A review of early warning systems for prompt detection of patients at risk for clinical decline

Early Warning Scores (EWS) are a composite evaluation of a patient's basic physiology, changes of which are the first indicators of clinical decline and are used to prompt further patient assessment and when indicated intervention. These are sometimes referred to as "track and triggers systems" with tracking meant to denote periodic observation of physiology and trigger being a predetermined response criteria. This review article examines the most widely used EWS, with special attention paid to those used in military and trauma populations.The earliest EWS is the Modified Early Earning Score (MEWS). In MEWS, points are allocated to vital signs based on their degree of abnormality, and summed to yield an aggregate score. A score above a threshold would elicit a clinical response such as a rapid response team. Modified Early Earning Score was subsequently followed up with the United Kingdom's National Early Warning Score, the electronic cardiac arrest triage score, and the 10 Signs of Vitality score, among others.Severity of illness indicators have been in military and civilian trauma populations, such as the Revised Trauma Score, Injury Severity Score, and Trauma and Injury Severity. The sequential organ failure assessment score and its attenuated version quick sequential organ failure assessment were developed to aggressively identify patients near septic shock.Effective EWS have certain characteristics. First, they should accurately capture vital signs information. Second, almost all data should be derived electronically rather than manually. Third, the measurements should take into consideration multiple organ systems. Finally, information that goes into an EWS must be captured in a timely manner. Future trends include the use of machine learning to detect subtle changes in physiology and the inclusion of data from biomarkers. As EWS improve, they will be more broadly used in both military and civilian environments. LEVEL OF EVIDENCE: Review article, level I.

TIGER Team: Rapid Response at the University of Missouri

By the end of the 20^th century, health care organizations worldwide were recognizing the benefits of a quick response when patients were experiencing a clinical decline and the difficulty in achieving that goal. The University of Missouri STAT Nurse program, developed in 1989, was an early innovation to deliver the "right care" at the "right time" every time. Over the years, the STAT Nurse program evolved and became the core component of a Rapid Response System. Today Rapid Response at University of Missouri Health Care is called the Targeted Interventional Group Emergency Response Team, also known as the TIGER Team after the much beloved University mascot.

Analysis of the early warning score to detect critical or high-risk patients in the prehospital setting

The early warning score can help to prevent, recognize and act at the first signs of clinical and physiological deterioration. The objective of this study is to evaluate different scales for use in the prehospital setting and to select the most relevant one by applicability and capacity to predict mortality in the first 48 h. A prospective longitudinal observational study was conducted in patients over 18 years of age who were treated by the advanced life support unit and transferred to the emergency department between April and July 2018. We analyzed demographic variables as well as the physiological parameters and clinical observations necessary to complement the EWS. Subsequently, each patient was followed up, considering their final diagnosis and mortality data. A total of 349 patients were included in our study. Early mortality before the first 48 h affected 27 patients (7.7%). The scale with the best capacity to predict early mortality was the National Early Warning Score 2, with an area under the curve of 0.896 (95% CI 0.82-0.97). The score with the lowest global classification error was 10 points with sensitivity of 81.5% (95% CI 62.7-92.1) and specificity of 88.5% (95% CI 84.5-91.6). The early warning score studied (except modified early warning score) shows no statistically significant differences between them; however, the National Early Warning Score 2 is the most used score internationally, validated at the prehospital scope and with a wide scientific literature that supports its use. The Prehospital Emergency Medical Services should include this scale among their operative elements to complement the structured and objective evaluation of the critical patient.

Predictive value of the prehospital NEWS2-L —National Early Warning Score 2 Lactate— for detecting early death after an emergency

OBJECTIVES

To evaluate the ability of the prehospital National Early Warning Score 2 Lactate (preNEWS2-L) to predict early mortality, defined as death within 48 hours of the index event. We also explored the predictive capacity of the score for 7- and 30-day all-cause mortality.

MATERIAL AND METHODS

Prospective, observational longitudinal study in patients attended by ambulance responders and transferred to the emergency departments of reference hospitals. We collected demographic, physiologic, clinical, and analytical data and the main diagnosis. The main outcome measure was all-cause mortality.

