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Aims and Objectives: To evaluate whether the scale used for assessment of hospital ward patients could predict in-hospital and 30-day mortality amongst those with deviating vital signs; that is, that patients classified as medium or high risk would have increased risk of in-hospital and 30-day mortality compared to patients with low risk., Background: The National Early Warning Score (NEWS) is a widely adopted scale for assessing deviating vital signs. A clinical risk scale that comes with the NEWS divides the risk for critical illness into three risk categories, low, medium and high., Design: Retrospective analysis of vital sign data., Methods: Logistic regression models for age-adjusted in-hospital and 30-day mortality were used for analyses of 1,107 patients with deviating vital signs., Results: Patients classified as medium or high risk by NEWS experienced a 2.11 or 3.40 increase, respectively, in odds of in-hospital death (95% CI: 1.27-3.51, p = 0.004% and 95% CI: 1.90-6.01, p < 0.001) compared to low-risk patients. Moreover, those with NEWS medium or high risk were associated with a 1.98 or 3.19 increase, respectively, in odds of 30-day mortality (95% CI: 1.32-2.97, p = 0.001% and 95% CI: 1.97-5.18, p < 0.001)., Conclusion: The NEWS risk classification seems to be a reliable predictor of mortality on patients in hospital wards., Relevance to Clinical Practice: The NEWS risk classification offers a simple way to identify deteriorating patients and can aid the healthcare staff to prioritise amongst patients., (© 2018 John Wiley & Sons Ltd.)

Objectives: There are no established mortality risk equations specifically for emergency medical patients who are admitted to a general hospital ward. Such risk equations may be useful in supporting the clinical decision-making process. We aim to develop and externally validate a computer-aided risk of mortality (CARM) score by combining the first electronically recorded vital signs and blood test results for emergency medical admissions., Design: Logistic regression model development and external validation study., Setting: Two acute hospitals (Northern Lincolnshire and Goole NHS Foundation Trust Hospital (NH)-model development data; York Hospital (YH)-external validation data)., Participants: Adult (aged ≥16 years) medical admissions discharged over a 24-month period with electronic National Early Warning Score(s) and blood test results recorded on admission., Results: The risk of in-hospital mortality following emergency medical admission was 5.7% (NH: 1766/30 996) and 6.5% (YH: 1703/26 247). The C-statistic for the CARM score in NH was 0.87 (95% CI 0.86 to 0.88) and was similar in an external hospital setting YH (0.86, 95% CI 0.85 to 0.87) and the calibration slope included 1 (0.97, 95% CI 0.94 to 1.00)., Conclusions: We have developed a novel, externally validated CARM score with good performance characteristics for estimating the risk of in-hospital mortality following an emergency medical admission using the patient's first, electronically recorded, vital signs and blood test results. Since the CARM score places no additional data collection burden on clinicians and is readily automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: We investigated the national early warning scores (NEWSs) and related outcomes of patients in a tertiary referral center's multidisciplinary emergency department (ED). Patients were further categorized into three groups: triaged directly to intensive care unit (EDICU), triaged to general ward with later ICU admission (EDwardICU) and triaged to general ward (EDward). NEWSs and subsequent outcomes among these sub groups were compared., Methods: We conducted a prospective one-month cohort study in Tampere University Hospital's ED, Finland. ED-NEWSs were obtained for all adult patients without treatment limitations, and control (ward) NEWSs were further obtained for the EDwardICU and EDward patients., Results: Cohort consisted of 1,354 patients with a median ED-NEWS of 2, and higher ED-NEWS was associated with in-hospital mortality (OR 1.26, 95% CI 1.11-1.42; AUROC 0.75, 0.64‒0.86, p < 0.001) and 30-day mortality (OR 1.27, 1.17-1.39; AUROC 0.78, 0.71‒0.84, p < 0.001) irrespective of age and comorbidity. There were 64 patients in EDICU group, 12 patients in EDwardICU group and 1,278 patients in EDward group with median ED-NEWSs of 7, 3 and 2 (p < 0.001), respectively. After the first 24 h in wards, median NEWSs of the EDwardICU patients had substantially increased as compared with EDward patients (6 vs. 2, p < 0.001). There were no statistical differences in last NEWS before ICU admission between the EDICU and EDwardICU patients (7 vs. 8, p = 0.534), or in ICU severity-of-illness scores or patient outcomes., Conclusions: ED-NEWS is independently associated with in-hospital and 30-day mortality with acceptable discrimination capability. Direct and late ICU admissions occurred with comparable NEWSs at admission., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The second article on the use of track and trigger scoring (TTS) and National Early Warning Scoring Systems (NEWS 1 and 2) discusses how their use in relation to some patients can be too sensitive and in the case of others it merely detects late deterioration. This raises concerns that TTS and NEWS focus on a single set of observations at one point in time. They, therefore, ignore the observational trends by failing to compare the latest readings against previous sets of vital signs. It is therefore important that nurses do not rely solely on these tools, but use them in conjunction with their physiological knowledge and clinical assessment to identify deteriorating patients, as well as those who do not require unnecessary escalation of care.

