The measurement frequency and completeness of vital signs in general hospital wards: An evidence free zone?

Implementing Autonomous Control in the Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring

Conventional patient monitoring methods require skin-to-skin contact, continuous observation, and long working shifts, causing physical and mental stress for medical professionals. Remote patient monitoring (RPM) assists healthcare workers in monitoring patients distantly using various wearable sensors, reducing stress and infection risk. RPM can be enabled by using the Digital Twins (DTs)-based Internet of Robotic Things (IoRT) that merges robotics with the Internet of Things (IoT) and creates a virtual twin (VT) that acquires sensor data from the physical twin (PT) during operation to reflect its behavior. However, manual navigation of PT causes cognitive fatigue for the operator, affecting trust dynamics, satisfaction, and task performance. Also, operating manual systems requires proper training and long-term experience. This research implements autonomous control in the DTs-based IoRT to remotely monitor patients with chronic or contagious diseases. This work extends our previous paper that required the user to manually operate the PT using its VT to collect patient data for medical inspection. The proposed decision-making algorithm enables the PT to autonomously navigate towards the patient's room, collect and transmit health data, and return to the base station while avoiding various obstacles. Rather than manually navigating, the medical personnel direct the PT to a specific target position using the Menu buttons. The medical staff can monitor the PT and the received sensor information in the pre-built virtual environment (VE). Based on the operator's preference, manual control of the PT is also achievable. The experimental outcomes and comparative analysis verify the efficiency of the proposed system.

Nurse productivity: using evidence to enhance nurses' use of time

The UK is experiencing a nursing shortage, making it challenging to maintain the staffing levels required to deliver effective patient care. One way of enhancing the care delivered by the existing workforce could be to optimise nurse productivity; however, previous efforts to do this have been largely ineffective, due in part to a focus on the processes of care delivery rather than the nursing activities within these processes. In this article, the author explores the concept of nurse productivity and suggests that enhancing productivity requires the identification of nursing activities and consideration of how these may be undertaken in a more time-efficient manner - or removed altogether. The author discusses two such activities: intentional (hourly) rounding, and fixed-time manual vital signs for patients on general wards. The author also considers the potential of using automatic continuous remote monitoring on general hospital wards to free up nurses' time for other care activities.

Indicators of patient deterioration in poorly resourced private hospitals: Which vital sign to watch? A retrospective case-control study

BACKGROUND

Patient vital signs are a measure of wellness if monitored regularly and accurately. Staff shortages in poorly resourced regional hospitals often result in inadequate patient monitoring, putting patients at risk of undetected deterioration.

OBJECTIVE

This study aims to explore the pattern and completeness of vital sign monitoring and the contribution of each vital sign in predicting clinical deterioration events in resource-poor regional/rural hospitals.

METHOD

Using a retrospective case-control study design, we compared 24 h of vital sign data from deteriorating and nondeteriorating patients from two poorly-resourced regional hospitals. Descriptive statistics, t-tests, and analysis of variance are used to compare patient-monitoring frequency and completeness. The contribution of each vital sign in predicting patient deterioration was determined using the Area Under the Receiver Operator Characteristic curve and binary logistical regression analysis.

RESULTS

Deteriorating patients were monitored more frequently (9.58 [7.02] times) in the 24-h period than nondeteriorating patients (4.93 [2.66] times). However, the completeness of vital sign documentation was higher in nondeteriorating (85.2%) than in deteriorating patients (57.7%). Body temperature was the most frequently omitted vital sign. Patient deterioration was positively linked to the frequency of abnormal vital signs and the number of abnormal vital signs per set (Area Under the Receiver Operator Characteristic curve: 0.872 and 0.867, respectively). No single vital sign strongly predicts patient outcomes. However, a supplementary oxygen value of >3 L/min and a heart rate of >139 beats/min were the best predictors of patient deterioration.

CONCLUSION

Given the poor resourcing and often geographical remoteness of small regional hospitals, it is prudent that the nursing staff are made aware of the vital signs that best indicate deterioration for the cohort of patients in their care. Tachycardic patients on supplementary oxygen are at high risk of deterioration.

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.

