“Identifying the hospitalised patient in crisis”—A consensus conference on the afferent limb of Rapid Response Systems

Combining the Nurse Intuition Patient Deterioration Scale with the National Early Warning Score provides more Net Benefit in predicting serious adverse events: A prospective cohort study in medical, surgical, and geriatric wards

OBJECTIVES

This prospective cohort study aimed to assess the predictive value of the Nurse Intuition Patient Deterioration Scale (NIPDS) combined with the National Early Warning Score (NEWS) for identifying serious adverse events in patients admitted to diverse hospital wards.

RESEARCH METHODOLOGY/DESIGN

Data was collected between December 2020 and February 2021 in a 350-bed acute hospital near Brussels, Belgium. The study followed a prospective cohort design, employing NIPDS alongside NEWS for risk assessment. Patients were monitored for 24 h post-registration, with outcomes recorded.

SETTING

The study was conducted in a hospital with a Rapid Response System (RRS) and electronic patient record wherein NEWS was routinely collected. Patients admitted to two medical, two surgical, and two geriatric wards were included.

MAIN OUTCOME MEASURES

The primary outcome included death, urgent code calls, or unplanned ICU transfers within 24 h after NIPDS registration. The secondary outcome comprised rapid response team activations or changes in Do-Not-Resuscitate codes.

RESULTS

In a cohort of 313 patients, 10/313 and 31/313 patients reached the primary and secondary outcome respectively. For the primary outcome, NIPDS had a sensitivity of 0.900 and specificity of 0.927, while NEWS had a sensitivity of 0.300 and specificity of 0.974. Decision Curve Analysis demonstrated that NIPDS provided more Net Benefit across various Threshold Probabilities. Combining NIPDS and NEWS showed potential for optimizing rapid response systems. Especially in resource-constrained settings, NIPDS could be used as a calling criterion.

CONCLUSION

The NIPDS displayed strong predictive capabilities for adverse events. Integrating NIPDS into existing rapid response systems can objectify nurse intuition, enhancing patient safety.

IMPLICATIONS FOR CLINICAL PRACTICE

The Nurse Intuition Patient Deterioration Scale (NIPDS) is a valuable tool for detecting patient deterioration. Implementing NIPDS alongside traditional scores such as NEWS can improve patient care and safety. The optimal NIPDS threshold to activate rapid response is ≥5.

PeriOperative Quality Initiative (POQI) international consensus statement on perioperative arterial pressure management

Arterial pressure monitoring and management are mainstays of haemodynamic therapy in patients having surgery. This article presents updated consensus statements and recommendations on perioperative arterial pressure management developed during the 11th POQI PeriOperative Quality Initiative (POQI) consensus conference held in London, UK, on June 4-6, 2023, which included a diverse group of international experts. Based on a modified Delphi approach, we recommend keeping intraoperative mean arterial pressure ≥60 mm Hg in at-risk patients. We further recommend increasing mean arterial pressure targets when venous or compartment pressures are elevated and treating hypotension based on presumed underlying causes. When intraoperative hypertension is treated, we recommend doing so carefully to avoid hypotension. Clinicians should consider continuous intraoperative arterial pressure monitoring as it can help reduce the severity and duration of hypotension compared to intermittent arterial pressure monitoring. Postoperative hypotension is often unrecognised and might be more important than intraoperative hypotension because it is often prolonged and untreated. Future research should focus on identifying patient-specific and organ-specific hypotension harm thresholds and optimal treatment strategies for intraoperative hypotension including choice of vasopressors. Research is also needed to guide monitoring and management strategies for recognising, preventing, and treating postoperative hypotension.

Pro-Con Debate: Universal Versus Selective Continuous Monitoring of Postoperative Patients

In this Pro-Con commentary article, we discuss use of continuous physiologic monitoring for clinical deterioration, specifically respiratory depression in the postoperative population. The Pro position advocates for 24/7 continuous surveillance monitoring of all patients starting in the postanesthesia care unit until discharge from the hospital. The strongest arguments for universal monitoring relate to inadequate assessment and algorithms for patient risk. We argue that the need for hospitalization in and of itself is a sufficient predictor of an individual's risk for unexpected respiratory deterioration. In addition, general care units carry the added risk that even the most severe respiratory events will not be recognized in a timely fashion, largely due to higher patient to nurse staffing ratios and limited intermittent vital signs assessments (e.g., every 4 hours). Continuous monitoring configured properly using a "surveillance model" can adequately detect patients' respiratory deterioration while minimizing alarm fatigue and the costs of the surveillance systems. The Con position advocates for a mixed approach of time-limited continuous pulse oximetry monitoring for all patients receiving opioids, with additional remote pulse oximetry monitoring for patients identified as having a high risk of respiratory depression. Alarm fatigue, clinical resource limitations, and cost are the strongest arguments for selective monitoring, which is a more targeted approach. The proponents of the con position acknowledge that postoperative respiratory monitoring is certainly indicated for all patients, but not all patients need the same level of monitoring. The analysis and discussion of each point of view describes who, when, where, and how continuous monitoring should be implemented. Consideration of various system-level factors are addressed, including clinical resource availability, alarm design, system costs, patient and staff acceptance, risk-assessment algorithms, and respiratory event detection. Literature is reviewed, findings are described, and recommendations for design of monitoring systems and implementation of monitoring are described for the pro and con positions.

Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study

Background

The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care).

Objective

Provide an evidence-based approach to creating monitoring protocols based on a patient's risk of deterioration and link these to nursing workload and economic impact.

Design

Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders.

Setting and participants

Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations.

Results

Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a 'round', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation.

Conclusions

We explored several different scenarios with our stakeholders (clinicians and patients), based on how 'risk' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient's risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used.

Study registration

This study is registered as ISRCTN10863045.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.

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.

Causes, Diagnostic Testing, and Treatments Related to Clinical Deterioration Events among High-Risk Ward Patients

OBJECTIVE

Timely intervention for clinically deteriorating ward patients requires that care teams accurately diagnose and treat their underlying medical conditions. However, the most common diagnoses leading to deterioration and the relevant therapies provided are poorly characterized. Therefore, we aimed to determine the diagnoses responsible for clinical deterioration, the relevant diagnostic tests ordered, and the treatments administered among high-risk ward patients using manual chart review.

DESIGN

Multicenter retrospective observational study.

SETTING

Inpatient medical-surgical wards at four health systems from 2006-2020 PATIENTS: Randomly selected patients (1,000 from each health system) with clinical deterioration, defined by reaching the 95th percentile of a validated early warning score, electronic Cardiac Arrest Risk Triage (eCART), were included.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Clinical deterioration was confirmed by a trained reviewer or marked as a false alarm if no deterioration occurred for each patient. For true deterioration events, the condition causing deterioration, relevant diagnostic tests ordered, and treatments provided were collected. Of the 4,000 included patients, 2,484 (62%) had clinical deterioration confirmed by chart review. Sepsis was the most common cause of deterioration (41%; n=1,021), followed by arrhythmia (19%; n=473), while liver failure had the highest in-hospital mortality (41%). The most common diagnostic tests ordered were complete blood counts (47% of events), followed by chest x-rays (42%), and cultures (40%), while the most common medication orders were antimicrobials (46%), followed by fluid boluses (34%), and antiarrhythmics (19%).

CONCLUSIONS

We found that sepsis was the most common cause of deterioration, while liver failure had the highest mortality. Complete blood counts and chest x-rays were the most common diagnostic tests ordered, and antimicrobials and fluid boluses were the most common medication interventions. These results provide important insights for clinical decision-making at the bedside, training of rapid response teams, and the development of institutional treatment pathways for clinical deterioration.

KEY POINTS

Question: What are the most common diagnoses, diagnostic test orders, and treatments for ward patients experiencing clinical deterioration? Findings: In manual chart review of 2,484 encounters with deterioration across four health systems, we found that sepsis was the most common cause of clinical deterioration, followed by arrythmias, while liver failure had the highest mortality. Complete blood counts and chest x-rays were the most common diagnostic test orders, while antimicrobials and fluid boluses were the most common treatments. Meaning: Our results provide new insights into clinical deterioration events, which can inform institutional treatment pathways, rapid response team training, and patient care.

Surveillance and patient safety in nursing research: A bibliometric analysis from 1993 to 2023

AIMS

To identify and characterize the thematic foci, structure and evolution of nursing research on surveillance and patient safety.