Introduction: The NEWS is a physiological score, which prescribes an appropriate response for the deteriorating patient in need of urgent medical care. However, it has been suggested that compliance with early warning scoring systems for identifying patient deterioration may vary out of hours. We aimed to (1) assess the scoring accuracy and the adequacy of the prescribed clinical responses to NEWS and (2) assess whether responses were affected by time of day, day of week and score severity., Methods: We performed a prospective observational study of 370 adult patients admitted to an acute medical ward in a London District General Hospital. Patient characteristics, NEW score, time of day, day of week and clinical response data were collected for the first 24h of admission. Patients with less than a 12h hospital stay were excluded. We analysed data with univariate and multivariate logistic regression., Results: In 70 patients (18.9%) the NEW score was calculated incorrectly. There was a worsening of the clinical response with increasing NEW score. An appropriate clinical response to the NEWS was observed in 274 patients (74.1%). Patients admitted on the weekend were more likely to receive an inadequate response, compared to patients admitted during the week (p<0.0001). After adjusting for confounders, increasing NEWS score remained significantly associated with an inadequate clinical response. Furthermore, our results demonstrate a small increase in inadequate NEWS responses at night, however this was not clinically or statistically significant., Conclusion: The high rate of incorrectly calculated NEW scores has implications for the prescribed actions. Clinical response to NEWS score triggers is significantly worse at weekends, highlighting an important patient safety concern., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

BACKGROUND: Population aging is a social problem that is being faced in most countries. OBJECTIVE: To apply the National Early Warning Score (NEWS) for an early warning on the vital signs and consciousness of elderly patients who are hospitalized in the gastrointestinal surgical department and to provide a reference for early detection of changes in illness severity in elderly patients by studying the correlation between NEWS value and changes in illness severity. METHODS: We enrolled 528 elderly patients who were hospitalized in the gastrointestinal surgical department of a tertiary grade A hospital in Guizhou Province between June 2020 and May 2021, to analyze how NEWS max value correlates with illness severity and obtain the optimal NEWS cutoff value for both potentially critically ill and critically ill elderly patients using the receiver operating characteristic (ROC) curve. RESULTS: There were statistically significant differences in NEWS values between elderly patients with various illness severities (P < 0.05). NEWS values correlated positively with illness severity (r = 0.605, P < 0.001). Based on the ROC curve, early warning trigger values for NEWS to identify potentially critically ill, critically ill and terminally ill elderly patients were 6, 7 and 8, respectively. The area under the curve (AUC) for potentially critically ill, critically ill and terminally ill elderly patients was 0.907, 0.921 and 0.939, respectively. NEWS performed better in detecting patient illness severity than Modified Early Warning Score (MEWS) in AUC, sensitivity, specificity, and Youden's index, with statistically significant differences (P < 0.05). CONCLUSION: An early warning on the vital signs and consciousness of hospitalized elderly patients using NEWS can facilitate advanced detection of changes in illness severity of elderly patients by medical staff and enable timely treatment, thus significantly lowering the risks of illness deterioration. [ABSTRACT FROM AUTHOR]

