[Experience of nurses using the COVID-19 Early Warning Score in the care of COVID-19 patients: A qualitative study]

Experience of nurses using the COVID-19 Early Warning Score in the care of COVID-19 patients: A qualitative study Abstract: Background: In all phases of the COVID-19 disease, patients are at risk of acute deterioration. In order to identify patients at risk at an early stage, the COVID-19-EWS Salzburg was implemented in April 2020 at the University Hospital Salzburg. So far, the applicability, practicability and relevance of the EWS for acute inpatient COVID-19 care are unknown. Aim: The aim of this qualitative study was to describe the relevance and practicability of the COVID-19-EWS Salzburg as a risk assessment tool for acute inpatient COVID-19 care, based on the experiences of the nursing staff. Methods: Nine semi-structured expert interviews were conducted with the nursing staff of the COVID-19 acute care unit. The data were analysed by qualitative content analysis. Results: Nurses described the EWS as relevant to practice because the score facilitates decision-making, increases patient safety, and enhances interprofessional communication. Both the Early Warning Score (EWS) and experience in caring for COVID-19 patients were found to be relevant for decision-making in the context of managing clinical deterioration. The score provided a sense of security in the care of COVID-19 patients, particularly to new and inexperienced nurses. Conclusion: The participating nurses describe the COVID-19-EWS Salzburg as a useful and practical risk assessment instrument, complementing clinical judgment. A need for adaptation concerning the parameters oxygen saturation and oxygen requirement was identified.

General ward nurses detection and response to clinical deterioration in three hospitals at the Kenyan coast: a convergent parallel mixed methods study

BACKGROUND

In low and middle-income countries like Kenya, critical care facilities are limited, meaning acutely ill patients are managed in the general wards. Nurses in these wards are expected to detect and respond to patient deterioration to prevent cardiac arrest or death. This study examined nurses' vital signs documentation practices during clinical deterioration and explored factors influencing their ability to detect and respond to deterioration.

METHODS

This convergent parallel mixed methods study was conducted in the general medical and surgical wards of three hospitals in Kenya's coastal region. Quantitative data on the extent to which the nurses monitored and documented the vital signs 24 h before a cardiac arrest (death) occurred was retrieved from patients' medical records. In-depth, semi-structured interviews were conducted with twenty-four purposefully drawn registered nurses working in the three hospitals' adult medical and surgical wards.

RESULTS

This study reviewed 405 patient records and found most of the documentation of the vital signs was done in the nursing notes and not the vital signs observation chart. During the 24 h prior to death, respiratory rate was documented the least in only 1.2% of the records. Only a very small percentage of patients had any vital event documented for all six-time points, i.e. four hourly. Thematic analysis of the interview data identified five broad themes related to detecting and responding promptly to deterioration. These were insufficient monitoring of vital signs linked to limited availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork constraints among healthcare workers.

CONCLUSION

The study showed that nurses did not consistently monitor and record vital signs in the general wards. They also worked in suboptimal ward environments that do not support their ability to promptly detect and respond to clinical deterioration. The findings illustrate the importance of implementation of standardised systems for patient assessment and alert mechanisms for deterioration response. Furthermore, creating a supportive work environment is imperative in empowering nurses to identify and respond to patient deterioration. Addressing these issues is not only beneficial for the nurses but, more importantly, for the well-being of the patients they serve.

Preparedness for Severe Maternal Morbidity in European Hospitals: The MaCriCare Study

PURPOSE

To evaluate obstetric units (OUs) and intensive care units (ICUs) preparedness for severe maternal morbidity (SMM).

METHODS

From September 2021 to January 2022, an international multicentre cross-sectional study surveyed OUs in 26 WHO Europe Region countries. We assessed modified early obstetric warning score usage (MEOWS), approaches to four SMM clinical scenarios, invasive monitoring availability in OUs, and access to high-dependency units (HDUs) and onsite ICUs. Within ICUs, we examined the availability of trained staff, response to obstetric emergencies, leadership, and data collection.