DESIGN

Bibliometric analysis.

METHODS

Bibliometric methods were employed to analyse 1145 articles, using Bibliometrix and VOSviewer software.

DATA SOURCE

The Scopus bibliographic database was searched on April 7, 2023.

RESULTS

A keyword co-occurrence analysis found the most frequently occurring keywords to be: patient safety, nursing, nurses, adverse events, monitoring, critical care, quality improvement, vital signs, safety, alarm fatigue, education, nursing care, surveillance, clinical alarms, failure to rescue, evidence-based practice, acute care, clinical deterioration, communication, intensive care. Network mapping, clustering and time-tracking of the keywords revealed the focal themes, structure and evolution of the research field.

CONCLUSION

By assessing critical areas of the nursing research field, this study extends and enriches the current discourse on surveillance and patient safety for nursing researchers and practitioners. Critical challenges still have to be met by nurses, however, including the failure to rescue deteriorating patients. Further knowledge and understanding of surveillance and patient safety must be successfully translated from research to practice.

IMPLICATIONS FOR THE PROFESSION

This study highlights the gaps in nursing knowledge with regard to surveillance and patient safety and encourages nursing professionals to turn to evidence-based surveillance practices.

IMPACT

In addressing the problem of surveillance and its effect on patient safety, this study found that, in most clinical care settings, preventing failures to rescue and adverse patient outcomes still remains a challenge for the nursing profession. This study should have an impact on nursing academics' future research themes and on nursing professionals' future clinical practices.

REPORTING METHOD

Relevant EQUATOR guidelines have been adhered to by employing recognized bibliometric reporting methods.

Night-time detection and response in relation to deteriorating inpatients: A scoping review

BACKGROUND

Although detection and response to clinical deterioration have been studied, the range and nature of studies focused on night-time clinical setting remain unclear.

AIM

This study aimed to identify and map existing research and findings concerning night-time detection and response to deteriorating inpatients in usual care or research settings.

STUDY DESIGN

A scoping review method was used. PubMed, CINAHL, Web of Science, and Ichushi-Web databases were systematically searched. We included studies focusing on night-time detection and response to clinical deterioration.

RESULTS

Twenty-eight studies were included. These studies were organized into five categories: night-time medical emergency team or rapid response team (MET/RRT) response, night-time observation using the early warning score (EWS), available resources for physicians' practice, continuous monitoring of specific parameters, and screening for night-time clinical deterioration. The first three categories were related to interventional measures in usual care settings, and relevant findings mainly demonstrated the actual situation and challenges of night-time practice. The final two categories were related to the interventions in the research settings and included innovative interventions to identify at-risk or deteriorating patients.

CONCLUSIONS

Systematic interventional measures, such as MET/RRT and EWS, could have been sub-optimally performed at night. Innovations in monitoring technologies or implementation of predictive models could be helpful in improving the detection of night-time deterioration.

RELEVANCE TO CLINICAL PRACTICE

This review provides a compilation of current evidence regarding night-time practice concerning patient deterioration. However, a lack of understanding exists on specific and effective practices regarding timely action for deteriorating patients at night.

Missing data imputation techniques for wireless continuous vital signs monitoring

Wireless vital signs sensors are increasingly used for remote patient monitoring, but data analysis is often challenged by missing data periods. This study explored the performance of various imputation techniques for continuous vital signs measurements. Wireless vital signs measurements (heart rate, respiratory rate, blood oxygen saturation, axillary temperature) from surgical ward patients were used for repeated random simulation of missing data periods (gaps) of 5-60 min in two-hour windows. Gaps were imputed using linear interpolation, spline interpolation, last observation- and mean carried forwards technique, and cluster-based prognosis. Imputation performance was evaluated using the mean absolute error (MAE) between original and imputed gap samples. Besides, effects on signal features (window's slope, mean) and early warning scores (EWS) were explored. Gaps were simulated in 1743 data windows, obtained from 52 patients. Although MAE ranges overlapped, median MAE was structurally lowest for linear interpolation (heart rate: 0.9-2.6 beats/min, respiratory rate: 0.8-1.8 breaths/min, temperature: 0.04-0.17 °C, oxygen saturation: 0.3-0.7% for 5-60 min gaps) but up to twice as high for other techniques. Three techniques resulted in larger ranges of signal feature bias compared to no imputation. Imputation led to EWS misclassification in 1-8% of all simulations. Imputation error ranges vary between imputation techniques and increase with gap length. Imputation may result in larger signal feature bias compared to performing no imputation, and can affect patient risk assessment as illustrated by the EWS. Accordingly, careful implementation and selection of imputation techniques is warranted.

Prospective, multicenter validation of the deep learning-based cardiac arrest risk management system for predicting in-hospital cardiac arrest or unplanned intensive care unit transfer in patients admitted to general wards

BACKGROUND

Retrospective studies have demonstrated that the deep learning-based cardiac arrest risk management system (DeepCARS™) is superior to the conventional methods in predicting in-hospital cardiac arrest (IHCA). This prospective study aimed to investigate the predictive accuracy of the DeepCARS™ for IHCA or unplanned intensive care unit transfer (UIT) among general ward patients, compared with that of conventional methods in real-world practice.

METHODS

This prospective, multicenter cohort study was conducted at four teaching hospitals in South Korea. All adult patients admitted to general wards during the 3-month study period were included. The primary outcome was predictive accuracy for the occurrence of IHCA or UIT within 24 h of the alarm being triggered. Area under the receiver operating characteristic curve (AUROC) values were used to compare the DeepCARS™ with the modified early warning score (MEWS), national early warning Score (NEWS), and single-parameter track-and-trigger systems.

RESULTS

Among 55,083 patients, the incidence rates of IHCA and UIT were 0.90 and 6.44 per 1,000 admissions, respectively. In terms of the composite outcome, the AUROC for the DeepCARS™ was superior to those for the MEWS and NEWS (0.869 vs. 0.756/0.767). At the same sensitivity level of the cutoff values, the mean alarm counts per day per 1,000 beds were significantly reduced for the DeepCARS™, and the rate of appropriate alarms was higher when using the DeepCARS™ than when using conventional systems.

CONCLUSION

The DeepCARS™ predicts IHCA and UIT more accurately and efficiently than conventional methods. Thus, the DeepCARS™ may be an effective screening tool for detecting clinical deterioration in real-world clinical practice. Trial registration This study was registered at ClinicalTrials.gov ( NCT04951973 ) on June 30, 2021.

Early Warning Scores to Support Continuous Wireless Vital Sign Monitoring for Complication Prediction in Patients on Surgical Wards: Retrospective Observational Study

BACKGROUND

Wireless vital sign sensors are increasingly being used to monitor patients on surgical wards. Although early warning scores (EWSs) are the current standard for the identification of patient deterioration in a ward setting, their usefulness for continuous monitoring is unknown.

OBJECTIVE

This study aimed to explore the usability and predictive value of high-rate EWSs obtained from continuous vital sign recordings for early identification of postoperative complications and compares the performance of a sensor-based EWS alarm system with manual intermittent EWS measurements and threshold alarms applied to individual vital sign recordings (single-parameter alarms).

METHODS

Continuous vital sign measurements (heart rate, respiratory rate, blood oxygen saturation, and axillary temperature) collected with wireless sensors in patients on surgical wards were used for retrospective simulation of EWSs (sensor EWSs) for different time windows (1-240 min), adopting criteria similar to EWSs based on manual vital signs measurements (nurse EWSs). Hourly sensor EWS measurements were compared between patients with (event group: 14/46, 30%) and without (control group: 32/46, 70%) postoperative complications. In addition, alarms were simulated for the sensor EWSs using a range of alarm thresholds (1-9) and compared with alarms based on nurse EWSs and single-parameter alarms. Alarm performance was evaluated using the sensitivity to predict complications within 24 hours, daily alarm rate, and false discovery rate (FDR).