RESULTS

s. A total of 707 patients were included. Thirty-seven patients (5.2%) died within 48 hours of the index event. The area under the receiver operating characteristic curve (AUC) for the preNEWS2-L score's prediction of early death was 0.91 (95% CI, 0.83-0.96). The AUCs for death within 7 and 30 days were 0.86 (95% CI, 0.79-0.92) and 0.82 (95% CI, 0.76-0.87), respectively, showing that the score's ability to predict death decreases by almost 10% between 48 hours and 30 days.

CONCLUSION

The preNEWS2-L is a useful prognostic tool that can be assessed quickly and easily in prehospital settings.

The effect of fractional inspired oxygen concentration on early warning score performance: A database analysis

OBJECTIVES

To calculate fractional inspired oxygen concentration (FiO2) thresholds in ward patients and add these to the National Early Warning Score (NEWS). To evaluate the performance of NEWS-FiO2 against NEWS when predicting in-hospital death and unplanned intensive care unit (ICU) admission.

METHODS

A multi-centre, retrospective, observational cohort study was carried out in five hospitals from two UK NHS Trusts. Adult admissions with at least one complete set of vital sign observations recorded electronically were eligible. The primary outcome measure was an 'adverse event' which comprised either in-hospital death or unplanned ICU admission. Discrimination was assessed using the Area Under the Receiver Operating Characteristic curve (AUROC).

RESULTS

A cohort of 83,304 patients from a total of 271,363 adult admissions were prescribed oxygen. In this cohort, NEWS-FiO2 (AUROC 0.823, 95% CI 0.819-0.824) outperformed NEWS (AUORC 0.811, 95% CI 0.809-0.814) when predicting in-hospital death or unplanned ICU admission within 24 h of a complete set of vital sign observations.

CONCLUSIONS

NEWS-FiO2 generates a performance gain over NEWS when studied in ward patients requiring oxygen. This warrants further study, particularly in patients with respiratory disorders.

Early warning systems in obstetrics: A systematic literature review

Introduction

Several versions of Early Warning Systems (EWS) are used in obstetrics to detect and treat early clinical deterioration to avert morbidity and mortality. EWS can potentially be useful to improve the quality of care and reduce the risk of maternal mortality in resource-limited settings. We conducted a systematic literature review of published obstetric early warning systems, define their predictive accuracy for morbidity and mortality, and their effectiveness in triggering corrective actions and improving health outcomes.

Methods

We systematically searched for primary research articles on obstetric EWS published in peer-reviewed journals between January 1997 and March 2018 in Medline, CINAHL, SCOPUS, Science Direct, and Science Citation Index. We also searched reference lists of relevant articles and websites of professional societies. We included studies that assessed the predictive accuracy of EWS to detect clinical deterioration, or/and their effectiveness in improving clinical outcomes in obstetric inpatients. We excluded studies with a paediatric or non-obstetric adult population. Cross-sectional and qualitative studies were also excluded. We performed a narrative synthesis since the outcomes reported were heterogeneous.

Results

A total of 381 papers were identified, 17 of which met the inclusion criteria. Eleven of the included studies evaluated the predictive accuracy of EWS for obstetric morbidity and mortality, 5 studies assessed the effectiveness of EWS in improving clinical outcomes, while one study addressed both. Sixteen published EWS versions were reviewed, 14 of which included five basic clinical observations (pulse rate, respiratory rate, temperature, blood pressure, and consciousness level). The obstetric EWS identified had very high median (inter-quartile range) sensitivity—89% (72% to 97%) and specificity—85% (67% to 98%) but low median (inter-quartile range) positive predictive values—41% (25% to 74%) for predicting morbidity or ICU admission. Obstetric EWS had a very high accuracy in predicting death (AUROC >0.80) among critically ill obstetric patients. Obstetric EWS improves the frequency of routine vital sign observation, reduces the interval between the recording of specifically defined abnormal clinical observations and corrective clinical actions, and can potentially reduce the severity of obstetric morbidity.

Conclusion

Obstetric EWS are effective in predicting severe morbidity (in general obstetric population) and mortality (in critically ill obstetric patients). EWS can contribute to improved quality of care, prevent progressive obstetric morbidity and improve health outcomes. There is limited evidence of the effectiveness of EWS in reducing maternal death across all settings. Clinical parameters in most obstetric EWS versions are routinely collected in resource-limited settings, therefore implementing EWS may be feasible in such settings.