Pediatric vital signs monitoring in hospital wards: Recognition systems and factors influencing nurses' attitudes and practices

AIMS

To describe: 1) systems in place for recognition and response to deteriorating children in Italy, 2) attitudes and practices of registered nurses (RN) towards vital signs (VS) monitoring in pediatric wards, 3) the associations of nurses attitudes and pratices with nurses' and organizational characteristics.

DESIGN AND METHODS

A multicentre cross-sectional correlational study. Data were collected between January-May 2020 using: an adapted version of the 'Survey on Recognition and Response Systems in Australia', and the 'Ped-V Scale'. Descriptive and adjusted linear regression analysis was performed, accounting for clustering.

RESULTS

Ten Italian hospitals participated, 432 RNs responded to the Ped-V scale (response rate = 52%). Five (50%) hospitals had a VS policy in place, three hospitals (30%) had a Pediatric Early Warning System (PEWS), almost all hospitals had a system in place to respond to deteriorating children. Following multivariate regression analysis, having a PEWS was significantly associated with Ped-V scale 'Workload', 'Clinical competence', 'Standardization' dimensions; gender was associated with 'key indicators' and pediatric surgical ward with 'Clinical competence'.

CONCLUSIONS

The use of VS policies and PEWS was not consistent across hospitals caring for children in Italy. Nurses' attitudes and practices (i.e., perception of workload, and clinical competence) were significantly lower in hospitals with increased complexity of care/PEWS. Gender was significantly associated with knowledge scores.

PRACTICE IMPLICATIONS

System strategies to improve nurses' attitudes and practices towards VS monitoring and education are warranted to support effective behaviors towards VS monitoring, their interpretation, and appropriate communication to activate the efferent limb of the rapid response system.

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.

Combined Cardiac and Respiratory Monitoring from a Single Signal: A Case Study Employing the Fantasia Database

This study proposes a novel method for obtaining the electrocardiogram (ECG) derived respiration (EDR) from a single lead ECG and respiration-derived cardiogram (RDC) from a respiratory stretch sensor. The research aims to reconstruct the respiration waveform, determine the respiration rate from ECG QRS heartbeat complexes data, locate heartbeats, and calculate a heart rate (HR) using the respiration signal. The accuracy of both methods will be evaluated by comparing located QRS complexes and inspiration maxima to reference positions. The findings of this study will ultimately contribute to the development of new, more accurate, and efficient methods for identifying heartbeats in respiratory signals, leading to better diagnosis and management of cardiovascular diseases, particularly during sleep where respiration monitoring is paramount to detect apnoea and other respiratory dysfunctions linked to a decreased life quality and known cause of cardiovascular diseases. Additionally, this work could potentially assist in determining the feasibility of using simple, no-contact wearable devices for obtaining simultaneous cardiology and respiratory data from a single device.

Vital signs-based deterioration prediction model assumptions can lead to losses in prediction performance

OBJECTIVE

Vital signs-based models are complicated by repeated measures per patient and frequently missing data. This paper investigated the impacts of common vital signs modeling assumptions during clinical deterioration prediction model development.

STUDY DESIGN AND SETTING

Electronic medical record (EMR) data from five Australian hospitals (1 January 2019-31 December 2020) were used. Summary statistics for each observation's prior vital signs were created. Missing data patterns were investigated using boosted decision trees, then imputed with common methods. Two example models predicting in-hospital mortality were developed, as follows: logistic regression and eXtreme Gradient Boosting. Model discrimination and calibration were assessed using the C-statistic and nonparametric calibration plots.

RESULTS

The data contained 5,620,641 observations from 342,149 admissions. Missing vitals were associated with observation frequency, vital sign variability, and patient consciousness. Summary statistics improved discrimination slightly for logistic regression and markedly for eXtreme Gradient Boosting. Imputation method led to notable differences in model discrimination and calibration. Model calibration was generally poor.

CONCLUSION

Summary statistics and imputation methods can improve model discrimination and reduce bias during model development, but it is questionable whether these differences are clinically significant. Researchers should consider why data are missing during model development and how this may impact clinical utility.