In 2012, the National Early Warning Score (NEWS) was introduced to standardise monitoring of vital signs and improve patient safety in acute hospitals. By 2017 around two-thirds of NHS hospitals were using NEWS and an updated version, NEWS2, was released. In 2019 all acute hospital trusts and ambulance services were required to use NEWS2. Now NEWS2 is being used increasingly in care homes and community settings. People living in care homes are often frail and have multiple healthcare conditions. NEWS was never designed to monitor the health of older people, but it has the potential to improve care by enabling staff to identify people who are becoming unwell and to provide care within care homes and the person's own home. However, if it is not introduced with care, it could lead to an increase in the number of people attending accident and emergency departments. This article examines the emerging evidence base and concludes that appropriate support and advanced care planning are of crucial importance. [ABSTRACT FROM AUTHOR]

Abstract Background The novel coronavirus SARS-19 produces ‘COVID-19’ in patients with symptoms. COVID-19 patients admitted to the hospital require early assessment and care including isolation. The National Early Warning Score (NEWS) and its updated version NEWS2 is a simple physiological scoring system used in hospitals, which may be useful in the early identification of COVID-19 patients. We investigate the performance of multiple enhanced NEWS2 models in predicting the risk of COVID-19. Methods Our cohort included unplanned adult medical admissions discharged over 3 months (11 March 2020 to 13 June 2020 ) from two hospitals (YH for model development; SH for external model validation). We used logistic regression to build multiple prediction models for the risk of COVID-19 using the first electronically recorded NEWS2 within ± 24 hours of admission. Model M0’ included NEWS2; model M1’ included NEWS2 + age + sex, and model M2’ extends model M1’ with subcomponents of NEWS2 (including diastolic blood pressure + oxygen flow rate + oxygen scale). Model performance was evaluated according to discrimination (c statistic), calibration (graphically), and clinical usefulness at NEWS2 ≥ 5. Results The prevalence of COVID-19 was higher in SH (11.0 %=277/2520) than YH (8.7 %=343/3924) with a higher first NEWS2 scores ( SH 3.2 vs YH 2.8) but similar in-hospital mortality (SH 8.4 % vs YH 8.2 %). The c-statistics for predicting the risk of COVID-19 for models M0’,M1’,M2’ in the development dataset were: M0’: 0.71 (95 %CI 0.68–0.74); M1’: 0.67 (95 %CI 0.64–0.70) and M2’: 0.78 (95 %CI 0.75–0.80)). For the validation datasets the c-statistics were: M0’ 0.65 (95 %CI 0.61–0.68); M1’: 0.67 (95 %CI 0.64–0.70) and M2’: 0.72 (95 %CI 0.69–0.75) ). The calibration slope was similar across all models but Model M2’ had the highest sensitivity (M0’ 44 % (95 %CI 38-50 %); M1’ 53 % (95 %CI 47-59 %) and M2’: 57 % (95 %CI 51-63 %)) and specificity (M0’ 75 % (95 %CI 73-77 %); M1’ 72 % (95 %CI 70-74 %) and M2’: 76 % (95 %CI 74-78 %)) for the validation dataset at NEWS2 ≥ 5. Conclusions Model M2’ appears to be reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions.

Background: The vital‐sign monitoring strategy of patients with acute aortic dissection in the emergency department is mainly based on traditional experience. This study attempts to explore the significance of the national early warning score (NEWS) in monitoring the condition of patients with acute aortic dissection during emergency observation and to provide evidence for emergency nurses in optimal and scientific monitoring of patients. Methods: The case–control method was used to continuously enrol patients with acute aortic dissection who had been in the emergency department; the STROBE checklist was used in this process. Based on patients' clinical deterioration, they were divided into two groups: clinical deterioration and non‐clinical deterioration. The NEWS at each time point was compared by independent‐samples t‐test, and the predictive power of NEWS was evaluated according to the area under the receiver operating characteristic curve. Results: A total of 290 patients with acute aortic dissection were included: 46 patients showed clinical deterioration and 244 did not. There were significant differences in the NEW scores of the two groups at admission time and at 12, 8, 4 and 0.5 h before clinical deterioration. The NEW scores of the clinical deterioration group showed an upward trend, while the non‐clinical deterioration group showed a relatively stable trend. The NEWS can be used to predict the occurrence of clinical deterioration earlier at 4 h before clinical deterioration. Simultaneously, the patient's respiration rate and SpO2 had better predictive performance than other vital signs. Conclusion: The NEWS can be used to triage patients with acute aortic dissection admitted to the emergency department. Continuous use of the NEWS for monitoring can play a vital role in early warning of clinical deterioration in patients with acute aortic dissection. In clinical care, attention should also be paid when patients with acute aortic dissection have abnormal respiration rate and SpO2. [ABSTRACT FROM AUTHOR]