RESULTS

1133 responses were evaluated. MEOWS use was 34.5%. Non-obstetric early warning scores were being used. 21.4% (242) of OUs provided invasive monitoring in the OU. A quarter lacked access to onsite HDU beds. In cases of SMM, up to 13.8% of all OUs indicated the need for transfer to another hospital. The transfer rate was highest (74.0%) in small units. 81.9% of centers provided onsite ICU facilities to obstetric patients. Over 90% of the onsite ICUs provided daily specialist obstetric reviews but lacked immediate access to key resources: 3.4% - uterotonic drugs, 7.5% - neonatal resuscitation equipment, 9.2% - neonatal resuscitation team, 11.4% - perimortem cesarean section equipment. 41.2% reported obstetric data to a national database.

CONCLUSION

Gaps in provision exist for obstetric patients with SMM in Europe, potentially compromising patient safety and experience. MEOWS use in OUs was low, while access to invasive monitoring and onsite HDU and ICU facilities was variable. ICUs frequently lacked resources and did not universally collect obstetric data for quality control.

The predictive value of the modified early warning score for admission to the intensive care unit in patients with a hematologic malignancy - A multicenter observational study

OBJECTIVES

The modified early warning score (MEWS) is used to detect clinical deterioration of hospitalized patients. We aimed to investigate the predictive value of MEWS and derived quick Sequential Organ Failure Assessment (qSOFA) scores for intensive care unit admission in patients with a hematologic malignancy admitted to the ward.

DESIGN

Retrospective, observational study in two Dutch university hospitals.

SETTING

Data from adult patients with a hematologic malignancy, admitted to the ward over a 2-year period, were extracted from electronic patient files.

MAIN OUTCOME MEASURES

Intensive care admission.

RESULTS

We included 395 patients with 736 hospital admissions; 2% (n = 15) of admissions resulted in admission to the intensive care unit. A higher MEWS (OR 1.5; 95 %CI 1.3-1.80) and qSOFA (OR 4.4; 95 %CI 2.1-9.3) were associated with admission. Using restricted cubic splines, a rise in the probability of admission for a MEWS ≥ 6 was observed. The AUC of MEWS for predicting admission was 0.830, the AUC of qSOFA was 0.752. MEWS was indicative for intensive care unit admission two days before admission.

CONCLUSIONS

MEWS was a sensitive predictor of ICU admission in patients with a hematologic malignancy, superior to qSOFA. Future studies should confirm cut-off values and identify potential additional characteristics, to further enhance identification of critically ill hemato-oncology patients.

IMPLICATIONS FOR CLINICAL PRACTICE

The Modified Early Warning Score (MEWS) can be used as a tool for healthcare providers to monitor clinical deterioration and predict the need for intensive care unit admission in patients with a hematologic malignancy. Yet, consistent application and potential reevaluation of current thresholds is crucial. This will enable bedside nurses to more effectively identify patients needing adjunctive care, facilitating timely interventions and improved outcome.

The implementation of a real time early warning system using machine learning in an Australian hospital to improve patient outcomes

BACKGROUND

Early Warning Scores (EWS) monitor inpatient deterioration predominantly using vital signs. We evaluated inpatient outcomes after implementing an Artificial Intelligence (AI) based intervention in our local EWS.

METHODS

A prior study calculated a Deterioration Index (DI) with logistic regression utilising demographics, vital signs, and laboratory results at multiple time points to predict any major adverse event (MAE-all cause mortality, ICU admission, or medical emergency team activation). The current study is a single hospital, pre-post study in Australia comparing the DI plus the existing EWS (Between the Flags-BTF) to only BTF. Data were collected on all eligible inpatients (≥ 16 years, admitted ≥ 24 hours, in general non-palliative wards). Controls were inpatients in the same hospital between January and December 2019. The DI was integrated into the electronic medical record and alerts were sent to senior ward nurse phones (July 2020 -April 2021).