RESULTS

The hourly sensor EWSs of the event group (median 3.4, IQR 3.1-4.1) was significantly higher (P<.004) compared with the control group (median 2.8, IQR 2.4-3.2). The alarm sensitivity of the hourly sensor EWSs was the highest (80%-67%) for thresholds of 3 to 5, which was associated with alarm rates of 2 (FDR=85%) to 1.2 (FDR=83%) alarms per patient per day respectively. The sensitivity of sensor EWS-based alarms was higher than that of nurse EWS-based alarms (maximum=40%) but lower than that of single-parameter alarms (87%) for all thresholds. In contrast, the (false) alarm rates of sensor EWS-based alarms were higher than that of nurse EWS-based alarms (maximum=0.6 alarm/patient/d; FDR=80%) but lower than that of single-parameter alarms (2 alarms/patient/d; FDR=84%) for most thresholds. Alarm rates for sensor EWSs increased for shorter time windows, reaching 70 alarms per patient per day when calculated every minute.

CONCLUSIONS

EWSs obtained using wireless vital sign sensors may contribute to the early recognition of postoperative complications in a ward setting, with higher alarm sensitivity compared with manual EWS measurements. Although hourly sensor EWSs provide fewer alarms compared with single-parameter alarms, high false alarm rates can be expected when calculated over shorter time spans. Further studies are recommended to optimize care escalation criteria for continuous monitoring of vital signs in a ward setting and to evaluate the effects on patient outcomes.

Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making

The emergency department (ED) is a fast-paced environment responsible for large volumes of patients with varied disease acuity. Operational pressures on EDs are increasing, which creates the imperative to efficiently identify patients at imminent risk of acute deterioration. The aim of this study is to systematically compare the performance of machine learning algorithms based on logistic regression, gradient boosted decision trees, and support vector machines for predicting imminent clinical deterioration for patients based on cross-sectional patient data extracted from electronic patient records (EPR) at the point of entry to the hospital. We apply state-of-the-art machine learning methods to predict early patient deterioration, based on their first recorded vital signs, observations, laboratory results, and other predictors documented in the EPR. Clinical deterioration in this study is measured by in-hospital mortality and/or admission to critical care. We build on prior work by incorporating interpretable machine learning and fairness-aware modelling, and use a dataset comprising 118, 886 unplanned admissions to Salford Royal Hospital, UK, to systematically compare model variations for predicting mortality and critical care utilisation within 24 hours of admission. We compare model performance to the National Early Warning Score 2 (NEWS2) and yield up to a 0.366 increase in average precision, up to a [Formula: see text] reduction in daily alert rate, and a median 0.599 reduction in differential bias amplification across the protected demographics of age and sex. We use Shapely Additive exPlanations to justify the models' outputs, verify that the captured data associations align with domain knowledge, and pair predictions with the causal context of each patient's most influential characteristics. Introducing our modelling to clinical practice has the potential to reduce alert fatigue and identify high-risk patients with a lower NEWS2 that might be missed currently, but further work is needed to trial the models in clinical practice. We encourage future research to follow a systematised approach to data-driven risk modelling to obtain clinically applicable support tools.

Modifications to rapid response team (medical emergency team) activation criteria and its impact on patient safety

BACKGROUND

Modifications to rapid response team (RRT) activation criteria occur commonly in Australian hospitals without evidence to define their use.

AIMS

To evaluate the effectiveness of RRT activation criteria modifications in preventing RRT activation and differences in adverse events associated with treatment delays caused by modifications.

METHODS

A prospective chart audit of hospital patients with RRT activation criteria modifications admitted during a 12-month period in a large regional hospital in Toowoomba, Australia. The incidence of RRT activation criteria modifications, RRT activations and rates of adverse events following criteria modifications were investigated. Adverse events were defined as a delayed treatment on the ward, unplanned intensive care unit admission, cardiac arrest and unexpected death. Differences in patient outcomes among medical and surgical patients were also investigated.

RESULTS

A total of 271 patients out of 4009 admitted patients had modifications to their RRT activation criteria. There was no difference in rates of RRT activation in patients with modified criteria compared with patients with unmodified criteria (P = 0.37). In patients with RRT activation criteria modifications, rates of adverse events were higher in patients who met their modified RRT criteria (93.3%) compared with those who did not meet modified RRT criteria (3.8%; P < 0.001). Additionally, in patients with modifications, rates of adverse events were higher in medical patients (27.6%; n = 50) compared with surgical patients (15.6%; n = 14; P = 0.03).

CONCLUSIONS

The results strongly suggest that RRT criteria modification is associated with no difference in rates of RRT activation and with detrimental impacts on patient safety, particularly in medical patients.

Value of improving patient safety: health economic considerations for rapid response systems-a rapid review of the literature and expert round table

OBJECTIVES

Failure to rescue deteriorating patients in hospital is a well-researched topic. We aimed to explore the impact of safer care on health economic considerations for clinicians, providers and policymakers.

DESIGN

We undertook a rapid review of the available literature and convened a round table of international specialists in the field including experts on health economics and value-based healthcare to better understand health economics of clinical deterioration and impact of systems to reduce failure to rescue.

RESULTS

Only a limited number of publications have examined the health economic impact of failure to rescue. Literature examining this topic lacked detail and we identified no publications on long-term cost outside the hospital following a deterioration event. The recent pandemic has added limited literature on prevention of deterioration in the patients' home.Cost-effectiveness and cost-efficiency are dependent on broader system effects of adverse events. We suggest including the care needs beyond the hospital and loss of income of patients and/or their informal carers as well as sickness of healthcare staff exposed to serious adverse events in the analysis of adverse events. They are likely to have a larger health economic impact than the direct attributable cost of the hospital admission of the patient suffering the adverse event. Premorbid status of a patient is a major confounder for health economic considerations.

CONCLUSION

In order to optimise health at the population level, we must limit long-term effects of adverse events through improvement of our ability to rapidly recognise and respond to acute illness and worsening chronic illness both in the home and the hospital.

The Effect of Continuous Versus Periodic Vital Sign Monitoring on Disease Severity of Patients with an Unplanned ICU Transfer

Continuous vital sign monitoring (CM) may detect ward patient's deterioration earlier than periodic monitoring. This could result in timely ICU transfers or in a transfer delay due to misperceived higher level of care on the ward. The primary objective of this study was to compare patient's disease severity upon unplanned ICU transfer, before and after CM implementation. We included a one-year period before and after CM implementation between August 1, 2017 - July 31, 2019. Before implementation, surgical and internal medicine patients' vital signs were periodically monitored, compared to continuous monitoring with wireless linkage to hospital systems after implementation. In both periods the same early warning score (EWS) protocol was in place. Primary outcome was disease severity scores upon ICU transfer. Secondary outcomes were ICU and hospital length of stay, incidence of mechanical ventilation and ICU mortality. In the two one-year periods 93 and 59 unplanned ICU transfer episodes were included, respectively. Median SOFA (3 (2-6) vs 4 (2-7), p = .574), APACHE II (17 (14-20) vs 16 (14-21), p = .824) and APACHE IV (59 (46-67) vs 50 (36-65), p = .187) were comparable between both periods, as were the median ICU LOS (3.0 (1.7-5.8) vs 3.1 (1.6-6.1), p.962), hospital LOS (23.6 (11.5-38.0) vs 19 (13.9-39.2), p = .880), incidence of mechanical ventilation (28 (47%) vs 22 (54%), p.490), and ICU mortality (11 (13%) vs 10 (19%), p.420). This study shows no difference in disease severity upon unplanned ICU transfer after CM implementation for patients who have deteriorated on the ward.

Balancing responsibilities, rewards and challenges: A qualitative study illuminating the complexity of being a rapid response team nurse

AIM AND OBJECTIVE

To explore Rapid Response Team nurses' perceptions of what it means being a Rapid Response Team nurse including their perceptions of the collaborative and organisational aspects of the rapid response team (RRT).

BACKGROUND

For more than 20 years, RRT nurses have been on the frontline of critical situations in acute care hospitals. However, a few studies report nurses' perceptions of their role as RRT nurses, including collaboration with general ward nurses and physicians. This knowledge is important to guide development and adjustment of the RRT to benefit both patients' safety and team members' job satisfaction.

DESIGN

Qualitative focus group interviews.

METHODS

A qualitative approach was applied. Throughout 2018 and across three regions and three acute care settings in Denmark, eight focus group interviews were conducted in which 27 RRT nurses participated. Transcribed interviews were analysed using inductive content analysis. Reporting of this study followed the COREQ checklist.

RESULTS

One overarching theme 'Balancing responsibilities, rewards, and challenges' was derived, comprising six categories: 'Becoming, developing and fulfilling the RRT nurse role', 'Helping patients as the core function of RRT', 'The RRT-call at its best', 'The obvious and the subtle RRT tasks', 'Carrying the burden of the RRT', and 'Organisational benefits and barriers for an optimal RRT'.