Aim: To investigate whether trends in the NEWS values are associated with patient mortality in general ward patients. Methods: A one-year prospective observational study in three hospitals in Finland. All data on patients’ NEWS values during the first three days of general ward admissions were collected. The linear regression model was used to investigate the association of the NEWS trajectories with subsequent mortality. We used three outcome measures: 4–7-day, 4–14-day and 4–21-day mortality rates after the 0–3 days of initial hospitalization, respectively. Results: The study cohort consisted of 11,331 general ward patients. The non-survivors had higher initial NEWS score values in all outcome categories (all p

Aim: Early identification of patients at risk of serious adverse events (SAEs) is of vital importance, yet it remains a challenging task. We investigated the predictive power of National Early Warning Score (NEWS) 2, as compared to NEWS, among patients assessed by a Rapid response team (RRT). Methods: Prospective, observational cohort study on 898 consecutive patients assessed by the RRTs in 26 Swedish hospitals. For each patient, NEWS and NEWS 2 scores were uniformly calculated by the study team. The associations of NEWS and NEWS 2 scores with unanticipated admissions to Intensive care unit (ICU), mortality and in-hospital cardiac arrests (IHCA) within 24 h, and the composite of these three events were investigated using logistic regression. The predictive power of NEWS and NEWS 2 was assessed using the area under the receiver operating characteristic (AUROC) curves. Results: The prognostic accuracy of NEWS/NEWS 2 in predicting mortality was acceptable (AUROC 0.69/0.67). In discriminating the composite outcome and unanticipated ICU admission, both NEWS and NEWS 2 were relatively weak (AUROC 0.62/0.62 and AUROC 0.59/0.60 respectively); for IHCA the performance was poor. There were no differences between NEWS and NEWS 2 as to the predictive power. Conclusion: The prognostic accuracy of NEWS 2 to predict mortality within 24 h was acceptable. However, the prognostic accuracy of NEWS 2 to predict IHCA was poor. NEWS and NEWS 2 performed similar in predicting the risk of SAEs but their performances were not sufficient for use as a risk stratification tool in patients assessed by a RRT.

Background: The novel coronavirus SARS-19 produces 'COVID-19' in patients with symptoms. COVID-19 patients admitted to the hospital require early assessment and care including isolation. The National Early Warning Score (NEWS) and its updated version NEWS2 is a simple physiological scoring system used in hospitals, which may be useful in the early identification of COVID-19 patients. We investigate the performance of multiple enhanced NEWS2 models in predicting the risk of COVID-19.Methods: Our cohort included unplanned adult medical admissions discharged over 3 months (11 March 2020 to 13 June 2020 ) from two hospitals (YH for model development; SH for external model validation). We used logistic regression to build multiple prediction models for the risk of COVID-19 using the first electronically recorded NEWS2 within ± 24 hours of admission. Model M0' included NEWS2; model M1' included NEWS2 + age + sex, and model M2' extends model M1' with subcomponents of NEWS2 (including diastolic blood pressure + oxygen flow rate + oxygen scale). Model performance was evaluated according to discrimination (c statistic), calibration (graphically), and clinical usefulness at NEWS2 ≥ 5.Results: The prevalence of COVID-19 was higher in SH (11.0 %=277/2520) than YH (8.7 %=343/3924) with a higher first NEWS2 scores ( SH 3.2 vs YH 2.8) but similar in-hospital mortality (SH 8.4 % vs YH 8.2 %). The c-statistics for predicting the risk of COVID-19 for models M0',M1',M2' in the development dataset were: M0': 0.71 (95 %CI 0.68-0.74); M1': 0.67 (95 %CI 0.64-0.70) and M2': 0.78 (95 %CI 0.75-0.80)). For the validation datasets the c-statistics were: M0' 0.65 (95 %CI 0.61-0.68); M1': 0.67 (95 %CI 0.64-0.70) and M2': 0.72 (95 %CI 0.69-0.75) ). The calibration slope was similar across all models but Model M2' had the highest sensitivity (M0' 44 % (95 %CI 38-50 %); M1' 53 % (95 %CI 47-59 %) and M2': 57 % (95 %CI 51-63 %)) and specificity (M0' 75 % (95 %CI 73-77 %); M1' 72 % (95 %CI 70-74 %) and M2': 76 % (95 %CI 74-78 %)) for the validation dataset at NEWS2 ≥ 5.Conclusions: Model M2' appears to be reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions. [ABSTRACT FROM AUTHOR]

