The impact of the use of the Early Warning Score (EWS) on patient outcomes: A systematic review

Resuscitation ◽  
2014 ◽  
Vol 85 (5) ◽  
pp. 587-594 ◽  
Author(s):  
N. Alam ◽  
E.L. Hobbelink ◽  
A.J. van Tienhoven ◽  
P.M. van de Ven ◽  
E.P. Jansma ◽  
...  
10.2196/13782 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. e13782
Author(s):  
Heidi Mcneill ◽  
Saif Khairat

Background Intensive care unit (ICU) readmissions have been shown to increase a patient’s in-hospital mortality and length of stay (LOS). Despite this, no methods have been set in place to prevent readmissions from occurring. Objective The aim of this literature review was to evaluate the impact of ICU readmission on patient outcomes and to evaluate the effect of using a risk stratification tool, the National Early Warning Score (NEWS), on ICU readmissions. Methods A database search was performed on PubMed, Cumulative Index of Nursing and Allied Health Literature, Google Scholar, and ProQuest. In the initial search, 2028 articles were retrieved; after inclusion and exclusion criteria were applied, 12 articles were ultimately used in this literature review. Results This literature review found that patients readmitted to the ICU have an increased mortality rate and LOS at the hospital. The sample sizes in the reviewed studies ranged from 158 to 745,187 patients. Readmissions were most commonly associated with respiratory issues about 18% to 59% of the time. The NEWS has been shown to detect early clinical deterioration in a patient within 24 hours of transfer, with a 95% CI of 0.89 to 0.94 (P<.001), a sensitivity of 93.6% , and a specificity of 82.2%. Conclusions ICU readmissions are associated with worse patient outcomes, including hospital mortality and increased LOS. Without the use of an objective screening tool, the provider has been solely responsible for the decision of patient transfer. Assessment with the NEWS could be helpful in decreasing the frequency of inappropriate transfers and ultimately ICU readmission.


2019 ◽  
Author(s):  
Heidi Mcneill ◽  
Saif Khairat

BACKGROUND Intensive care unit (ICU) readmissions have been shown to increase a patient’s in-hospital mortality and length of stay (LOS). Despite this, no methods have been set in place to prevent readmissions from occurring. OBJECTIVE The aim of this literature review was to evaluate the impact of ICU readmission on patient outcomes and to evaluate the effect of using a risk stratification tool, the National Early Warning Score (NEWS), on ICU readmissions. METHODS A database search was performed on PubMed, Cumulative Index of Nursing and Allied Health Literature, Google Scholar, and ProQuest. In the initial search, 2028 articles were retrieved; after inclusion and exclusion criteria were applied, 12 articles were ultimately used in this literature review. RESULTS This literature review found that patients readmitted to the ICU have an increased mortality rate and LOS at the hospital. The sample sizes in the reviewed studies ranged from 158 to 745,187 patients. Readmissions were most commonly associated with respiratory issues about 18% to 59% of the time. The NEWS has been shown to detect early clinical deterioration in a patient within 24 hours of transfer, with a 95% CI of 0.89 to 0.94 (<i>P</i>&lt;.001), a sensitivity of 93.6% , and a specificity of 82.2%. CONCLUSIONS ICU readmissions are associated with worse patient outcomes, including hospital mortality and increased LOS. Without the use of an objective screening tool, the provider has been solely responsible for the decision of patient transfer. Assessment with the NEWS could be helpful in decreasing the frequency of inappropriate transfers and ultimately ICU readmission.


Author(s):  
Diane E. Twigg ◽  
Lisa Whitehead ◽  
Gemma Doleman ◽  
Sonia El‐Zaemey