CONCLUSION

Being a RRT nurse is a complex task. Nurses experience professional satisfaction and find it meaningful helping deteriorating patients. The inadequate resources available to train general ward staff how to manage basic clinical tasks are an added stress to nurses.

RELEVANCE TO CLINICAL PRACTICE

Organisational managers need a better understanding of the necessary staffing requirements to attend patients' needs, train staff and handle the increasing acuity of ward patients. Failure to do so will be detrimental to patient outcomes and compromise RRT nurses' job satisfaction.

Advantage of Vital Sign Monitoring Using a Wireless Wearable Device for Predicting Septic Shock in Febrile Patients in the Emergency Department: A Machine Learning-Based Analysis

Intermittent manual measurement of vital signs may not rapidly predict sepsis development in febrile patients admitted to the emergency department (ED). We aimed to evaluate the predictive performance of a wireless monitoring device that continuously measures heart rate (HR) and respiratory rate (RR) and a machine learning analysis in febrile but stable patients in the ED. We analysed 468 patients (age, ≥18 years; training set, n = 277; validation set, n = 93; test set, n = 98) having fever (temperature >38 °C) and admitted to the isolation care unit of the ED. The AUROC of the fragmented model with device data was 0.858 (95% confidence interval [CI], 0.809−0.908), and that with manual data was 0.841 (95% CI, 0.789−0.893). The AUROC of the accumulated model with device data was 0.861 (95% CI, 0.811−0.910), and that with manual data was 0.853 (95% CI, 0.803−0.903). Fragmented and accumulated models with device data detected clinical deterioration in febrile patients at risk of septic shock 9 h and 5 h 30 min earlier, respectively, than those with manual data. Continuous vital sign monitoring using a wearable device could accurately predict clinical deterioration and reduce the time to recognise potential clinical deterioration in stable ED patients with fever.

Understanding the use of the National Early Warning Score 2 in acute care settings: a realist review protocol

INTRODUCTION

Failure to recognise and respond to patient deterioration in an appropriate and timely manner has been highlighted as a global patient safety concern. Early Warning Scores (EWSs) using vital signs were introduced to address this concern, with the aim of getting the patient timely and appropriate treatment. The National Early Warning Score 2 (NEWS2) is in use across the NHS, and many other settings globally. While patient improvements have been shown, research has identified that the NEWS2 is not always used as intended. Therefore, this review will use a realist approach to understand what the mechanisms are that influence appropriate use (or not) of the NEWS2 in acute care settings, how, for whom and in which contexts. The findings will inform clinicians of what helps and/or hinders appropriate use of the NEWS2 in clinical practice, thus helping to facilitate successful implementation.

METHODS AND ANALYSIS

Our realist review will follow Pawson's iterative six step process: (1) Development of initial programme theory. (2) Searching the literature; an information scientist will develop, pilot and refine the search strategy. A systematic search will be completed, based on subject relevancy on the following databases: Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline, Embase (OvidSP), Web of Science (Science Citation Index and Social Science Citation), Cochrane Database of Systematic Reviews, Joanna Briggs Institute, Ethos, Proquest Dissertations and Theses Global, and Google Scholar for documents dating from 1997 (date of the first published EWS) to present. To retrieve additional relevant data 'snowballing' (finding references and authors by hand, contacting authors, searching reference lists and citation-tracking using Google Scholar) will be used. Inclusion criteria include all documents (including grey literature) that relate to the use of EWSs/NEWS2 in the English language only. Documents set in the paediatric, maternity and primary care settings will be excluded. (3) Selecting documents and quality appraisal. (4) Extracting and organising the data. (5) Synthesising the data. (6) Disseminating the findings. We will recruit a group of stakeholders comprised of experienced clinicians who use the NEWS2 as part of their clinical practice to provide feedback throughout the review. Step 1 has already begun with the development of an initial programme theory. This initial programme theory presents how the NEWS2 is supposed to work (or not), it will now be developed, tested and refined.

ETHICS AND DISSEMINATION

Ethical approval is not required for this study as it is secondary research. Dissemination will include a peer-reviewed publication and conference presentations. Findings will also be amplified through social media platforms with user friendly summaries. Our stakeholder group will also contribute to dissemination of findings in their clinical areas and among existing networks.

PROSPERO REGISTRATION NUMBER

CRD42022304497.

Upcoming and urgent challenges in critical care research based on COVID-19 pandemic experience

While the coronavirus disease 2019 (COVID-19) pandemic placed a heavy burden on healthcare systems worldwide, it also induced urgent mobilisation of research teams to develop treatments preventing or curing the disease and its consequences. It has, therefore, challenged critical care research to rapidly focus on specific fields while forcing critical care physicians to make difficult ethical decisions. This narrative review aims to summarise critical care research -from organisation to research fields- in this pandemic setting and to highlight opportunities to improve research efficiency in the future, based on what is learned from COVID-19. This pressure on research revealed, i.e., i/ the need to harmonise regulatory processes between countries, allowing simplified organisation of international research networks to improve their efficiency in answering large-scale questions; ii/ the importance of developing translational research from which therapeutic innovations can emerge; iii/ the need for improved triage and predictive scores to rationalise admission to the intensive care unit. In this context, key areas for future critical care research and better pandemic preparedness are artificial intelligence applied to healthcare, characterisation of long-term symptoms, and ethical considerations. Such collaborative research efforts should involve groups from both high and low-to-middle income countries to propose worldwide solutions. As a conclusion, stress tests on healthcare organisations should be viewed as opportunities to design new research frameworks and strategies. Worldwide availability of research networks ready to operate is essential to be prepared for next pandemics. Importantly, researchers and physicians should prioritise realistic and ethical goals for both clinical care and research.

Outcomes of Vital Sign Monitoring of an Acute Surgical Cohort With Wearable Sensors and Digital Alerting Systems: A Pragmatically Designed Cohort Study and Propensity-Matched Analysis

Background: The implementation and efficacy of wearable sensors and alerting systems in acute secondary care have been poorly described.

Objectives: to pragmatically test one such system and its influence on clinical outcomes in an acute surgical cohort.

Methods: In this pragmatically designed, pre-post implementation trial, participants admitted to the acute surgical unit at our institution were recruited. In the pre-implementation phase (September 2017 to May 2019), the SensiumVitals™ monitoring system, which continuously measures temperature, heart, and respiratory rates, was used for monitoring alongside usual care (intermittent monitoring in accordance with the National Early Warning Score 2 [NEWS 2] protocol) without alerts being generated. In the post-implementation phase (May 2019 to March 2020), alerts were generated when pre-established thresholds for vital parameters were breached, requiring acknowledgement from healthcare staff on provided mobile devices. Hospital length of stay, intensive care use, and 28-days mortality were measured. Balanced cohorts were created with 1:1 ‘optimal’ propensity score logistic regression models.

Results: The 1:1 matching method matched the post-implementation group (n = 141) with the same number of subjects from the pre-implementation group (n = 141). The median age of the entire cohort was 52 (range: 18–95) years and the median duration of wearing the sensor was 1.3 (interquartile range: 0.7–2.0) days. The median alert acknowledgement time was 111 (range: 1–2,146) minutes. There were no significant differences in critical care admission (planned or unplanned), hospital length of stay, or mortality.

Conclusion: This study offered insight into the implementation of digital health technologies within our institution. Further work is required for optimisation of digital workflows, particularly given their more favourable acceptability in the post pandemic era. Clinical trials registration information: ClinicalTrials.gov Identifier: NCT04638738.

Wearables alone will not eliminate failure to rescue

Surveys suggest that anaesthesiologists believe that continuous monitoring with wearables will lead to improved patient outcomes. However, evidence suggests that several critical factors, including timely recognition of physiological problems, the presence of a trained team to respond to the alerts, and that the alerts occur far in advance of the deterioration, are required before overall improvement can occur. Wearables alone will not change patients' outcomes, they must be implemented as part of a system change that takes advantage of the higher frequency observations that continuous monitoring provides.