RESULTS

We enrolled 28,639 patients (median age 73 years, IQR:60-83) with 52.3% female. The intervention and control groups did not show any statistically significant differences apart from reduced admissions via the emergency department in the intervention group (40.4% vs 41.6%, P=0.03). Risk for an MAE was lower in intervention than control (RR: 0.81; 95%CI: 0.74-0.89). Length of hospital stay was significantly reduced in the intervention group (3.74 days, IQR 1.84-7.26) compared to the control group (3.86 days, IQR 1.86-7.86, P=0.002) CONCLUSIONS: Implementing the DI in one hospital in Australia was associated with some improved patient outcomes. Future RCTs are needed for further validation.

Multicenter validation of Early Warning Scores for detection of clinical deterioration in COVID-19 hospitalized patients

OBJECTIVE

Investigate the predictive value of NEWS2, NEWS-C, and COVID-19 Severity Index for predicting intensive care unit (ICU) transfer in the next 24h.

DESIGN

Retrospective multicenter study.

SETTING

Two third-level hospitals in Argentina.

PATIENTS

All adult patients with confirmed COVID-19, admitted on general wards, excluding patients with non-intubated orders.

INTERVENTIONS

Patients were divided between those who were admitted to ICU and non-admitted. We calculated the three scores for each day of hospitalization.

VARIABLES

We evaluate the calibration and discrimination of the three scores for the outcome ICU admission within 24, 48h, and at hospital admission.

RESULTS

We evaluate 13,768 days of hospitalizations on general medical wards of 1318 patients. Among these, 126 (9.5%) were transferred to ICU. The AUROC of NEWS2 was 0.73 (95%CI 0.68-0.78) 24h before ICU admission, and 0.52 (95%CI 0.47-0.57) at hospital admission. The AUROC of NEWS-C was 0.73 (95%CI 0.68-0.78) and 0.52 (95%CI 0.47-0.57) respectively, and the AUROC of COVID-19 Severity Index was 0.80 (95%CI 0.77-0.84) and 0.61 (95%CI 0.58-0.66) respectively. COVID-19 Severity Index presented better calibration than NEWS2 and NEWS-C.

CONCLUSION

COVID-19 Severity index has better calibration and discrimination than NEWS2 and NEWS-C to predict ICU transfer during hospitalization.

Multicenter validation of Early Warning Scores for detection of clinical deterioration in COVID-19 hospitalized patients

Objective

Investigate the predictive value of NEWS2, NEWS-C, and COVID-19 Severity Index for predicting intensive care unit (ICU) transfer in the next 24 h.

Design

Retrospective multicenter study.

Setting

Two third-level hospitals in Argentina.

Patients

All adult patients with confirmed COVID-19, admitted on general wards, excluding patients with non-intubated orders.

Interventions

Patients were divided between those who were admitted to ICU and non-admitted. We calculated the three scores for each day of hospitalization.

Variables

We evaluate the calibration and discrimination of the three scores for the outcome ICU admission within 24, 48 h, and at hospital admission.

Results

We evaluate 13,768 days of hospitalizations on general medical wards of 1318 patients. Among these, 126 (9.5%) were transferred to ICU. The AUROC of NEWS2 was 0.73 (95%CI 0.68-0.78) 24 h before ICU admission, and 0.52 (95%CI 0.47-0.57) at hospital admission. The AUROC of NEWS-C was 0.73 (95%CI 0.68-0.78) and 0.52 (95%CI 0.47-0.57) respectively, and the AUROC of COVID-19 Severity Index was 0.80 (95%CI 0.77-0.84) and 0.61 (95%CI 0.58-0.66) respectively. COVID-19 Severity Index presented better calibration than NEWS2 and NEWS-C.

Conclusion

COVID-19 Severity index has better calibration and discrimination than NEWS2 and NEWS-C to predict ICU transfer during hospitalization.

