data (2012-2016) from two hospitals in Ottawa, Ontario. Consecutive hospitalized adult patients assessed by the RRT were included. Vital signs and laboratory values were collected at the time of RRT assessment. Patients were followed to the point of in-hospital death or hospital discharge. ‘Suspected infection’ was defined as concomitant administration of antibiotics and sampling of body fluid cultures. The Number Needed to Examine (NNE) was calculated, which indicates the number of patients that need to be evaluated in order to detect one patient who will die in-hospital, and is an indirect measure of the cost-effectiveness of each alert.


Results: 5,995 patients were included in analysis, of whom 1,833 (30.6%) died in-hospital. 1,708 patients (28.5%) met criteria for ‘suspected infection’. A HEWS above the low-risk threshold (≥ 3) had a sensitivity of 90.8% (95% CI: 89.4-92.1) and specificity of 32.4% (95% CI: 31.0-33.9) for in-hospital mortality, with a NNE of 2.7 (95% CI: 2.6-2.8). A HEWS above the moderate-risk threshold (≥ 5) had a sensitivity of 73.4% (95% CI: 71.3-75.4) and specificity of 60.7% (95% CI: 59.2-62.2) for in-hospital mortality, with a NNE of 2.2 (95% CI: 2.1-2.3). Finally, a high-risk HEWS (≥ 9) had a sensitivity of 33.9% (95% CI: 31.8-36.2) and specificity of 99.5% (95% CI: 99.3-99.7) for in-hospital mortality, with a NNE of 1.0 (95% CI: 1.0-1.1). The area under the receiver operating characteristic (ROC) curve for mortality was 0.743 (95% CI: 0.730-0.757) for HEWS, and 0.754 (95% CI: 0.733-0.782) for NEWS2. Among patients with suspected infection, a HEWS ≥ 3 had a sensitivity of 91.2% (88.6-93.4) and specificity of 33.3 (95% CI 30.6-36.1) for in-hospital mortality, with a NNE of 2.5 (95% CI: 2.4-2.5). A HEWS ≥ 5 had a sensitivity of 74.8 (95% CI: 70.8-78.4) and specificity of 54.7 (51.8-57.5), with a NNE of 2.4 (95% CI: 2.3-2.5).     


Conclusions: The HEWS has comparable clinical accuracy to NEWS2 for prediction of in-hospital mortality among RRT patients. This external application of the HEWS suggests that it may be a valuable tool in the risk-stratification of hospitalized patients with acute deterioration. Early detection, appropriate risk-stratification, and optimal disposition in this patient population have been associated with improved outcomes.

    This eLearning portal is powered by:
    This eLearning portal is powered by MULTIEPORTAL
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.

Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.

Save Settings