Validity and effectiveness of paediatric early warning systems and track and trigger tools for identifying and reducing clinical deterioration in hospitalised children: a systematic review

OBJECTIVE

To assess (1) how well validated existing paediatric track and trigger tools (PTTT) are for predicting adverse outcomes in hospitalised children, and (2) how effective broader paediatric early warning systems are at reducing adverse outcomes in hospitalised children.

DESIGN

Systematic review.

DATA SOURCES

British Nursing Index, Cumulative Index of Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effectiveness, EMBASE, Health Management Information Centre, Medline, Medline in Process, Scopus and Web of Knowledge searched through May 2018.

ELIGIBILITY CRITERIA

We included (1) papers reporting on the development or validation of a PTTT or (2) the implementation of a broader early warning system in paediatric units (age 0-18 years), where adverse outcome metrics were reported. Several study designs were considered.

DATA EXTRACTION AND SYNTHESIS

Data extraction was conducted by two independent reviewers using template forms. Studies were quality assessed using a modified Downs and Black rating scale.

RESULTS

36 validation studies and 30 effectiveness studies were included, with 27 unique PTTT identified. Validation studies were largely retrospective case-control studies or chart reviews, while effectiveness studies were predominantly uncontrolled before-after studies. Metrics of adverse outcomes varied considerably. Some PTTT demonstrated good diagnostic accuracy in retrospective case-control studies (primarily for predicting paediatric intensive care unit transfers), but positive predictive value was consistently low, suggesting potential for alarm fatigue. A small number of effectiveness studies reported significant decreases in mortality, arrests or code calls, but were limited by methodological concerns. Overall, there was limited evidence of paediatric early warning system interventions leading to reductions in deterioration.

CONCLUSION

There are several fundamental methodological limitations in the PTTT literature, and the predominance of single-site studies carried out in specialist centres greatly limits generalisability. With limited evidence of effectiveness, calls to make PTTT mandatory across all paediatric units are not supported by the evidence base.

PROSPERO REGISTRATION NUMBER

CRD42015015326.

Use of the National Early Warning Score (NEWS) to Identify Acutely Deteriorating Patients with Sepsis in Acute Medical Ward

INTRODUCTION

The National Early Warning Score (NEWS) is well established in acute medical units to identify acutely deteriorating patients and is shown to have good prognostic value. NEWS, however, has only been used in the Emergency Department as a triage tool. We aimed to evaluate the validity of NEWS in Acute Medical Ward (AMW) that treats predominantly acute infection-related conditions to the Internal Medicine service.

MATERIALS AND METHODS

We undertook a retrospective cohort study and analysed NEWS records of all patients admitted to AMW at Singapore General Hospital between 1 August 2015 and 30 July 2017. The outcome was defined as deterioration that required transfer to Intermediate Care Area (ICA), Intensive Care Unit (ICU) or death within 24 hours of a vital signs observation set.

RESULTS

A total of 298,743 vital signs observation sets were obtained from 11,300 patients. Area under receiver operating characteristic curve for any of the 3 outcomes (transfer to ICA, ICU or death) over a 24-hour period was 0.896 (95% confidence interval, 0.890-0.901). Event rate was noted to be high above 0.250 when the score was >9. In the medium-risk group (score of 5 or 6), event rate was <0.125.

CONCLUSION

NEWS accurately triages patients according to the likelihood of adverse outcomes in infection-related acute medical settings.

Automated early detection of obstetric complications: theoretic and methodologic considerations

Compared with adults who are admitted to general medical-surgical wards, women who are admitted to labor and delivery services are at much lower risk of experiencing unexpected critical illness. Nonetheless, critical illness and other complications that put either the mother or fetus at risk do occur. One potential approach to prevention is to use automated early warning systems, such as those used for nonpregnant adults. Predictive models that use data extracted in real time from electronic records constitute the cornerstone of such systems. This article addresses several issues that are involved in the development of such predictive models: specification of temporal characteristics, choice of denominator, selection of outcomes for model calibration, potential uses of existing adult severity of illness scores, approaches to data processing, statistical considerations, validation, and options for instantiation. These have not been addressed explicitly in the obstetrics literature, which has focused on the use of manually assigned scores. In addition, this article provides some results from work in progress to develop 2 obstetric predictive models with the use of data from 262,071 women who were admitted to a labor and delivery service at 15 Kaiser Permanente Northern California hospitals between 2010 and 2017.