Characteristics and Prognosis of Hospitalized Patients at High Risk of Deterioration Identified by the Rapid Response System: a Multicenter Cohort Study

We aimed to investigate the characteristics and prognosis of high risk hospitalized patients identified by the rapid response system (RRS). A multicentered retrospective cohort study was conducted from June 2019 to December 2020. The National Early Warning Score (NEWS) was used for RRS activation. The outcome was unexpected intensive care unit (ICU) admission within 24 hours after RRS activation. The 11,459 patients with RRS activations were included. We found distinct clinical characteristics in patients who underwent ICU admission. All NEWS parameters were associated with the risk of unexpected ICU admission except body temperature. Body mass index, pulmonary disease, and cancer are related to the decreased risk of unexpected ICU admission. In conclusion, there were differences in clinical characteristics among high risk patients, and those differences were associated with unexpected ICU admissions. Clinicians should consider factors relating to unexpected ICU admission in the management of high risk patients identified by RRS.

The Role of Modified Early Warning Score (MEWS) in the Prognosis of Acute Pancreatitis

Objectives

Modified Early Warning Score (MEWS) is a reliable, safe, instant, and inexpensive score for prognosticating patients with acute pancreatitis (AP) due to its ability to reflect ongoing changes of the systemic inflammatory response syndrome associated with AP. Our study sought to determine an optimal MEWS value in predicting severity in AP and determine its accuracy in doing so.

Methods

Patients diagnosed with AP and admitted to a single institution were analyzed to determine the value of MEWS in identifying severe AP (SAP). The highest MEWS (hMEWS) score for the day and the mean of all the scores of a given day (mMEWS) were determined for each day. Sensitivity, specificity, negative predictive value (NPV), and positive predictive values (PPV) were calculated for the optimal MEWS values obtained.

Results

Two hundred patients were included in the study. The data suggested that an hMEWS value > 2 on day one is most accurate in predicting SAP, with a specificity of 90.8% and PPV of 83.3%. An mMEWS of > 1.2 on day two was the most accurate in predicting SAP, with a sensitivity of 81.2%, specificity of 76.6%, PPV of 69.8%, and NPV of 85.9%. These were found to be more accurate than previous studies.

Conclusions

MEWS provides a novel, easy, instant, repeatable, and reliable prognostic score that is comparable, if not superior, to existing scoring systems. However, its true value may lie in its use in resource-limited settings such as primary health care centers.

Predictive Models of Fever, ICU Transfer, and Mortality in Hospitalized Patients With Neutropenia

Supplemental Digital Content is available in the text.

Neutropenia is a common side effect of myelosuppressive chemotherapy and is associated with adverse outcomes. Early Warning Scores are used to identify at-risk patients and facilitate rapid clinical interventions. Since few Early Warning Scores have been validated in patients with neutropenia, we aimed to create predictive models and nomograms of fever, ICU transfer, and mortality in hospitalized neutropenic patients.

The impact of a modified New Zealand Early Warning Score (M-NZEWS) and NZEWS on ward patients triggering a medical emergency team activation: A mixed methods sequential design

INTRODUCTION

Limited research exists on the effectiveness of the New Zealand Early Warning Score (NZEWS).

AIM

To determine the impact of a modified NZEWS (M-NZEWS) and NZEWS on ward patients' medical emergency team activation triggers.

RESEARCH DESIGN

Mixed methods sequential design.

METHODS

Three phases included: 1) review of M-NZEWS electronic data to determine the effect of a M-NZEWS and NZEWS on ward patients; 2) an in-depth review of 20 Māori patients allocated to lower escalation zones if the NZEWS were adopted and 3) the number of electronic medical emergency team activation triggers compared to the number of actual medical emergency team activations.

RESULTS

1255 patients and 3505 vital sign data sets were analysed. Adopting the NZEWS would result in 396 (26.8%) fewer patients triggering a medical emergency team activation. The biggest impact would be on Māori, with 38.6% of Māori allocated to a lower escalation zone. Only 51.2% of patients with a medical emergency team activation had vital signs triggering the response electronically documented.