Real-time risk prediction of colorectal surgery-related post-surgical complications using GRU-D model

BACKGROUND

Post-surgical complications (PSCs) have been an increasing concern for hospitals in light of Medicare penalties for 30-day readmissions. PSCs have become a target for quality improvement and benchmark for the healthcare system. Over half (60 %) of the deep or organ space surgical site infections are discovered after discharge, leading to a readmission. There has thus been a push to develop risk prediction models for targeted preventive interventions for PSCs.

OBJECTIVE

We experiment several Gated Recurrent Unit with Decay (GRU-D) based deep learning architectures with various feature sampling schemes in predicting the risk of colorectal PSCs and compare with atemporal logistic regression models (logit).

METHOD

We used electronic health record (EHR) data of 3,535 colorectal surgical patients involved in the national surgical quality improvement program (NSQIP) between 2006 and 2018. Single layer, stacked layer, and multimodal GRU-D models with sigmoid activation were used to develop risk prediction models. Area Under the Receiver Operating Characteristic curve (AUROC) was calculated by comparing predicted probability of developing complications versus truly observed PSCs (NSQIP adjudicated) within 30 days after surgery. We set up cross-validation and an independent held-out dataset for testing model performance consistency.

RESULTS AND CONCLUSION

The primary contribution of our study is the formulation of a novel real-time PSC risk prediction task using GRU-D with demonstrated clinical utility. GRU-D outperforms the logit model in predicting wound and organ space infection and shows improved performance as additional data points become available. Logit model outperforms GRU-D before surgery for superficial infection and bleeding. For the same sampling scheme, there is no obvious advantage of complex architectures (stacked, multimodal) over single layer GRU-D. Obtaining more data points closer to the occurrence of PSCs is more important than using a more frequent sampling scheme in training GRU-D models. The fourth predicted risk quartile by single layer GRU-D contains 63 %, 59 %, and 66 % organ space infection cases, at 4 h before, 72 h after, and 168 h after surgery, respectively, suggesting its potential application as a bedside risk assessment tool.

The clinical neglect of vital signs' assessment: an emerging patient safety issue?

OBJECTIVE

Vital signs assessment is a critical component of acute clinical care. Despite this, research has consistently found that the assessment of these signs is often neglected in clinical practice. This paper highlights three recent cases in the media where the neglect of vital signs assessment resulted in patient mortality.

RESULTS

Recent media reports highlighted the potentially devastating consequences of vital signs not being rigorously assessed including avoidable death. The public needs to be confident they will receive safe, quality health care when admitted to hospital.

CONCLUSION

The neglect of vital signs assessment places patients at risk of poor outcomes. Early detection of clinical deterioration via the assessment of vital signs facilitates prompt medical intervention. Factors contributing to the neglect of vital signs assessment need to be identified and corrective action taken to improve the safety of clinical care.

Effect of the national early warning score on monitoring the vital signs of patients in the emergency room

OBJECTIVE

To verify the effect of using the National Early Warning Score (NEWS) system on the compliance of the vital signs monitoring interval with those recommended for patients in the emergency room.

METHODS

This is a quasi-experimental, before-and-after study, performed in an emergency room with 280 adult patients selected by convenience. The effect of NEWS on the compliance of the vital signs monitoring interval with those recommended by the system was analyzed by linear regression.

RESULTS

In the Pre-NEWS phase, 143 patients were analyzed (mean age ± standard deviation: 54.4 ± 20.5; male: 56.6%) and, in the Post-NEWS phase, 137 patients (mean age ± standard deviation: 55.5 ± 20.8; male: 50.4%). There was compliance of the vital signs monitoring interval with what is recommended by NEWS in 92.6% of vital signs records after adopting this instrument. This compliance was 9% (p < 0.001) higher in the Post-NEWS phase.

CONCLUSION

The use of the NEWS system increased the compliance of the vital signs monitoring intervals with the ones recommended, but this compliance decreased when the NEWS score pointed to a shorter interval in the monitoring of vital signs.