Aims: To explore Registered Nurses' experiences and perceptions with National Early Warning Score and Individual Early Warning Score to identify patient deterioration. Design: A qualitative exploratory design. Methods: Six focus groups were conducted at six Danish hospitals from February to June 2019. Registered Nurses from both medical, surgical and emergency departments participated. The focus groups were analysed using content analysis. Results: One theme and four categories were identified. Theme: Meaningful in identifying patient deterioration but causing frustration due to lack of flexibility. Categories: (a) Inter‐professional collaboration strengthened through the use of Early Warning Score systems, (b) Enhanced professional development and communication among nurses when using Early Warning Score systems, (c) Detecting patient deterioration by integrating nurses' clinical gaze with Early Warning Score systems and (d) Modification and fear of making mistakes when using Early Warning Score systems. [ABSTRACT FROM AUTHOR]

Abstract Background The National Early Warning Score (NEWS/NEWS 2) has been adopted across the National Health Service (NHS) in the U.K. as a method of escalating care for deteriorating patients. Intensive Care Unit (ICU) resources are limited and in high demand, with patient discharge a focal point for managing resources effectively. There are currently no universally accepted methods for assessing discharge of patients from an ICU, which can cause premature discharges and put patients at risk of subsequent deterioration, readmission to ICU or death. Methods We tested the ability of the NEWS to discriminate patients within 24h of admission to an ICU in a U.S. hospital during 2001–2012, by their end discharge location: home; hospital ward; nursing facility; hospice and death. The NEWS performance was compared across five different ICU specialties, using the area under the receiver operating characteristic (AUROC) curve and a large vital signs database (n=2,723,055) collected from 28,523 critical care admissions. Results The NEWS AUROC (95% CI) at 24h following admission: all patients 0.727 (0.709–0.745); Coronary Care Unit (CCU) 0.829 (0.821–0.837); Cardiac Surgery Recovery Unit (CSRU) 0.844 (0.838–0.850); Medical Intensive Care Unit (MICU) 0.778 (0.767–0.791); Surgical Intensive Care Unit (SICU) 0.775 (0.762–0.788); Trauma Surgical Intensive Care Unit (TSICU) 0.765 (0.751–0.773). Conclusions The NEWS has reasonable discrimination for any ICU patient’s discharge location. The NEWS has greater ability to discriminate patients in the Coronary Care Unit (CCU) and Cardiac Surgery Recovery Unit (CSRU) compared to other ICU specialties. The NEWS has the real potential to be applied within a universal discharge planning tool for ICU, improving patient safety at the point of discharge.

Aims: International early warning scores (EWS) including the additive National Early Warning Score (NEWS) and logistic EWS currently utilise physiological snapshots to predict clinical deterioration. We hypothesised that a dynamic score including vital sign trajectory would improve discriminatory power.Methods: Multicentre retrospective analysis of electronic health record data from postoperative patients admitted to cardiac surgical wards in four UK hospitals. Least absolute shrinkage and selection operator-type regression (LASSO) was used to develop a dynamic model (DyniEWS) to predict a composite adverse event of cardiac arrest, unplanned intensive care re-admission or in-hospital death within 24 h.Results: A total of 13,319 postoperative adult cardiac patients contributed 442,461 observations of which 4234 (0.96%) adverse events in 24 h were recorded. The new dynamic model (AUC = 0.80 [95% CI 0.78-0.83], AUPRC = 0.12 [0.10-0.14]) outperforms both an updated snapshot logistic model (AUC = 0.76 [0.73-0.79], AUPRC = 0.08 [0.60-0.10]) and the additive National Early Warning Score (AUC = 0.73 [0.70-0.76], AUPRC = 0.05 [0.02-0.08]). Controlling for the false alarm rates to be at current levels using NEWS cut-offs of 5 and 7, DyniEWS delivers a 7% improvement in balanced accuracy and increased sensitivities from 41% to 54% at NEWS 5 and 18% to -30% at NEWS 7.Conclusions: Using an advanced statistical approach, we created a model that can detect dynamic changes in risk of unplanned readmission to intensive care, cardiac arrest or in-hospital mortality and can be used in real time to risk-prioritise clinical workload. [ABSTRACT FROM AUTHOR]