CONCLUSION

Changing from the M-NZEWS to NZEWS will reduce the number of medical emergency team activation triggers, with the biggest impact on Māori. Electronic vital sign data does not accurately reflect the number of ward medical emergency team triggers or activations.

National Early Warning Score: A survey of registered nurses' perceptions, experiences and barriers

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.

Predictors of in-hospital cardiac arrest within 24 h after emergency department triage: A case-control study in urban Thailand

OBJECTIVE

This study describes the predictors of in-hospital cardiac arrest (IHCA) within 24 h of ED triage and evaluates their ability to predict patients at risk of IHCA.

METHODS

A case-control study was conducted in the ED. 'Cases' are herein defined as hospitalised patients who experienced IHCA within 24 h after ED triage. The exclusion criteria were those younger than 16 years old, cases of traumatic arrest, or had do-not-resuscitate orders. The controls were adults, non-traumatic cases, who did not experience IHCA within 24 h of ED triage. A multivariable regression model was used to identify significant predictors of IHCA. The ability to discriminate was quantified by utilising an area under receiver operating characteristic (AuROC) curve.

RESULTS

Two hundred and fifty IHCAs were compared with 1000 controls. Five predictors emerged that were: higher National Early Warning Score (NEWS) at triage, equal or increase of NEWS after ED management, coronary artery disease as a comorbid disease, the use of a vasoactive agent, and initial serum bicarbonate level lower than 23.5 mmoL/L, independently associated with IHCA. The AuROC of the final model from all predictors was 0.91 (95% CI 0.89-0.93) higher than NEWS alone model (AuROC at 0.78, 95% CI 0.74-0.81).

CONCLUSIONS

We conclude that a combination of NEWS and four independent predictors identify patients at risk of IHCA more effectively than NEWS alone.

The National Early Warning Score predicts mortality in hospital ward patients with deviating vital signs: A retrospective medical record review study

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.

Continuous vital sign monitoring after major abdominal surgery-Quantification of micro events

INTRODUCTION

Millions of patients undergo major abdominal surgery worldwide each year, and the post-operative phase carries a high risk of respiratory and circulatory complications. Standard ward observation of patients includes vital sign registration at regular intervals. Patients may deteriorate between measurements, and this may be detected by continuous monitoring. The aim of this study was to compare the number of micro events detected by continuous monitoring to those documented by the widely used standardized Early Warning Score (EWS).

METHODS

Fifty patients were continuously monitored with peripheral arterial oxygen saturation (SpO₂ ), heart rate (HR), and respiratory rate (RR) the first 4 days after major abdominal cancer surgery. EWS was monitored as routine practice. Number and duration of events were analyzed using Fisher's exact test and Wilcoxon rank sum test.

RESULTS

Continuous monitoring detected a SpO₂ <92% in 98% of patients vs 16% of patients detected by EWS (P < .0001). Micro events of SpO₂ <92% lasting longer than 60 minutes were found in 58% of patients by continuous monitoring vs 16% by the EWS (P < .0001). Fifty-two percent of patients had micro events of SpO₂ <85% lasting longer than 10 minutes. Continuous monitoring found tachycardia in 60% of patients vs 6% by the EWS. Frequency of events for bradycardia, tachypnea, and bradypnea showed similar patterns.

CONCLUSION

Very low SpO₂ and tachycardia in post-operative patients are common and under-diagnosed by the EWS. Continuous monitoring can discover these micro events and potentially contribute to earlier detection and, potentially, result in prevention of clinical complications.

Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards

BACKGROUND

Large amounts of patient data are routinely manually collected in hospitals by using standalone medical devices, including vital signs. Such data is sometimes stored in spreadsheets, not forming part of patients' electronic health records, and is therefore difficult for caregivers to combine and analyze. One possible solution to overcome these limitations is the interconnection of medical devices via the Internet using a distributed platform, namely the Internet of Things. This approach allows data from different sources to be combined in order to better diagnose patient health status and identify possible anticipatory actions.