"Help Me Sleep": A Quality Initiative to Reduce Overnight Vital Signs

BACKGROUND AND OBJECTIVES

Sleep is an essential part of the recovery process, yet inpatient sleep quality is poor. Patients and families report that vital signs are the most bothersome overnight disruption. Obtaining vital signs every 4 hours (Q4H) is not evidence-based and is frequently ordered indiscriminately. We aimed to decrease the percentage of patient nights with vital sign checks between 12 am and 6 am in a low-risk population from 98% to 70% within 12 months to minimize overnight sleep disruptions and improve inpatient sleep.

METHODS

We conducted a quality improvement project on 3 pediatric hospital medicine teams at a large free-standing children's hospital. Our multidisciplinary team defined low-risk patients as those admitted for hyperbilirubinemia and failure to thrive. Interventions were focused around education, electronic health record decision support, and patient safety. The outcome measure was the percentage of patient nights without a vital sign measurement between 12 am and 6 am and was analyzed by using statistical process control charts. Our process measure was the use of an appropriate vital sign order. Balancing measures included adverse patient events, specifically code blues outside the ICU and emergent transfers.

RESULTS

From March 2020 to April 2021, our pediatric hospital medicine (PHM) services admitted 449 low-risk patients for a total of 1550 inpatient nights. The percentage of patient nights with overnight vital signs decreased from 98% to 38%. There were no code blues or emergent transfers.

CONCLUSION

Our improvement interventions reduced the frequency of overnight vital sign monitoring in 2 low-risk groups without any adverse events.

Efeito do national early warning score no monitoramento dos sinais vitais de pacientes no pronto-socorro

RESUMO Objetivo: Verificar o efeito do uso do sistema National Early Warning Score (NEWS) na conformidade do intervalo de monitoramento dos sinais vitais com o recomendado em pacientes no pronto-socorro. Método: Estudo quasi-experimental, do tipo antes e depois, realizado em um pronto-socorro com 280 pacientes adultos selecionados por conveniência. O efeito do NEWS na conformidade do intervalo de monitoramento dos sinais vitais com o recomendado pelo sistema foi analisado por regressão linear. Resultados: Na fase Pré-NEWS, foram analisados 143 pacientes (idade média ± desvio-padrão: 54,4 ± 20,5; sexo masculino: 56,6%) e, na fase Pós-NEWS, 137 pacientes (idade média ± desvio-padrão: 55,5 ± 20,8; sexo masculino: 50,4%). Houve conformidade do intervalo de monitoramento dos sinais vitais com o recomendo pelo NEWS em 92,6% dos registros de sinais vitais após adoção desse instrumento. Essa conformidade foi maior na fase Pós-NEWS em 9% (p < 0,001). Conclusão: O uso do sistema NEWS aumentou a conformidade dos intervalos de monitorização dos sinais vitais com o recomendado, porém essa conformidade diminuiu quando o escore NEWS apontou para intervalo menor no monitoramento dos sinais vitais.

How long do nursing staff take to measure and record patients' vital signs observations in hospital? A time-and-motion study

Introduction

Monitoring vital signs in hospital is an important part of safe patient care. However, there are no robust estimates of the workload it generates for nursing staff. This makes it difficult to plan adequate staffing to ensure current monitoring protocols can be delivered.

Objective

To estimate the time taken to measure and record one set of patient's vital signs; and to identify factors associated with the time required to measure and record one set of patient's vital signs.

Methods

We undertook a time-and-motion study of 16 acute medical or surgical wards across four hospitals in England. Two trained observers followed a standard operating procedure to record the time taken to measure and record vital signs. We used mixed-effects models to estimate the mean time using whole vital signs rounds, which included equipment preparation, time spent taking vital signs at the bedside, vital signs documentation, and equipment storing. We tested whether our estimates were influenced by nurse, ward and hospital factors.

Results

After excluding non-vital signs related interruptions, dividing the length of a vital signs round by the number of vital signs assessments in that round yielded an estimated time per vital signs set of 5 min and 1 second (95% Confidence Interval (CI) = 4:39–5:24). If interruptions within the round were included, the estimated time was 6:26 (95% CI = 6:01–6:50). If only time taking each patient's vital signs at the bedside was considered, after excluding non-vital signs related interruptions, the estimated time was 3:45 (95% CI = 3:32–3:58). We found no substantial differences by hospital, ward or nurse characteristics, despite different systems for recording vital signs being used across the hospitals.