Statistical Modeling and Aggregate-Weighted Scoring Systems in Prediction of Mortality and ICU Transfer: A Systematic Review

BACKGROUND

The clinical deterioration of patientsin general hospital wards is an important safety issue. Aggregate-weighted early warning systems (EWSs) may not detect risk until patients present with acute decline.

PURPOSE

We aimed to compare the prognostic test accuracy and clinical workloads generated by EWSs using statistical modeling (multivariable regression or machine learning) versus aggregate-weighted tools.

DATA SOURCES

We searched PubMed and CINAHL using terms that described clinical deterioration and use of an advanced EWS.

STUDY SELECTION

The outcome was clinical deterioration (intensive care unit transfer or death) of adult patients on general hospital wards. We included studies published from January 1, 2012 to September 15, 2018.

DATA EXTRACTION

Following 2015 PRIMSA systematic review protocol guidelines; 2015 TRIPOD criteria for predictive model evaluation; and the Cochrane Collaboration guidelines, we reported model performance, adjusted positive predictive value (PPV), and conducted simulations of workup-to-detection ratios.

DATA SYNTHESIS

Of 285 articles, six studies reported the model performance of advanced EWSs, and five were of high quality. All EWSs using statistical modeling identified at-risk patients with greater precision than aggregate-weighted EWSs (mean AUC 0.80 vs 0.73). EWSs using statistical modeling generated 4.9 alerts to find one true positive case versus 7.1 alerts in aggregate-weighted EWSs; a nearly 50% relative workload increase for aggregate-weighted EWSs.

CONCLUSIONS

Compared with aggregate-weighted tools, EWSs using statistical modeling consistently demonstrated superior prognostic performance and generated less workload to identify and treat one true positive case. A standardized approach to reporting EWS model performance is needed, including outcome definitions, pretest probability, observed and adjusted PPV, and workup-to-detection ratio.

The Association Between Fever and Subsequent Deterioration Among Hospitalized Children With Elevated PEWS

OBJECTIVES

To evaluate the association between fever and subsequent deterioration among patients with Pediatric Early Warning Score (PEWS) elevations to ≥4 to inform improvements to care escalation processes at our institution.

METHODS

We performed a cohort study of hospitalized children at a single quaternary children's hospital with PEWS elevations to ≥4 between January 1, 2014 and March 31, 2014. Bivariable analysis was used to compare characteristics between patients with and without unplanned ICU transfers and critical deterioration events (CDEs) (ie, unplanned ICU transfers with life-sustaining interventions initiated in the first 12 ICU hours). A multivariable Poisson regression was used to assess the relative risk of unplanned ICU transfers and CDEs.

RESULTS

The study population included 220 PEWS elevations from 176 unique patients. Of those, 33% had fever (n = 73), 40% experienced an unplanned ICU transfer (n = 88), and 19% experienced CDEs (n = 42). Bivariable analysis revealed that febrile patients were less likely to experience an unplanned ICU transfer than those without fever. The same association was found in multivariable analysis with only marginal significance (adjusted relative risk 0.68; 95% confidence interval 0.45-1.01; P = .058). There was no difference in the CDE risk for febrile versus afebrile patients (adjusted relative risk 0.79; 95% confidence interval 0.43-1.44; P = .44).

CONCLUSIONS

At our institution, patients with an elevated PEWS appeared less likely to experience an unplanned ICU transfer if they were febrile. We were underpowered to evaluate the effect on CDEs. These findings contributed to our recognition that (1) PEWS may not include all relevant clinical factors used for clinical decision-making regarding care escalation and (2) further study is needed in this area.

Beyond Reporting Early Warning Score Sensitivity: The Temporal Relationship and Clinical Relevance of "True Positive" Alerts that Precede Critical Deterioration

BACKGROUND

Clinical deterioration is difficult to detect in hospitalized children. The pediatric Rothman Index (pRI) is an early warning score that incorporates vital signs, laboratory studies, and nursing assessments to generate deterioration alerts.

OBJECTIVES

(1) Evaluate the timing of pRI alerts and clinicians recognizing deterioration or escalating care prior to critical deterioration events (CDEs) and (2) determine whether the parameters triggering alerts were clinically related to deterioration.