METHODS

This work introduces the concept of the Internet of Health Things (IoHT), focusing on surveying the different approaches that could be applied to gather and combine data on vital signs in hospitals. Common heuristic approaches are considered, such as weighted early warning scoring systems, and the possibility of employing intelligent algorithms is analyzed.

RESULTS

As a result, this article proposes possible directions for combining patient data in hospital wards to improve efficiency, allow the optimization of resources, and minimize patient health deterioration.

CONCLUSION

It is concluded that a patient-centered approach is critical, and that the IoHT paradigm will continue to provide more optimal solutions for patient management in hospital wards.

External validation of a decision tree early warning score using only laboratory data: A retrospective review of prospectively collected data

INTRODUCTION

Early warning scores (EWS) have been developed to identify the degree of illness severity among acutely ill patients. One system, The Laboratory Decision Tree Early Warning Score (LDT-EWS) is wholly laboratory data based. Laboratory data was used in the development of a rare computerized method, developing a decision tree analysis. This article externally validates LDT-EWS, which is obligatory for an EWS before clinical use.

METHOD

We conducted a retrospective review of prospectively collected data based on a time limited sample of all patients admitted through the medical admission unit (MAU) on a Danish secondary hospital. All consecutive adult patients admitted from 2 October 2008 until 19 February 2009, and from 23 February 2010 until 26 May 2010, were included. Validation was made by calculating the discriminatory power as area under the receiver-operating curve (AUROC) and calibration (precision) as Hosmer-Lemeshow Goodness of fit test.

RESULTS

A total of 5858 patients were admitted and 4902 included (83.7%). In-hospital mortality in our final dataset (n=4902) was 3.5%. Discriminatory power (95% CI), identifying in-hospital death was 0.809 (0.777-0.842). Calibration was good with a goodness-of-fit test of X²=5.37 (7 degrees of freedom), p=0.62.

CONCLUSION

LDT-EWS has acceptable ability to identify patients at high risk of dying during hospitalization with good precision. Further studies performing impact analysis are required before this score should be implemented in clinical practice.

A survey of midwives' use of systematic monitoring in parturients

OBJECTIVE

systematic monitoring has recently been implemented widely in non-obstetric departments. In the UK, Early Warning Score (EWS) systems specifically designed for the obstetric population (OEWS) are used. No information on the use of OEWS in Scandinavia has been reported. Consequently, we wanted to investigate the use of vital signs and attitude towards systematic monitoring of parturients in Denmark, Norway and Sweden.

DESIGN

electronic questionnaires sent to heads of midwifery. The heads of midwifery referred two clinically active midwives. All in-hospital obstetric departments in Scandinavia were invited to participate.

FINDINGS

heads of midwifery from 76 departments (68%), and 125 clinical midwives (82%) responded. Ten per cent of midwives reported use of OEWS. Reported implementation barriers to OEWS included lack of evidence and suspected impact on the parturient due to frequent interruptions. fifty-four per cent of clinical midwives reported a systolic blood pressure threshold of 90-139mmHg, while 33% reported a threshold of>160mmHg. Ninety-three per cent stated a low threshold for maternal heart rate<60 bpm whereas 10% reported an upper threshold heart rate ≥ 150 bpm. Forty-seven per cent reported call for assistance thresholds for maternal heart rate at 60-110 bpm.

KEY CONCLUSIONS

OEWS is not implemented in Scandinavian obstetric departments and reported thresholds of vital signs varied considerably. Major barriers for implementation in Scandinavia include midwives' concern of interruptions for the parturient and increased workload, and unclear benefit from use of OEWS. Local departments should provide midwives with unambiguous thresholds for vital signs in parturients either through local guidelines or via OEWS.