Rapid response teams-how and who? A protocol for a randomised clinical trial evaluating the composition of the efferent limb of the rapid response system

BACKGROUND

Many patients experiencing deterioration have documented deviation of vital signs prior to the deterioration event. Increasing focus on these patients led to the rapid response systems and their configuration with afferent and efferent limbs. The two most prevalent team constellations in the efferent limb are the medical emergency team (MET), usually led by a doctor, and the critical care outreach team (CCOT), usually led by a nurse. The two constellations have not previously been examined in a comparative clinical trial.

METHODS

This is a single centre non-inferiority randomised controlled trial of MET vs CCOT. All patients will be randomised at the time of the call. The intervention group will be the critical care outreach team. The primary outcome is mortality at 30 days and the occurrence of serious adverse events. All patients will be followed for 90 days. We aim to detect or reject a change of 7% in mortality whilst accepting a type I error of 5 and type II error of 20, using a sample size of maximum of 2000 individual patients.

DISCUSSION

There is evidence supporting a benefit for the patient when using rapid response systems; however, earlier randomised studies are marked by cross-contamination and selection bias. Previous studies have primarily examined the effect of RRS on hospital cardiac arrests (IHCA) and mortality. Our study will be examining the effect on intensive care unit admissions as well as the ICHA and mortality.

CONCLUSION

This study may highlight potential benefits of specific configurations of rapid response systems and their impact on safety outcomes.

Reducing ICU Utilization, Length of Stay, and Cost by Optimizing the Clinical Use of Continuous Monitoring System Technology in the Hospital

BACKGROUND

Continuous monitoring system technology (CMST) aids in earlier detection of deterioration of hospitalized patients, but whether improved outcomes are sustainable is unknown.

METHODS

This interrupted time series evaluation explored whether optimized clinical use of CMST was associated with sustained improvement in intensive care unit (ICU) utilization, hospital length of stay, cardiac arrest rates, code blue events, mortality, and cost across multiple adult acute care units.

RESULTS

A total of 20,320 patients in the postoptimized use cohort compared with 16,781 patients in the preoptimized use cohort had a significantly reduced ICU transfer rate (1.73% vs 2.25%, P = .026) corresponding to 367.11 ICU days saved over a 2-year period, generating an estimated cost savings of more than $2.3 million. Among patients who transferred to the ICU, hospital length of stay was decreased (8.37 vs 9.64 days, P = .004). Cardiac arrest, code blue, and mortality rates did not differ significantly.

CONCLUSION

Opportunities exist to promote optimized adoption and use of CMST at acute care facilities to sustainably improve clinical outcomes and reduce cost.

Automated alert and activation of medical emergency team using early warning score

Background

Timely recognition of warning signs from deteriorating patients and proper treatment are important in improving patient safety. In comparison to the traditional medical emergency team (MET) activation triggered by phone calls, automated activation of MET may minimize activation delays. However, limited data are available on the effects of automated activation systems on the time from derangement to MET activation and on clinical outcomes. The objective of this study was to determine the impact of an automated alert and activation system for MET on clinical outcomes in unselected hospitalized patients.

Methods

This is an observational study using prospectively collected data from consecutive patients managed by the MET at a university-affiliated, tertiary hospital from March 2013 to December 2019. The automated alert system automatically calculates the Modified Early Warning Score (MEWS) and subsequently activates MET when the MEWS score is 7 or higher, which was implemented since August 2016. The outcome measures of interest including hospital mortality in patients with MEWS of 7 or higher were compared between pre-implementation and post-implementation groups of the automated alert and activation system in the primary analysis. The association between the implementation of the system and hospital mortality was evaluated with logistic regression analysis.

Results

Of the 7678 patients who were managed by MET during the study period, 639 patients during the pre-implementation period and 957 patients during the post-implementation period were included in the primary analysis. MET calls due to abnormal physiological variables were more common during the pre-implementation period, while MET calls due to medical staff’s worries or concern about the patient’s condition were more common during the post-implementation period. The median time from deterioration to MET activation was significantly shortened in the post-implementation period compared to the pre-implementation period (34 min vs. 60 min, P < 0.001). In addition, unplanned ICU admission rates (41.2% vs. 71.8%, P < 0.001) was reduced during the post-implementation period. Hospital mortality was decreased after implementation of the automated alert system (27.2% vs. 38.5%, P < 0.001). The implementation of the automated alert and activation system was associated with decreased risk of death in the multivariable analysis (adjusted OR 0.73, 95% CI 0.56–0.90).

Conclusions

After implementing an automated alert and activation system, the time from deterioration to MET activation was shortened and clinical outcomes were improved in hospitalized patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40560-021-00588-y.

Situation awareness and the mitigation of risk associated with patient deterioration: A meta-narrative review of theories and models and their relevance to nursing practice

BACKGROUND

Accurate situation awareness has been identified as a critical component of effective deteriorating patient response systems and an essential patient safety skill for nursing practice. However, situation awareness has been defined and theorised from multiple perspectives to explain how individuals, teams and systems maintain awareness in dynamic task environments.

AIM

Our aim was to critically analyse the different approaches taken to the study of situation awareness in healthcare and explore the implications for nursing practice and research as it relates to clinical deterioration in ward contexts.

METHODS

We undertook a meta-narrative review of the healthcare literature to capture how situation awareness has been defined, theorised and studied in healthcare. Following an initial scoping review, we conducted an extensive search of ten electronic databases and included any theoretical, empirical or critical papers with a primary focus on situation awareness in an inpatient hospital setting. Included papers were collaboratively categorised in accordance with their theoretical framing, research tradition and paradigm with a narrative review presented.

RESULTS

A total of 120 papers were included in this review. Three overarching narratives reflecting philosophical, patient safety and solution focussed framings of situation awareness and seven meta-narratives were identified as follows: individual, team and systems perspectives of situation awareness (meta-narratives 1-3), situation awareness and patient safety (meta-narrative 4), communication tools, technologies and education to support situation awareness (meta-narratives 5-7). We identified a concentration of literature from anaesthesia and operating rooms and a body of research largely located within a cognitive engineering tradition and a positivist research paradigm. Endsley's situation awareness model was applied in over 80% of the papers reviewed. A minority of papers drew on alternative situation awareness theories including constructivist, collaborative and distributed perspectives.

CONCLUSIONS

Nurses have a critical role in identifying and escalating the care of deteriorating patients. There is a need to build on prior studies and reflect on the reality of nurse's work and the constraints imposed on situation awareness by the demands of busy inpatient wards. We suggest that this will require an analysis that complements but goes beyond the dominant cognitive engineering tradition to reflect the complex socio-cultural reality of ward-based teams and to explore how situation awareness emerges in increasingly complex, technologically enabled distributed healthcare systems.

A new situation awareness model decreases clinical deterioration in the emergency departments-A controlled intervention study

BACKGROUND

Studies have suggested that adding subjective parameters to early warning score (EWS) systems might prompt more proactive treatment and positively affect clinical outcomes. Hence, the study aimed to investigate effect of a situation awareness model consisting of objective and subjective parameters on clinical deterioration in adult emergency department (ED) patients.

METHODS

This controlled pre-and-post interventional study was carried out in July-December 2016 and November 2017-April 2018. In ED patients ≥ 18 years, we examined if a situation awareness model compared with a conventional EWS system could reduce clinical deterioration. The new model consisted of a regional EWS, combined with skin observation, clinical concern and patients' and relatives' concerns, pain, dyspnea, and team risk assessment. Clinical deterioration was defined as change in vital signs requiring increased observation or physician assessment, that is, increase in early warning score from either 0 or 1 to score ≥2 or an increase from score ≥2 and above. Secondary outcomes were mortality, intensive care unit (ICU) admissions, and readmissions.

RESULTS

We included 34 556 patients. Patients with two or more registered EWS were included in the primary analysis (N = 21 839). Using difference-in-difference regression, we found a reduced odds of clinical deterioration of 21% (OR 0.79 95% CI [0.69; 0.90]) in the intervention groups compared with controls. No impact on mortality, ICU, or readmissions was found.

CONCLUSION

The situation awareness model reduces odds of clinical deterioration, defined as a clinically relevant increase in EWS, in an unselected adult population of ED patients. However, there was no effect on secondary outcomes.

Optimizing Situation Awareness to Reduce Emergency Transfers in Hospitalized Children

BACKGROUND AND OBJECTIVES

Interventions to improve care team situation awareness (SA) are associated with reduced rates of unrecognized clinical deterioration in hospitalized children. By addressing themes from recent safety events and emerging corruptors to SA in our system, we aimed to decrease emergency transfers (ETs) to the ICU by 50% over 10 months.