DESIGN

CDEs are unplanned transfers to the intensive care unit with noninvasive ventilation, tracheal intubation, and/or vasopressor infusion in the 12 hours after transfer. Using one year of data from a large freestanding children's hospital without the pRI, we analyzed CDEs that would have been preceded by pRI alerts. We (1) compared the timing of pRI alerts to time-stamped notes describing changes in patient status and orders reflecting escalations of care and (2) identified score component(s) that caused alerts to trigger and determined whether these were clinically related to CDE etiology.

RESULTS

Fifty CDEs would have triggered pRI alertsif the pRI had been in use (sensitivity 68%). In 90% of CDEs, the first clinician note reflecting change in patient status and/or the first order reflecting escalation of care preceded the first pRI alert. All of the vital sign and laboratory components of the pRI and 51% of the nursing components were clinically related to the etiology of the CDE.

CONCLUSIONS

Evidence that clinicians were awareof deterioration preceded pRI alerts in most CDEs that generated alerts in the preceding 24 hours.

The inclusion of delirium in version 2 of the National Early Warning Score will substantially increase the alerts for escalating levels of care: findings from a retrospective database study of emergency medical admissions in two hospitals

BACKGROUND

The National Early Warning Score (NEWS) is being replaced with NEWS2 which adds 3 points for new confusion or delirium. We estimated the impact of adding delirium on the number of medium/high level alerts that are triggers to escalate care.

METHODS

Analysis of emergency medical admissions in two acute hospitals (York Hospital (YH) and Northern Lincolnshire and Goole NHS Foundation Trust hospitals (NH)) in England. Twenty per cent were randomly assigned to have delirium.

RESULTS

The number of emergency admissions (YH: 35584; NH: 35795), mortality (YH: 5.7%; NH: 5.5%), index NEWS (YH: 2.5; NH: 2.1) and numbers of NEWS recorded (YH: 879193; NH: 884072) were similar in each hospital. The mean number of patients with medium level alerts per day increased from 55.3 (NEWS) to 69.5 (NEWS2), a 25.7% increase in YH and 64.1 (NEWS) to 77.4 (NEWS2), a 20.7% increase in NH. The mean number of patients with high level alerts per day increased from 27.3 (NEWS) to 34.4 (NEWS2), a 26.0% increase in YH and 29.9 (NEWS) to 37.7 (NEWS2), a 26.1% increase in NH.

CONCLUSIONS

The addition of delirium in NEWS2 will have a substantial increase in medium and high level alerts in hospitalised emergency medical patients. Rigorous evaluation of NEWS2 is required before widespread implementation because the extent to which staff can cope with this increase without adverse consequences remains unknown.

Combination of the National Early Warning Score (NEWS) and inflammatory biomarkers for early risk stratification in emergency department patients: results of a multinational, observational study

OBJECTIVES

The National Early Warning Score (NEWS) helps to estimate mortality risk in emergency department (ED) patients. This study aimed to investigate whether the prognostic value of the NEWS at ED admission could be further improved by adding inflammatory blood markers (ie, white cell count (WCC), procalcitonin (PCT) and midregional-proadrenomedullin (MR-proADM).

DESIGN

Secondary analysis of a multinational, observational study (TRIAGE study, March 2013-October 2014).

SETTING

Three tertiary care centres in France, Switzerland and the USA.

PARTICIPANTS

A total of 1303 adult medical patients with complete NEWS data seeking ED care were included in the final analysis. NEWS was calculated retrospectively based on admission data.

MAIN OUTCOME MEASURES

The primary outcome was all-cause 30-day mortality. Secondary outcome was intensive care unit (ICU) admission. We used multivariate regression analyses to investigate associations of NEWS and blood markers with outcomes and area under the receiver operating curve (AUC) as a measure of discrimination.

RESULTS

Of the 1303 included patients, 54 (4.1%) died within 30 days. The NEWS alone showed fair prognostic accuracy for all-cause 30-day mortality (AUC 0.73), with a multivariate adjusted OR of 1.26 (95% CI 1.13 to 1.40, p<0.001). The AUCs for the prediction of mortality using the inflammatory markers WCC, PCT and MR-proADM were 0.64, 0.71 and 0.78, respectively. Combining NEWS with all three blood markers or only with MR-proADM clearly improved discrimination with an AUC of 0.82 (p=0.002). Combining the three inflammatory markers with NEWS improved prediction of ICU admission (AUC 0.70vs0.65 when using NEWS alone, p=0.006).