Aims & objectives: To describe registered nurses' perceptions, experiences and barriers for using the National Early Warning Score in relation to their work experience and medical affiliation. Background: Indications of inconsistencies in adherence to the National Early Warning Score have emerged. Design: Web‐based questionnaire study. Methods: The questionnaire was sent to 3,165 registered nurses working in somatic hospitals in the southern part of Sweden. Strengthening the Reporting of Observational Studies in Epidemiology was adhered. Results: Seventy‐one per cent of the 1,044 respondents reported adherence to the National Early Warning Score guidelines recommended frequency of monitoring and 74% to the clinical response scale. The shorter the working experience, the higher the proportion of registered nurses who answered positively to the National Early Warning Score allowing them to better prioritise their care with short nursing experience. When categorising nurses according to their workplace's medical affiliation, adherence to the National Early Warning Score guidelines recommended frequency of monitoring was reported highest in surgery and orthopaedics (66%) and lowest in the cardiac high dependency unit (52%). Corresponding proportions of reported adherence to the clinical response scale were highest in orthopaedics (82%) and lowest in the cardiac high dependency unit (48%). Lack of response from the doctor was reported as one of the main reasons for not adhering to the National Early Warning Score by 50% of the registered nurse. Conclusion: In general, registered nurses perceived the National Early Warning Score as a useful tool, supporting their gut feeling about an unstable patient. Barriers to the National Early Warning Score were found in doctors and the most experienced registered nurses, indicating the need for resources to be focused on the adherence of these members of the healthcare team. Relevance to clinical practice: In general, the registered nurses answered positively to the National Early Warning Score. We found indications that there is a need to focus resources on the adherence of the most experienced registered nurse and the doctors. [ABSTRACT FROM AUTHOR]

This article discusses the evidence in relation to preventable deaths and a reported culture of suboptimal care. It warns of the dangers of over-relying on track and trigger systems (TTS) in place of clinical judgement. The article explores cultural and behavioural factors, the effects of short staffing and inappropriate skill mix, which all increase the risk of human error. It emphasises a key message that registered nurses must reflect on the need to change their individual and team approaches to the recognition and assessment of the deteriorating patient. [ABSTRACT FROM AUTHOR]

Evidence suggests that the identification and response to the deteriorating patient continues to be an ongoing concern, despite the widespread use of track and trigger score (TTS) systems. This article discusses the variations in the parameters included in the different TTS systems in use across the NHS and their sensitivity. Clinical guidelines and physiological theory are used to appraise the parameters allocated in the National Early Warning Score (NEWS 1 and 2), highlighting potential limitations of the tool. The findings lead to the conclusion that registered nurses should not rely solely on NEWS, but should use it to support their clinical judgement. [ABSTRACT FROM AUTHOR]

