NEWS Scoring System: Use in Hematologic Malignancies and Cellular Therapeutics Patient Populations

Suhr, Kelsey; Steen, Cyndy; Albrecht-Thompson, Robin; Williams, Jennifer

doi:10.1188/20.cjon.e21-e27

Cited by 3 publications

(5 citation statements)

References 7 publications

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“…Tindakan pemberian skor dan pembacaan skor pada EWS digunakan sebagai bagian dari keputusan klinis yang berfungsi sebagai indikator ketajaman pada frekuensi pemantauan dan alokasi sumber daya. Eskalasi numerik pada EWS berperan disaat pengambilan intervensi dalam pengaktifkan panggilan MET segera jika diperlukan seperti pada skor EWS > 7dan memiliki setidaknya satu kriteria tambahan (Suhr et al, 2020).…”

Section: Pemantauan Disertai Manajemen Tindakanunclassified

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Implementasi Early Warning System (Ews) dalam Mendeteksi Perburukan Akut pada Pasien Dewasa di Ruang Rawat Inap Rumah Sakit

Astuti,

Trisyani,

Mirwanti

2023

JOTING

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The purpose of this scoping review is to identify how the application of EWS to detecting acute deterioration in adult patients in general ward hospital. The method used was a scoping review and the literature has been obtained from searches derived from four databases originating from PubMed, Scopus, Sage, and CINAHL. The results showed that the implementation of EWS consisted of 6 components (vital sign recording, EWS scoring and reading, EWS protocol, clinical response based on escalation protocol, information assistance process using bundle communication (SBAR), medical emergency team (MET) system activation). Seven main of vital sign have to measured are respiratory rate, oxygen saturation, oxygen supplementation, temperature, pulse, systolic blood pressure, and level of consciousness. Persistence and additional commitment since 2009 were identified as significantly increasing benefits during the implementation of EWS instruments to improve patient outcomes. This success was obtained from experience that can increase the knowledge and competence of nurses. Changes in the risk of the EWS score can be read by nurses as an indication of clinical deterioration that requires stabilization interventions. Innovations have also been carried out since 2013 which have been successfully implemented in various countries, especially in 2019 and 2021 which are called EWS electronic. Based on this study, EWS proved to be accurate in detecting deterioration in patients. Therefore, to improve the implementation of EWS nurses must have good knowledge, because in implementing EWS requires critical thinking, and the ability to analyze numerical score classifications as a basis for decision making. Keywords: Early Warning System, EWS, Nurse Implementation, Patient deterioration.

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Section: Pemantauan Disertai Manajemen Tindakanunclassified

“…Penggunaan SBAR memfasilitasi percakapan interprofesional dan menghindarkan kesalahan penerimaan informasi. Penggunaan SBAR memudahkan perawat untuk memulai percakapan tentang agresivitas penatalaksanaan dan pengobatan pada pasien (Suhr et al, 2020).…”

Section: Pemantauan Disertai Manajemen Tindakanunclassified

Implementasi Early Warning System (Ews) dalam Mendeteksi Perburukan Akut pada Pasien Dewasa di Ruang Rawat Inap Rumah Sakit

Astuti,

Trisyani,

Mirwanti

2023

JOTING

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“…As such, the authors did not measure changes in clinical outcomes as a result of implementing MEWS in the emergency department. 26 Lind et al 23 Lee et al 27 Cooksley et al 16 Young et al 17 Aygun et al 28 Although several studies mentioned above have used variations of MEWS to predict morbidity and mortality in the oncology population, Suhr et al 29 studied the effect of the NEWS scoring system in the hematologic malignancy and cellular therapeutics population at the University of Kansas Health Systems, including patients admitted for allogenic or autologous transplantation, other treatment (eg, chemotherapy), or post-transplantation readmission. In the preimplementation period, the authors performed a retrospective chart review on patients who had RRT activation using the pre-existing SIRS criteria.…”

Section: Experience With Early Warning Scores In Oncologymentioning

confidence: 99%

“…The studies that have assessed the effect of these tools in inpatients with malignancy have used various scoring systems with different parameters and have evaluated different outcomes with no clear standardization. 16,17,23,[26][27][28][29] Furthermore, the studies only looked at absolute cutoff values for their scoring systems without assessing the predictive ability of dynamic changes in contiguous scores over time. The majority of studies were limited by their small sample size, single-institution focus, and retrospective nature.…”