Pregnancy physiology pattern prediction study (4P study): protocol of an observational cohort study collecting vital sign information to inform the development of an accurate centile-based obstetric early warning score

INTRODUCTION

Successive confidential enquiries into maternal deaths in the UK have identified an urgent need to develop a national early warning score (EWS) specifically for pregnant or recently pregnant women to aid more timely recognition, referral and treatment of women who are developing life-threatening complications in pregnancy or the puerperium. Although many local EWS are in use in obstetrics, most have been developed heuristically. No current obstetric EWS has defined the thresholds at which an alert should be triggered using evidence-based normal ranges, nor do they reflect the changing physiology that occurs with gestation during pregnancy.

METHODS AND ANALYSIS

An observational cohort study involving 1000 participants across three UK sites in Oxford, London and Newcastle. Pregnant women will be recruited at approximately 14 weeks' gestation and have their vital signs (heart rate, blood pressure, respiratory rate, oxygen saturation and temperature) measured at 4 to 6-week intervals during pregnancy. Vital signs recorded during labour and delivery will be extracted from hospital records. After delivery, participants will measure and record their own vital signs daily for 2 weeks. During the antenatal and postnatal periods, vital signs will be recorded on an Android tablet computer through a custom software application and transferred via mobile internet connection to a secure database. The data collected will be used to define reference ranges of vital signs across normal pregnancy, labour and the immediate postnatal period. This will inform the design of an evidence-based obstetric EWS.

ETHICS AND DISSEMINATION

The study has been approved by the NRES committee South East Coast-Brighton and Sussex (14/LO/1312) and is registered with the ISRCTN (10838017). All participants will provide written informed consent and can withdraw from the study at any point. All data collected will be managed anonymously. The findings will be disseminated in international peer-reviewed journals and through research conferences.

Emergency department Modified Early Warning Score association with admission, admission disposition, mortality, and length of stay

BACKGROUND

Geisinger Health System implemented the Modified Early Warning Score (MEWS) in 2011 and is fully integrated to the Electronic Medical Record (EMR). Our objective was to assess whether the emergency department (ED) MEWS (auto-calculated by EMR) is associated with admission to the hospital, admission disposition, inpatient mortality, and length of stay (LOS) 4 years after its implementation.

METHODS

A random sample of 3,000 patients' first encounter in the ED was extracted in the study period (between January 1, 2014 and May 31, 2015). Logistic regression was done to analyze whether mean, maximum, and median ED MEWS is associated with admission disposition, mortality, and LOS.

RESULTS

Mean, maximum, and median ED MEWS is associated with admission to the hospital, admission disposition, and mortality. It correlates weakly with LOS.

CONCLUSION

MEWS can be integrated to the EMR, and the score automatically generated still helps predict catastrophic events. MEWS can be used as a triage tool when deciding whether and where patients should be admitted.

[Results of applying a paediatric early warning score system as a healthcare quality improvement plan]

OBJECTIVES

The aims of this study were to introduce a paediatric early warning score (PEWS) into our daily clinical practice, as well as to evaluate its ability to detect clinical deterioration in children admitted, and to train nursing staff to communicate the information and response effectively.

MATERIAL AND METHODS

An analysis was performed on the implementation of PEWS in the electronic health records of children (0-15 years) in our paediatric ward from February 2014 to September 2014. The maximum score was 6. Nursing staff reviewed scores >2, and if >3 medical and nursing staff reviewed it. Monitoring indicators: % of admissions with scoring; % of complete data capture; % of scores >3; % of scores >3 reviewed by medical staff, % of changes in treatment due to the warning system, and number of patients who needed Paediatric Intensive Care Unit (PICU) admission, or died without an increased warning score.

RESULTS

The data were collected from all patients (931) admitted. The scale was measured 7,917 times, with 78.8% of them with complete data capture. Very few (1.9%) showed scores >3, and 14% of them with changes in clinical management (intensifying treatment or new diagnostic tests). One patient (scored 2) required PICU admission. There were no deaths. Parents or nursing staff concern was registered in 80% of cases.

CONCLUSIONS

PEWS are useful to provide a standardised assessment of clinical status in the inpatient setting, using a unique scale and implementing data capture. Because of the lack of severe complications requiring PICU admission and deaths, we will have to use other data to evaluate these scales.