METHODS

An interdisciplinary team of physicians, nurses, respiratory therapists, and families convened to improve the original SA model for clinical deterioration and address communication inadequacies and evolving technology in our inpatient system. The key drivers included the establishment of a shared mental model, psychologically safe escalation, and efficient and effective SA tools. Novel interventions including the intentional inclusion of families and the interdisciplinary team in huddles, a mental model checklist, door signage, and an electronic health record SA navigator were evaluated via a time series analysis. Sequential inpatient-wide testing of the model allowed for iteration and consensus building across care teams and families. The primary outcome measure was ETs, defined as any ICU transfer in which the patient receives intubation, inotropes, or ≥3 fluid boluses within 1 hour.

RESULTS

The rate of ETs per 10 000 patient-days decreased from 1.34 to 0.41 during the study period. This coincided with special cause improvement in process measures, including risk recognition before medical response team activation and the use of tools to facilitate shared SA.

CONCLUSIONS

An innovative, proactive, and reliable process to predict, prevent, and respond to clinical deterioration was associated with a nearly 70% reduction in ETs.

The global elements of vital signs' assessment: a guide for clinical practice

The assessment of vital signs is critical for safe, high-quality care. Vital signs' data provide valuable insight into the patient's condition, including how they are responding to medical treatment and, importantly, whether the patient is deteriorating. Although abnormal vital signs have been associated with poor clinical outcomes, research has consistently found that vital signs' assessment is often neglected in clinical practice. Factors contributing to this include nurses' knowledge, clinical judgement, culture, tradition and workloads. To emphasise the importance of vital signs' assessment, global elements of vital signs' assessment are proposed. The elements reflect key principles underpinning vital signs' assessment and are informed by evidence-based literature.

Characterizing rescue performance in a tertiary care medical center: a systems approach to provide management decision support

Background

Allocation of limited resources to improve quality, patient safety, and outcomes is a decision-making challenge health care leaders face every day. While much valuable health care management research has concentrated on administrative data analysis, this approach often falls short of providing actionable information essential for effective management of specific system implementations and complex systems. This comprehensive performance analysis of a hospital-wide system illustrates application of various analysis approaches to support understanding specific system behaviors and identify leverage points for improvement. The study focuses on performance of a hospital rescue system supporting early recognition and response to patient deterioration, which is essential to reduce preventable inpatient deaths.

Methods

Retrospective analysis of tertiary care hospital inpatient and rescue data was conducted using a systems analysis approach to characterize: patient demographics; rescue activation types and locations; temporal patterns of activation; and associations of patient factors, including complications, with post-rescue care disposition and outcomes.

Results

Increases in bedside consultations (20% per year) were found with increased rescue activations during periods of resource limitations and changes (e.g., shift changes, weekends). Cardiac arrest, respiratory failure, and sepsis complications present the highest risk for rescue and death. Distributions of incidence of rescue and death by day of patient stay may suggest opportunities for earlier recognition.

Conclusions

Specific findings highlight the potential of using rescue-related risk and targeted resource deployment strategies to improve early detection of deterioration. The approach and methods applied can be used by other institutions to understand performance and allow rational incremental improvements to complex care delivery systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06855-w.

Role of a rapid response system and code status discussion as determinants of prognosis for critical inpatients: An observational study in a Japanese urban hospital

Rapid response systems (RRS) have been introduced worldwide to reduce unpredicted in-hospital cardiac arrest (IHCA) and in-hospital mortality. The role of advance care planning (ACP) in the management of critical patients has not yet been fully determined in Japan.We retrospectively assessed the characteristics of all inpatients with unpredicted IHCA in our hospital between 2016 and 2018. Yearly changes in the number of RRS activations and the incidence of unpredicted IHCA with or without code status discussion were evaluated from 2014 to 2018. Hospital standardized mortality ratios were assessed from the data reported in the annual reports by the National Hospital Organization.A total of 81 patients (age: 70.9 ± 13.3 years) suffered an unpredicted IHCA and had multiple background diseases, including heart disease (75.3%), chronic kidney disease (25.9%), and postoperative status (cardiovascular surgery, 18.5%). Most of the patients manifested non-shockable rhythms (69.1%); survival to hospital discharge rate was markedly lower than that with shockable rhythms (26.8% vs 72.0%, P < .001). The hospital standardized mortality ratios was maintained nearly constant at approximately 50.0% for 3 consecutive years. The number of cases of RRS activation markedly increased from 75 in 2014 to 274 patients in 2018; conversely, the number of unpredicted IHCA cases was reduced from 40 in 2014 to 18 in 2018 (P < .001). Considering the data obtained in 2014 and 2015 as references, the RRS led to a reduction in the relative risk of unpredicted IHCA from 2016 to 2018 (ie, 0.618, 95% confidence interval 0.453-0.843). The reduction in unpredicted IHCA was attributed partly to the increased number of patients who had discussed the code status, and a significant correlation was observed between these parameters (R2 = 0.992, P < .001). The reduction in the number of patients with end-stage disease, including congestive heart failure and chronic renal failure, paralleled the incidence of unpredicted IHCA.Both RRS and ACP reduced the incidence of unpredicted IHCA; RRS prevents progression to unpredicted IHCA, whereas ACP decreases the number of patients with no code status discussion and thus potentially reducing the patient subgroup progressing to an unpredicted IHCA.

Using machine learning to improve the accuracy of patient deterioration predictions: Mayo Clinic Early Warning Score (MC-EWS)

OBJECTIVE

We aimed to develop a model for accurate prediction of general care inpatient deterioration.

MATERIALS AND METHODS

Training and internal validation datasets were built using 2-year data from a quaternary hospital in the Midwest. Model training used gradient boosting and feature engineering (clinically relevant interactions, time-series information) to predict general care inpatient deterioration (resuscitation call, intensive care unit transfer, or rapid response team call) in 24 hours. Data from a tertiary care hospital in the Southwest were used for external validation. C-statistic, sensitivity, positive predictive value, and alert rate were calculated for different cutoffs and compared with the National Early Warning Score. Sensitivity analysis evaluated prediction of intensive care unit transfer or resuscitation call.

RESULTS

Training, internal validation, and external validation datasets included 24 500, 25 784 and 53 956 hospitalizations, respectively. The Mayo Clinic Early Warning Score (MC-EWS) demonstrated excellent discrimination in both the internal and external validation datasets (C-statistic = 0.913, 0.937, respectively), and results were consistent in the sensitivity analysis (C-statistic = 0.932 in external validation). At a sensitivity of 73%, MC-EWS would generate 0.7 alerts per day per 10 patients, 45% less than the National Early Warning Score.

DISCUSSION

Low alert rates are important for implementation of an alert system. Other early warning scores developed for the general care ward have achieved lower discrimination overall compared with MC-EWS, likely because MC-EWS includes both nursing assessments and extensive feature engineering.

CONCLUSIONS

MC-EWS achieved superior prediction of general care inpatient deterioration using sophisticated feature engineering and a machine learning approach, reducing alert rate.

Implementation of Wearable Sensors and Digital Alerting Systems in Secondary Care: Protocol for a Real-World Prospective Study Evaluating Clinical Outcomes

BACKGROUND

Advancements in wearable sensors have caused a resurgence in their use, particularly because their miniaturization offers ambulatory advantages while performing continuous vital sign monitoring. Digital alerts can be generated following early recognition of clinical deterioration through breaches of set parameter thresholds, permitting earlier intervention. However, a systematic real-world evaluation of these alerting systems has yet to be conducted, and their efficacy remains unknown.

OBJECTIVE

The aim of this study is to implement wearable sensors and digital alerting systems in acute general wards to evaluate the resultant clinical outcomes.

METHODS

Participants on acute general wards will be screened and recruited into a trial with a pre-post implementation design. In the preimplementation phase, the SensiumVitals monitoring system, which continuously measures temperature, heart, and respiratory rates, will be used for monitoring alongside usual care. In the postimplementation phase, alerts will be generated from the SensiumVitals system when pre-established thresholds for vital parameters have been crossed, requiring acknowledgement from health care staff; subsequent clinical outcomes will be analyzed.

RESULTS

Enrolment is currently underway, having started in September 2017, and is anticipated to end shortly. Data analysis is expected to be completed in 2021.