Section: Implementation Considerations For Inpatient Oncology Settingsmentioning

confidence: 99%

Early Warning Scores and Their Application in the Inpatient Oncology Settings

Nagarajah

Krzyzanowska

Murphy

2022

JCO Oncology Practice

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Early Warning Score (EWS) systems are tools that use alterations in vital signs to rapidly identify clinically deteriorating patients and escalate care accordingly. Since its conception in 1997, EWSs have been used in several settings, including the general inpatient ward, intensive care units, and the emergency department. Several iterations of EWSs have been developed with varying levels of sensitivity and specificity for use in different populations. There are multiple strengths of these tools, including their simplicity and their ability to standardize communication and to reduce inappropriate or delayed referrals to the intensive care unit. Although early identification of deteriorating patients in the oncology population is vital to reduce morbidity and mortality and to improve long-term prognosis, the application in the oncology setting has been limited. Patients with an oncological diagnosis are usually older, medically complex, and can have increased susceptibility to infections, end-organ damage, and death. A search using PubMed and Scopus was conducted for articles published between January 1997 and November 2020 pertaining to EWSs in the oncology setting. Seven relevant studies were identified and analyzed. The most commonly used EWS in this setting was the Modified Early Warning Score. Of the seven studies, only two included prospective validation of the EWS in the oncology population and the other five only included a retrospective assessment of the data. The majority of studies were limited by their small sample size, single-institution analysis, and retrospective nature. Future studies should assess dynamic changes in scores over time and evaluate balance measures to identify use of health care resources.

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“…Vital sign-based early warning scores (EWSs) were developed and adopted for screening patients at high risk of clinical deterioration [10,11,18,23]. However, vital sign-based EWSs, already widely used in many hospitals for activating the RRS, were found to have poor discriminatory power for identifying cancer patients at risk of deterioration [24,25]. Additionally, some studies have expressed concerns about applying conventional scoring systems to cancer patients, as these track and trigger scores may not reflect the diverse patterns and rapid deterioration of these patients.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Early Warning Score for Predicting Clinical Deterioration in General Ward Cancer Patients

Ko,

Kim,

Jeon

et al. 2023

Cancers

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Background: Cancer patients who are admitted to hospitals are at high risk of short-term deterioration due to treatment-related or cancer-specific complications. A rapid response system (RRS) is initiated when patients who are deteriorating or at risk of deteriorating are identified. This study was conducted to develop a deep learning-based early warning score (EWS) for cancer patients (Can-EWS) using delta values in vital signs. Methods: A retrospective cohort study was conducted on all oncology patients who were admitted to the general ward between 2016 and 2020. The data were divided into a training set (January 2016–December 2019) and a held-out test set (January 2020–December 2020). The primary outcome was clinical deterioration, defined as the composite of in-hospital cardiac arrest (IHCA) and unexpected intensive care unit (ICU) transfer. Results: During the study period, 19,739 cancer patients were admitted to the general wards and eligible for this study. Clinical deterioration occurred in 894 cases. IHCA and unexpected ICU transfer prevalence was 1.77 per 1000 admissions and 43.45 per 1000 admissions, respectively. We developed two models: Can-EWS V1, which used input vectors of the original five input variables, and Can-EWS V2, which used input vectors of 10 variables (including an additional five delta variables). The cross-validation performance of the clinical deterioration for Can-EWS V2 (AUROC, 0.946; 95% confidence interval [CI], 0.943–0.948) was higher than that for MEWS of 5 (AUROC, 0.589; 95% CI, 0.587–0.560; p < 0.001) and Can-EWS V1 (AUROC, 0.927; 95% CI, 0.924–0.931). As a virtual prognostic study, additional validation was performed on held-out test data. The AUROC and 95% CI were 0.588 (95% CI, 0.588–0.589), 0.890 (95% CI, 0.888–0.891), and 0.898 (95% CI, 0.897–0.899), for MEWS of 5, Can-EWS V1, and the deployed model Can-EWS V2, respectively. Can-EWS V2 outperformed other approaches for specificities, positive predictive values, negative predictive values, and the number of false alarms per day at the same sensitivity level on the held-out test data. Conclusions: We have developed and validated a deep learning-based EWS for cancer patients using the original values and differences between consecutive measurements of basic vital signs. The Can-EWS has acceptable discriminatory power and sensitivity, with extremely decreased false alarms compared with MEWS.

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NEWS Scoring System: Use in Hematologic Malignancies and Cellular Therapeutics Patient Populations

Cited by 3 publications

References 7 publications

Implementasi Early Warning System (Ews) dalam Mendeteksi Perburukan Akut pada Pasien Dewasa di Ruang Rawat Inap Rumah Sakit

Implementasi Early Warning System (Ews) dalam Mendeteksi Perburukan Akut pada Pasien Dewasa di Ruang Rawat Inap Rumah Sakit

Early Warning Scores and Their Application in the Inpatient Oncology Settings

Deep Learning-Based Early Warning Score for Predicting Clinical Deterioration in General Ward Cancer Patients

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