Objectives: To develop a logistic regression model to predict the risk of sepsis following emergency medical admission using the patient's first, routinely collected, electronically recorded vital signs and blood test results and to validate this novel computer-aided risk of sepsis model, using data from another hospital.Design: Cross-sectional model development and external validation study reporting the C-statistic based on a validated optimized algorithm to identify sepsis and severe sepsis (including septic shock) from administrative hospital databases using International Classification of Diseases, 10th Edition, codes.Setting: Two acute hospitals (York Hospital - development data; Northern Lincolnshire and Goole Hospital - external validation data).Patients: Adult emergency medical admissions discharged over a 24-month period with vital signs and blood test results recorded at admission.Interventions: None.Main Results: The prevalence of sepsis and severe sepsis was lower in York Hospital (18.5% = 4,861/2,6247; 5.3% = 1,387/2,6247) than Northern Lincolnshire and Goole Hospital (25.1% = 7,773/30,996; 9.2% = 2,864/30,996). The mortality for sepsis (York Hospital: 14.5% = 704/4,861; Northern Lincolnshire and Goole Hospital: 11.6% = 899/7,773) was lower than the mortality for severe sepsis (York Hospital: 29.0% = 402/1,387; Northern Lincolnshire and Goole Hospital: 21.4% = 612/2,864). The C-statistic for computer-aided risk of sepsis in York Hospital (all sepsis 0.78; sepsis: 0.73; severe sepsis: 0.80) was similar in an external hospital setting (Northern Lincolnshire and Goole Hospital: all sepsis 0.79; sepsis: 0.70; severe sepsis: 0.81). A cutoff value of 0.2 gives reasonable performance.Conclusions: We have developed a novel, externally validated computer-aided risk of sepsis, with reasonably good performance for estimating the risk of sepsis for emergency medical admissions using the patient's first, electronically recorded, vital signs and blood tests results. Since computer-aided risk of sepsis places no additional data collection burden on clinicians and is automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure. [ABSTRACT FROM AUTHOR]

The national early warning score (NEWS) is recommended to detect deterioration in hospitalised patients. In 2013, a NEWS-based system was introduced in a hospital service with over 250,000 annual admissions, generating large amounts of NEWS data. The quality of such data has not been described. We critically assessed NEWS data recorded over 12 months. This observational study included NEWS records from adult inpatients hospitalized in the Capital Region of Denmark during 2014. Physiological variables and the use of supplementary oxygen (NEWS variables) were recorded. We identified implausible records and assessed the distributions of NEWS variable values. Of 2,835,331 NEWS records, 271,103 (10%) were incomplete with one or more variable missing and 0.2% of records containing implausible values. Digit preferences were identified for respiratory rate, supplementation oxygen flow, pulse rate, and systolic blood pressure. There was an accumulation of pulse rate records below 91 beats per minute. Among complete NEWS records, 64% had NEWS ≥ 1; 29% had NEWS ≥ 3; and 8% had NEWS ≥ 6. In a large set of NEWS data, 10% of the records were incomplete. In a system where data were manually entered into an electronic medical record, digit preferences and the accumulation of pulse rate records below 91 beats per minute, which is the limit for NEWS point generation, showed that staff practice influenced the recorded values. This indicates a potential limitation of transferability of research results obtained in such systems to fully automated systems. [ABSTRACT FROM AUTHOR]

Objective: Routine administrative data have been used to show that patients admitted to hospitals over the weekend appear to have a higher mortality compared to weekday admissions. Such data do not take the severity of sickness of a patient on admission into account. Our aim was to incorporate a standardized vital signs physiological-based measure of sickness known as the National Early Warning Score to investigate if weekend admissions are: sicker as measured by their index National Early Warning Score; have an increased mortality; and experience longer delays in the recording of their index National Early Warning Score. Methods: We extracted details of all adult emergency medical admissions during 2014 from hospital databases and linked these with electronic National Early Warning Score data in four acute hospitals. We analysed 47,117 emergency admissions after excluding 1657 records, where National Early Warning Score was missing or the first (index) National Early Warning Score was recorded outside ±24 h of the admission time. Results: Emergency medical admissions at the weekend had higher index National Early Warning Score (weekend: 2.53 vs. weekday: 2.30, p<0.001) with a higher mortality (weekend: 706/11,332 6.23% vs. weekday: 2039/35,785 5.70%; odds ratio=1.10, 95% CI 1.01 to 1.20, p=0.04) which was no longer seen after adjusting for the index National Early Warning Score (odds ratio=0.99, 95% CI 0.90 to 1.09, p=0.87). Index National Early Warning Score was recorded sooner (-0.45 h, 95% CI -0.52 to -0.38, p<0.001) for weekend admissions. Conclusions: Emergency medical admissions at the weekend with electronic National Early Warning Score recorded within 24 h are sicker, have earlier clinical assessments, and after adjusting for the severity of their sickness, do not appear to have a higher mortality compared to weekday admissions. A larger definitive study to confirm these findings is needed. [ABSTRACT FROM AUTHOR]