CONCLUSIONS

This study will offer insight into the implementation of digital health technologies within a health care trust and aims to describe the effectiveness of wearable sensors for ambulatory continuous monitoring and digital alerts on clinical outcomes in acute general ward settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04638738; https://clinicaltrials.gov/ct2/show/NCT04638738.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/26240.

The pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV 2)

BACKGROUND

SARS-CoV-2 has ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters preceding an adverse event. Wearable sensors can measure vital signs continuously and remotely, outside of hospital facilities, recognising early clinical deterioration. We aim to determine the feasibility & acceptability of remote monitoring systems for quarantined individuals in a hotel suspected of COVID-19.

METHODS

A pilot, proof-of-concept, feasibility trial was conducted in engineered hotels near London airports (May-June 2020). Individuals arriving to London with mild suspected COVID-19 symptoms requiring quarantine, as recommended by Public Health England, or healthcare professionals with COVID-19 symptoms unable to isolate at home were eligible. The SensiumVitals™ patch, measuring temperature, heart & respiratory rates, was applied on arrival for the duration of their stay. Alerts were generated when pre-established thresholds were breeched; trained nursing staff could consequently intervene.

RESULTS

Fourteen individuals (M = 7, F = 7) were recruited; the mean age was 34.9 (SD 11) years. Mean length of stay was 3 (SD 1.8) days. In total, 10 vital alerts were generated across 4 participants, resulting in telephone contact, reassurance, or adjustment of the sensor. No individuals required hospitalisation or virtual general practitioner review.

DISCUSSION

This proof-of-concept trial demonstrated the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a pandemic at a hotel, acting as an extension to a healthcare trust. Benefits included reduced viral exposure to healthcare staff, with recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor.

CONCLUSION

Remote monitoring systems can be applied to hotels to deliver healthcare safely in individuals suspected of COVID-19. Further work is required to evaluate this model on a larger scale.

TRIAL REGISTRATION

Clinical trials registration information: ClinicalTrials.gov Identifier: NCT04337489 (07/04/2020).

Design of the pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV-2)

Background

The outbreak of SARS-CoV-2 (coronavirus, COVID-19), declared a pandemic by the World Health Organization (WHO), is a global health problem with ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters often preceding an adverse event. Wearable sensors can measure vital signs continuously (e.g. heart rate, respiratory rate, temperature) remotely and can be utilised to recognise early clinical deterioration.

Methods

We describe the protocol for a pilot, proof-of-concept, observational study to be conducted in an engineered hotel near London airports, UK. The study is set to continue for the duration of the pandemic. Individuals arriving to London with mild symptoms suggestive of COVID-19 or returning from high-risk areas requiring quarantine, as recommended by the Public Health England, or healthcare professionals with symptoms suggestive of COVID-19 unable to isolate at home will be eligible for a wearable patch to be applied for the duration of their stay. Notifications will be generated should deterioration be detected through the sensor and displayed on a central monitoring hub viewed by nursing staff, allowing for trend deterioration to be noted. The primary objective is to determine the feasibility of remote monitoring systems in detecting clinical deterioration for quarantined individuals in a hotel.

Discussion

This trial should prove the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a global pandemic at a hotel, acting as an extension to a healthcare trust. Potential benefits would include reducing infection risk of COVID-19 to healthcare staff, with earlier recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. We hope our results can power future, robust randomised trials.

Trial registration

ClinicalTrials.gov Identifier: NCT04337489.

Implementation of a paediatric early warning system as a complex health technology intervention

The national implementation groups of early warning systems in the UK and Ireland have identified a need to understand implementation, adoption and maintenance of these complex interventions. The literature on how to implement, scale, spread and sustain these systems is sparse. We describe a successful adoption and maintenance over 10 years of a paediatric early warning system as a sociotechnical intervention using the Nonadoption, Abandonment, Challenges to the Scale-Up, Spread, and Sustainability Framework for Health and Care Technologies. The requirement for iterative processes within environment, culture, policy, human action and the wider system context may explain the possible reasons for improved outcomes in small-scale implementation and meta-analyses that are not reported in multicentre randomised control trials of early warning systems.

The association between hospital length of stay before rapid response system activation and clinical outcomes: a retrospective multicenter cohort study

Background

Rapid response system (RRS) is being increasingly adopted to improve patient safety in hospitals worldwide. However, predictors of survival outcome after RRS activation because of unexpected clinical deterioration are not well defined. We investigated whether hospital length of stay (LOS) before RRS activation can predict the clinical outcomes.

Methods

Using a nationwide multicenter RRS database, we identified patients for whom RRS was activated during hospitalization at 9 tertiary referral hospitals in South Korea between January 1, 2016, and December 31, 2017. All information on patient characteristics, RRS activation, and clinical outcomes were retrospectively collected by reviewing patient medical records at each center. Patients were categorized into two groups according to their hospital LOS before RRS activation: early deterioration (LOS < 5 days) and late deterioration (LOS ≥ 5 days). The primary outcome was 28-day mortality and multivariable logistic regression was used to compare the two groups. In addition, propensity score-matched analysis was used to minimize the effects of confounding factors.

Results

Among 11,612 patients, 5779 and 5883 patients belonged to the early and late deterioration groups, respectively. Patients in the late deterioration group were more likely to have malignant disease and to be more severely ill at the time of RRS activation. After adjusting for confounding factors, the late deterioration group had higher 28-day mortality (aOR 1.60, 95% CI 1.44–1.77). Other clinical outcomes (in-hospital mortality and hospital LOS after RRS activation) were worse in the late deterioration group as well, and similar results were found in the propensity score-matched analysis (aOR for 28-day mortality 1.66, 95% CI 1.45–1.91).

Conclusions

Patients who stayed longer in the hospital before RRS activation had worse clinical outcomes. During the RRS team review of patients, hospital LOS before RRS activation should be considered as a predictor of future outcome.

Expectations of Continuous Vital Signs Monitoring for Recognizing Complications After Esophagectomy: Interview Study Among Nurses and Surgeons

Background

Patients undergoing esophagectomy are at serious risk of developing postoperative complications. To support early recognition of clinical deterioration, wireless sensor technologies that enable continuous vital signs monitoring in a ward setting are emerging.

Objective

This study explored nurses’ and surgeons’ expectations of the potential effectiveness and impact of continuous wireless vital signs monitoring in patients admitted to the ward after esophagectomy.

Methods

Semistructured interviews were conducted at 3 esophageal cancer centers in the Netherlands. In each center, 2 nurses and 2 surgeons were interviewed regarding their expectations of continuous vital signs monitoring for early recognition of complications after esophagectomy. Historical data of patient characteristics and clinical outcomes were collected in each center and presented to the local participants to support estimations on clinical outcome.

Results

The majority of nurses and surgeons expected that continuous vital signs monitoring could contribute to the earlier recognition of deterioration and result in earlier treatment for postoperative complications, although the effective time gain would depend on patient and situational factors. Their expectations regarding the impact of potential earlier diagnosis on clinical outcomes varied. Nevertheless, most caregivers would consider implementing continuous monitoring in the surgical ward to support patient monitoring after esophagectomy.

Conclusions

Caregivers expected that wireless vital signs monitoring would provide opportunities for early detection of postoperative complications in patients undergoing esophagectomy admitted to the ward and prevent sequelae under certain circumstances. As the technology matures, clinical outcome studies will be necessary to objectify these expectations and further investigate overall effects on patient outcome.

Adaptive threshold-based alarm strategies for continuous vital signs monitoring

Continuous vital signs monitoring in post-surgical ward patients may support early detection of clinical deterioration, but novel alarm approaches are required to ensure timely notification of abnormalities and prevent alarm-fatigue. The current study explored the performance of classical and various adaptive threshold-based alarm strategies to warn for vital sign abnormalities observed during development of an adverse event. A classical threshold-based alarm strategy used for continuous vital signs monitoring in surgical ward patients was evaluated retrospectively. Next, (combinations of) six methods to adapt alarm thresholds to personal or situational factors were simulated in the same dataset. Alarm performance was assessed using the overall alarm rate and sensitivity to detect adverse events. Using a wireless patch-based monitoring system, 3999 h of vital signs data was obtained in 39 patients. The clinically used classical alarm system produced 0.49 alarms/patient/day, and alarms were generated for 11 out of 18 observed adverse events. Each of the tested adaptive strategies either increased sensitivity to detect adverse events or reduced overall alarm rate. Combining specific strategies improved overall performance most and resulted in earlier presentation of alarms in case of adverse events. Strategies that adapt vital sign alarm thresholds to personal or situational factors may improve early detection of adverse events or reduce alarm rates as compared to classical alarm strategies. Accordingly, further investigation of the potential of adaptive alarms for continuous vital signs monitoring in ward patients is warranted.