CONCLUSION

NEWS is helpful in risk stratification of ED patients and can be further improved by the addition of inflammatory blood markers. Future studies should investigate whether risk stratification by NEWS in addition to biomarkers improve site-of-care decision in this patient population.

TRIAL REGISTRATION NUMBER

NCT01768494; Post-results.

The predictive value of triage early Warning Score (TEWS) on mortality of trauma patients presenting to the Emergency Department

INTRODUCTION

Posttraumatic injuries are among the most frequent reasons of admission to emergency room services (ERs). In the first assessment of the cases, ATLS protocols recommends use of triage decision scheme consisting of parametres of abnormal physiologic findings, anatomic injury site, pathogenic mechanism of injury, concomitant diseases and conditions, and activation of trauma teams in line with these criteria. The aim of this study is to evaluate TEWS(Triage Early Warning Score) as a marker for predicting mortality in trauma patients who presented to Emergency Services.

MATERIALS AND METHODS

381 trauma patients aged ≥ 18 years who admitted to the Emergency Service and met criteria of ATLS protocol were included in the study.TEWS values of the patients were calculated using patients'data included in the study forms. Impact level was scrutinized using multivariant logistic regression test. Level of statistical significance was accepted as p<0.05.

RESULTS

In the prediction of survival and ex patient rates; significant effectiveness of TEWS was observed [0.973 (0.944- 1)] (p<0.05). In the ROC analysis maximum TEWS AUC value was [0.930 (0.895-0.966)] with a cut-off value of 5 points. TEWS scores of 17.2% (66/381) of the patients who were discharged were above 5 points. These patients had undergone intubation (n= 21; 35%), tube thoracostomy (n= 16; 26.6%), transfusion of blood products (n= 29; 48.3%), and emergency surgery (n=16; 26.6%).

CONCLUSIONS

Triage Early Warning Score is effective in the prediction of emergency treatment, and prognosis in trauma patients hospitalized in the emergency services, and it may identify patients under risk. We think that Triage Early Warning Score together with ATLS protocol can be used as an easily applicable triage warning trauma score in trauma patients.

KEY WORDS

Mortality, Scoring systems, Trauma.

[Review of Early Warning Score in preventing sudden critical illness and death]

Early Warning Score (EWS) are used extensively to identify patients at risk of deterioration during hospital admission. The validation of EWS has primarily focused on investigating predictive validity, i.e. the association between EWS and severe adverse events. Few studies have tested, whether EWS work in the clinical setting, and if it prevents severe adverse events from occurring. Many of these studies have methodological limitations, and their clinical relevance could be questioned. Currently, there is limited evidence to support, that the implementation of EWS reduces the occurrence of severe adverse events.

Microsimulation Model Using Christiana Care Early Warning System (CEWS) to Evaluate Physiological Deterioration

While physiological warning signs prior to deterioration events during hospitalization have been widely studied, evaluating clinical interventions, such as rapid response team (RRT) activations, based on scoring systems remains an understudied area. Simulation of physiological deterioration patterns represented by scoring systems can facilitate testing different RRT policies without disturbing care processes. Christiana Care Early Warning System (CEWS) is a scoring system developed at the study hospital to detect the physiological warning signs and inform RRT activations. The objective of this study is to evaluate CEWS-triggered RRT policies based on patient demographics and policy structures. Using retrospective data derived from a subset of electronic health records between December 2015 and December 2016 (6000 patients), we developed a microsimulation model with integrated regression analysis to compare RRT policies on subpopulations defined by age, gender, and comorbidities to find score thresholds that result in the lowest percent of time spent above critical CEWS values. Policies that rely on average scores were more sensitive to threshold changes compared to policies that rely on current value and change in the CEWS. Policy using score threshold 10 provided the lowest percentage of time under the critical condition for majority of subpopulations. The proposed model is a novel framework to simulate individual deterioration patterns and systematically evaluate RRT policies based on their impact on health conditions. Our work highlights the importance of integration of data-driven models into personalized care and represents a significant opportunity to inform biomedical and health informatics research on designing and evaluating EWS-based clinical interventions.