2021 ◽  
Author(s):  
Patricia Pauline M. Remalante-Rayco ◽  
Evelyn Osio-Salido

Objective. To assess the performance of prognostic models in predicting mortality or clinical deterioration among patients with COVID-19, both hospitalized and non-hospitalized Methods. We conducted a systematic review of the literature until March 8, 2021. We included models for the prediction of mortality or clinical deterioration in COVID-19 with external validation. We used the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and the GRADEpro Guideline Development Tool (GDT) to assess the evidence obtained. Results. We reviewed 33 cohort studies. Two studies had a low risk of bias, four unclear risks, and 27 with a high risk of bias due to participant selection and analysis. For the outcome of mortality, the QCOVID model had excellent prediction with high certainty of evidence but was specific for use in England. The COVID Outcome Prediction in the Emergency Department (COPE) model, the 4C Mortality Score, the Age, BUN, number of comorbidities, CRP, SpO2/FiO2 ratio, platelet count, heart rate (ABC2-SPH) risk score, the Confusion Urea Respiration Blood Pressure (CURB-65) severity score, the Rapid Emergency Medicine Score (REMS), and the Risk Stratification in the Emergency Department in Acutely Ill Older Patients (RISE UP) score had fair to good prediction of death among inpatients, while the quick Sepsis-related Organ Failure Assessment (qSOFA) score had poor to fair prediction. The certainty of evidence for these models was very low to low. For the outcome of clinical deterioration, the 4C Deterioration Score had fair prediction, the National Early Warning Score 2 (NEWS2) score poor to good, and the Modified Early Warning Score (MEWS) had poor prediction. The certainty of evidence for these three models was also very low to low. None of these models had been validated in the Philippine setting. Conclusion. The QCOVID, COPE, ABC2-SPH, 4C, CURB-65, REMS, RISE-UP models for prediction of mortality and the 4C Deterioration and NEWS2 models for prediction of clinical deterioration are potentially useful but need to be validated among patients with COVID-19 of varying severity in the Philippine setting.


2018 ◽  
Vol 7 (3) ◽  
pp. e000088 ◽  
Author(s):  
Muge Capan ◽  
Stephen Hoover ◽  
Kristen E Miller ◽  
Carmen Pal ◽  
Justin M Glasgow ◽  
...  

BackgroundIncreasing adoption of electronic health records (EHRs) with integrated alerting systems is a key initiative for improving patient safety. Considering the variety of dynamically changing clinical information, it remains a challenge to design EHR-driven alerting systems that notify the right providers for the right patient at the right time while managing alert burden. The objective of this study is to proactively develop and evaluate a systematic alert-generating approach as part of the implementation of an Early Warning Score (EWS) at the study hospitals.MethodsWe quantified the impact of an EWS-based clinical alert system on quantity and frequency of alerts using three different alert algorithms consisting of a set of criteria for triggering and muting alerts when certain criteria are satisfied. We used retrospectively collected EHRs data from December 2015 to July 2016 in three units at the study hospitals including general medical, acute care for the elderly and patients with heart failure.ResultsWe compared the alert-generating algorithms by opportunity of early recognition of clinical deterioration while proactively estimating alert burden at a unit and patient level. Results highlighted the dependency of the number and frequency of alerts generated on the care location severity and patient characteristics.ConclusionEWS-based alert algorithms have the potential to facilitate appropriate alert management prior to integration into clinical practice. By comparing different algorithms with regard to the alert frequency and potential early detection of physiological deterioration as key patient safety opportunities, findings from this study highlight the need for alert systems tailored to patient and care location needs, and inform alternative EWS-based alert deployment strategies to enhance patient safety.


Author(s):  
Carol J Parker ◽  
Mathew J Reeves

Background: Stroke quality metrics play an increasingly important role in quality improvement efforts and policies, but the relationship between quality metrics and patient-orientated outcomes are not well described. We conducted a systematic review of observational hospital-based studies examining this relationship. Methods: We searched MEDLINE and EMBASE for studies published before December 31, 2010 that examined the relationship between 2 or more stroke quality metrics and patient-oriented outcomes in acute stroke admissions. Outcomes included mortality, length of stay, discharge to home, functional status, and stroke recurrence. Results: A total of 470 hits were identified. After screening the titles and abstracts, 27 studies underwent full review, and 14 were deemed eligible. Given the variation in study characteristics, quality metrics, and outcomes utilized, it was not possible to generate summary estimates describing the relationship between quality metric compliance and patient-oriented outcomes. Evidence of a positive relationship between quality metrics and improved patient outcomes was limited by the lack of high quality studies. Four of the 14 studies found a statistically significant relationship between increased compliance with acute care quality metrics and improved patient-oriented outcomes. Two studies failed to find an association between acute care measures and improved outcomes, but did find statistically significant positive relationships between compliance with post-acute rehabilitation measures and improved patient outcomes. Five other studies reported mixed findings, while the remaining three found no relationships. Conclusions: We found a limited evidence-base addressing the impact of compliance on stroke quality metrics and patient-oriented outcomes. Generation of data clarifying the relationship between compliance with stroke quality metrics and stroke-related outcomes should be prioritized so that the current investments undertaken to improve stroke care can be sustained.


2019 ◽  
Vol 129 ◽  
pp. 275-284 ◽  
Author(s):  
Mirela Prgomet ◽  
Julie Li ◽  
Ling Li ◽  
Andrew Georgiou ◽  
Johanna I. Westbrook

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