Consensus on predictors of clinical deterioration in emergency departments: A Delphi process study

AIM

The study aim was to determine relevance and applicability of generic predictors of clinical deterioration in emergency departments based on consensus among clinicians.

METHODS

Thirty-three predictors of clinical deterioration identified from literature were assessed in a modified two-stage Delphi-process. Sixty-eight clinicians (physicians and nurses) participated in the first round and 48 in the second round; all treating hospitalized patients in Danish emergency departments, some with pre-hospital experience. The panel rated the predictors for relevance (relevant marker of clinical deterioration) and applicability (change in clinical presentation over time, generic in nature and possible to detect bedside). They rated their level of agreement on a 9-point Likert scale and were also invited to propose additional generic predictors between the rounds. New predictors suggested by more than one clinician were included in the second round along with non-consensus predictors from the first round. Final decisions of non-consensus predictors after second round were made by a research group and an impartial physician.

RESULTS

The Delphi-process resulted in 19 clinically relevant and applicable predictors based on vital signs and parameters (respiratory rate, saturation, dyspnoea, systolic blood pressure, pulse rate, abnormal electrocardiogram, altered mental state and temperature), biochemical tests (serum c-reactive protein, serum bicarbonate, serum lactate, serum pH, serum potassium, glucose, leucocyte counts and serum haemoglobin), objective clinical observations (skin conditions) and subjective clinical observations (pain reported as new or escalating, and relatives' concerns).

CONCLUSION

The Delphi-process led to consensus of 19 potential predictors of clinical deterioration widely accepted as relevant and applicable in emergency departments.

[Postoperative remote monitoring]

During the course of surgical interventions, complications mostly occur in the postoperative period. Slight clinical indications can be observed, which precede a significant deterioration of the patient's condition. On the general ward vital parameters, such as heart and breathing frequencies are measured every 4-8 h. Even if the monitoring of critically ill patients is increased to every 2 h and the measurement of vital functions takes 10 min, the patient is only monitored for 120 min in a 24 h period and remains postoperatively on the general ward without monitoring for 22 out of 24 h. New wireless monitoring systems are available to continuously register some vital functions with the aid of wearable sensors. These systems can alert and alarm ward personnel if the patient's condition deteriorates. Although the optimal monitoring system does not yet exist and implementation of these new wireless monitoring systems might involve some risks, these new methods offer a great opportunity to optimize surveillance of postoperative patients on the general ward.

Clinical outcomes of digital sensor alerting systems in remote monitoring: a systematic review and meta-analysis

Advances in digital technologies have allowed remote monitoring and digital alerting systems to gain popularity. Despite this, limited evidence exists to substantiate claims that digital alerting can improve clinical outcomes. The aim of this study was to appraise the evidence on the clinical outcomes of digital alerting systems in remote monitoring through a systematic review and meta-analysis. A systematic literature search, with no language restrictions, was performed to identify studies evaluating healthcare outcomes of digital sensor alerting systems used in remote monitoring across all (medical and surgical) cohorts. The primary outcome was hospitalisation; secondary outcomes included hospital length of stay (LOS), mortality, emergency department and outpatient visits. Standard, pooled hazard ratio and proportion of means meta-analyses were performed. A total of 33 studies met the eligibility criteria; of which, 23 allowed for a meta-analysis. A 9.6% mean decrease in hospitalisation favouring digital alerting systems from a pooled random effects analysis was noted. However, pooled weighted mean differences and hazard ratios did not reproduce this finding. Digital alerting reduced hospital LOS by a mean difference of 1.043 days. A 3% mean decrease in all-cause mortality from digital alerting systems was noted. There was no benefit of digital alerting with respect to emergency department or outpatient visits. Digital alerts can considerably reduce hospitalisation and length of stay for certain cohorts in remote monitoring. Further research is required to confirm these findings and trial different alerting protocols to understand optimal alerting to guide future widespread implementation.

An Implementation Science Approach to Promote Optimal Implementation, Adoption, Use, and Spread of Continuous Clinical Monitoring System Technology

OBJECTIVES

This study aimed to apply implementation science tenets to guide the deployment and use of in-hospital Clinical Monitoring System Technology (CMST) and to develop a toolkit to promote optimal implementation, adoption, use, and spread of CMST.

METHODS

Six steps were carried out to (1) establish leadership support; (2) identify, educate, and sustain champions; (3) enlist clinical staff users to learn barriers and facilitators; (4) examine initial qualitative data from 11 clinician group interviews; (5) validate barriers/facilitators to CMST use and toolkit content; and (6) propose a toolkit to promote utilization. Clinical Monitoring System Technology output before and after implementation were compared.

RESULTS

The top 3 barriers to effective CMST use were as follows: (1) inadequate education/training/support, (2) clinical workflow challenges, and (3) lack of communication. Facilitators to CMST implementation and adoption included the following: (1) providing comprehensive and consistent CMST education, (2) presenting evidence early and often, (3) tailoring device and usage expectations to individual environments, and (4) providing regular feedback about progress. Empirical data drove the development of a CMST implementation toolkit covering 6 areas: (1) why, (2) readiness, (3) readiness and implementation, (4) patient/family introduction, (5) champions, (6) care team saves, and (7) troubleshooting. Clinical Monitoring System Technology positively impacted failure to rescue events. Monthly median cardiac alert responses decreased from 30 to 3.64 minutes (87.9%), and respiratory alert responses decreased from 26 to 4.85 minutes (81.4%).

CONCLUSIONS

Using implementation science tenets to concurrently guide deployment and study performance of 2 CMST devices and impact on workload was effective for both learning CMST efficacy at 2 hospital systems and developing a toolkit to promote optimal implementation, adoption, use, and spread.

Post-operative alarm signs in the rapid response system and hospital mortality after non-cardiac surgery

BACKGROUND

A variety of rapid response systems (RRSs) based on the systematic assessment of vital signs and laboratory tests have been developed to reduce hospital mortality through the early detection of alarm signs, while deterioration may still be reversible. This study aimed to determine the association between alarm signs and post-operative hospital mortality during post-operative days (POD) 0-3 in patients undergoing non-cardiac surgery.

METHODS

This retrospective observational study used data from the registry of a single tertiary academic hospital. The study population included patients who were ≥18 years old, admitted between 1 January 2013 and 30 June 2018 for non-cardiac surgery, and subsequently transferred to the general ward.

RESULTS

A total of 116 329 patients were included in the analysis. Among them, 10 099 patients (8.7%) showed positive alarm criteria and triggered the RRS in the post-operative ward during POD 0-3. In the multivariate logistic regression model, PaO₂ <55 mm Hg, SpO₂ <90%, and total CO₂ <15 mmol/L were associated with a 3.57-, 3.46-, and 12.53-fold increase in post-operative hospital mortality, respectively. Moreover, when compared to the no alarm signs group, patients with 1, 2, 3, and ≥4 alarm signs showed a 2.79-, 2.76-, 6.54-, and 20.02-fold increase in hospital mortality, respectively.

CONCLUSION

Increased post-operative hospital mortality was found to be associated with alarm signs detected by the RRS during POD 0-3. The post-operative alarm signs detected by the RRS may therefore be useful in determining high-risk patients who require medical interventions in the surgical ward.

Education, Implementation, and Teams: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

For this 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations, the Education, Implementation, and Teams Task Force applied the population, intervention, comparator, outcome, study design, time frame format and performed 15 systematic reviews, applying the Grading of Recommendations, Assessment, Development, and Evaluation guidance. Furthermore, 4 scoping reviews and 7 evidence updates assessed any new evidence to determine if a change in any existing treatment recommendation was required. The topics covered included training for the treatment of opioid overdose; basic life support, including automated external defibrillator training; measuring implementation and performance in communities, and cardiac arrest centers; advanced life support training, including team and leadership training and rapid response teams; measuring cardiopulmonary resuscitation performance, feedback devices, and debriefing; and the use of social media to improve cardiopulmonary resuscitation application.