Early Warning Scores to Predict Noncritical Events Overnight in Hospitalized Medical Patients: A Prospective Case Cohort Study

Abstract

Background Physicians are often called to evaluate patients overnight with varying levels of clinical deterioration. Early warning scores predict critical clinical deterioration in patients; however, it is unknown whether they are able to reliably predict which patients will need to be seen overnight and whether these patients will require further resource use. Methods A prospective case cohort study of 522 patient nights in a single tertiary care hospital in Vancouver, British Columbia, Canada, was conducted to assess the ability of Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS) to predict patients who will need to be seen overnight by physicians and will require other healthcare resources. Prediction ability was assessed using area under the receiver operating characteristic curve and logistic regression models. Results The MEWS and NEWS both significantly predicted which patients needed to be seen overnight, and area under the receiver operating characteristic curves (95% confidence interval) for MEWS and NEWS were 0.72 (0.66–0.78) and 0.69 (0.63–0.76), respectively. Odds ratios (95% confidence interval) for MEWS and NEWS predicting need to be seen overnight were 1.52 (1.34–1.73) and 1.22 (1.14–1.31), respectively. Conclusions Both MEWS and NEWS have fair ability to predict patients who will need to be seen overnight. This may be useful for improving handover and resource allocation for overnight care.

A novel predictive analytics score reflecting accumulating disease burden—an investigation of the cumulative CoMET score

“…The prediction of deterioration in hospitalized patients has traditionally utilized track-and-trigger systems, including the National Early Warning Score (NEWS), the Modified Early Warning Score (MEWS), the Rothman Index (RI) and others (Rothman et al 2013, Alam et al 2014, Smith et al 2014, Churpek et al 2012, Nannan Panday et al 2017, Green et al 2018, Rojas et al 2018, Bartkowiak et al 2019, Bittman et al 2020. These scoring systems have benefits including their relative ease of use and accessibility, yet suffer because they largely rely on vital signs and lab tests, which are variously intermittent, delayed, incorrect, unvalidated or indeed never taken (Grant 2018, Grant and Crimmons 2018, Grant 2019, Gerry et al 2020.…”

Using an Early Warning Score for Nurse Shift Patient Handover: Before-and-after Study

“…In addition, we posted the NEWS2 system in the wards to facilitate recognition of the system and clinical response. Nurses were asked to use a checklist to calculate the NEWS2 system, focusing on patients at high risk of deterioration based on vital sign abnormalities [20]. The first author reviewed the completed checklists during her frequent visits to the wards.…”

“…However, handover can be a risk to patient safety because of the possibility of loss of patient care information. A recommended practice regarding patient handover is prioritizing the handover of patients at the highest risk of deterioration and clearly communicating patient stability [20]. EWSs can be used to prioritize patients at risk of deterioration during nurse shift handovers in hospital wards.…”

Predictive analytics that reflect disease burden – the cumulative COMET score

“…The prediction of deterioration in hospitalized patients has traditionally utilized track-and-trigger systems, including the National Early Warning Score (NEWS) and others. [24][25][26][27][28][29][30][31][32][33] These scoring systems have benefits including their relative ease of use and accessibility, yet suffer because they largely rely on vital signs and lab tests, which are variously intermittent, delayed, incorrect, unvalidated or indeed never taken. [34][35][36][37] Few take account of crucial information contained within continuous cardiorespiratory monitoring.…”