Identifying Deteriorating Patients Through Multidisciplinary Team Training

Multidisciplinary training has improved maternity outcomes when the training has been well attended, regular, in house, used high-fidelity simulators, and integrated teamwork training. If these principles were used in other settings, better clinical care may result. This before-after study sought to establish whether a short multidisciplinary training intervention can improve recognition of the deteriorating patient using an aggregated physiological parameter scoring system (Early Warning Score [EWS]). Nursing, medical, and allied nursing staff participated in an hour-long training session, using real-life scenarios with simple tools and structured debriefing. After training, staff were more likely to calculate EWS scores correctly (68.02% vs 55.12%; risk ratio [RR] = 1.24, 95% confidence interval [CI] = 1.07-1.44), and observations were more likely to be performed at the correct frequency (78.57% vs 68.09%; RR = 1.20, 95% CI = 1.09-1.32). Multidisciplinary training, according to core principles, can lead to more accurate identification of deteriorating patients, with implications for subsequent care and outcome.

The impact of the use of the Early Warning Score (EWS) on patient outcomes: a systematic review. Resuscitation. 2014;85:587-594. [PMID: 24467882 DOI: 10.1016/j.resuscitation.2014.01.013]

BACKGROUND

Acute deterioration in critical ill patients is often preceded by changes in physiological parameters, such as pulse, blood pressure, temperature and respiratory rate. If these changes in the patient's vital parameters are recognized early, excess mortality and serious adverse events (SAEs) such as cardiac arrest may be prevented. The Early Warning Score (EWS) is a scoring system which assists with the detection of physiological changes and may help identify patients at risk of further deterioration.

OBJECTIVES

The aim of this systematic review is to evaluate the impact of the use of the Early Warning Score (EWS) on particular patient outcomes, such as in-hospital mortality, patterns of intensive care unit admission and usage, length of hospital stay, cardiac arrests and other serious adverse events of adult patients on general wards and in medical admission units.

DESIGN AND SETTING

Systematic review of studies identified from the bibliographic databases of PubMed, EMBASE.com and The Cochrane Library.

SELECTION CRITERIA

All controlled studies which measured in-hospital mortality, ICU mortality, serious adverse events (SAEs), cardiopulmonary arrest, length of stay and documentation of physiological parameters which used a EWS on the ward or the emergency department to identify patients at risk were included in the review.

DATA COLLECTION AND ANALYSIS

Three reviewers (NA, AT and EH) independently screened all potentially relevant titles and abstracts for eligibility, by using a standardized data-worksheet. Meta-analysis was not possible due to heterogeneity.

MAIN RESULTS

Seven studies met the inclusion criteria. The results of our included studies were mixed, with a positive trend towards better clinical outcomes following the introduction of the EWS chart, sometimes coupled with an outreach service. Six of the seven included studies used mortality as an endpoint: two of these studies reported no significant difference in in-hospital mortality rate; two found a significant reduction of in-hospital mortality; two other studies described a trend towards improved survival. Although, both ICU mortality and serious adverse events were not significantly improved, there was a trend towards reduction of these endpoints after introduction of the EWS. However only two studies looked respectively at each endpoint. There were conflicting results concerning cardiopulmonary arrests. One study found a reduction in the incidence of cardiac arrest calls as well as in the mortality of patients who underwent CPR, while another one found an increased incidence of cardio-pulmonary arrests. Neither study met all methodological quality criteria.

CONCLUSION

The EWS itself is a simple and easy to use tool at the bedside, which may be of help in recognizing patients with potential for acute deterioration. Coupled with an outreach service, it may be used to timely initiate adequate treatment upon recognition, which may influence the clinical outcomes positively. However, the use of adapted forms of the EWS together with different thresholds, poor or inadequate methodology makes it difficult in drawing comparisons. A general conclusion can thus not be generated from the lack of use of a single standardized score and the use of different populations. In future large multi-centre trials using one standardized score are needed also in order to facilitate comparison.