Discussion

The time taken to observe and record a patient's vital signs is considerable, so changes to recommended assessment frequency could have major workload implications. Variation in estimates derived from previous studies may, in part, arise from a lack of clarity about what was included in the reported times. We found no evidence that nurses save time when using electronic vital signs recording, or that the grade of staff measuring the vital signs influenced the time taken.

Conclusions

Measuring and recording vital signs is time consuming and the impact of interruptions and preparation away from the bedside is considerable. When considering the nursing workload around vital signs assessment, no assumption of relative efficiency should be made if different technologies or staff groups are deployed.

Vibrational spectroscopic analysis of blood for diagnosis of infections and sepsis: a review of requirements for a rapid diagnostic test

Infections and sepsis represent a growing global burden. There is a widespread clinical need for a rapid, high-throughput and sensitive technique for the diagnosis of infections and detection of invading pathogens and the presence of sepsis. Current diagnostic methods primarily consist of laboratory-based haematology, biochemistry and microbiology that are time consuming, labour- and resource-intensive, and prone to both false positive and false negative results. Current methods are insufficient for the increasing demands on healthcare systems, causing delays in diagnosis and initiation of treatment, due to the intrinsic time delay in sample preparation, measurement, and analysis. Vibrational spectroscopic techniques can overcome these limitations by providing a rapid, label-free and low-cost method for blood analysis, with limited sample preparation required, potentially revolutionising clinical diagnostics by producing actionable results that enable early diagnosis, leading to improved patient outcomes. This review will discuss the challenges associated with the diagnosis of infections and sepsis, primarily within the UK healthcare system. We will consider the clinical potential of spectroscopic point-of-care technologies to enable blood analysis in the primary-care setting.

[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.

Battlefield Vital Sign Monitoring in Role 1 Military Treatment Facilities: A Thematic Analysis of After-Action Reviews from the Prehospital Trauma Registry

INTRODUCTION

The Prehospital Trauma Registry (PHTR) captures after-action reviews (AARs) as part of a continuous performance improvement cycle and to provide commanders real-time feedback of Role 1 care. We have previously described overall challenges noted within the AARs. We now performed a focused assessment of challenges with regard to hemodynamic monitoring to improve casualty monitoring systems.

MATERIALS AND METHODS

We performed a review of AARs within the PHTR in Afghanistan from January 2013 to September 2014 as previously described. In this analysis, we focus on AARs specific to challenges with hemodynamic monitoring of combat casualties.

RESULTS

Of the 705 PHTR casualties, 592 had available AAR data; 86 of those described challenges with hemodynamic monitoring. Most were identified as male (97%) and having sustained battle injuries (93%), typically from an explosion (48%). Most were urgent evacuation status (85%) and had a medical officer in their chain of care (65%). The most common vital sign mentioned in AAR comments was blood pressure (62%), and nearly one-quarter of comments stated that arterial palpation was used in place of blood pressure cuff measurements.

CONCLUSIONS

Our qualitative methods study highlights the challenges with obtaining vital signs-both training and equipment. We also highlight the challenges regarding ongoing monitoring to prevent hemodynamic collapse in severely injured casualties. The U.S. military needs to develop better methods for casualty monitoring for the subset of casualties that are critically injured.

Development and validation of a methodology to measure the time taken by hospital nurses to make vital signs observations

BACKGROUND

Several time and motion studies have sought to quantify the nursing work involved in observing patients' vital signs. However, none of these studies offered a validated methodology that can be replicated. This is reflected in the high variation between these studies in the mean times for measuring and recording observations.

AIM

To describe the development and inter-rater reliability of a methodology for observing the nursing time and workload involved in measuring and recording patients' vital signs.

DISCUSSION

The authors developed a methodology that used the quality of interactions (QI) tool ( Bridges et al 2018 ) to measure and record the start and finish times of the rounds of nurses observing vital signs and individual observations clustered in rounds. Two raters concurrently documented their observations of nurses undertaking patient observations in a simulated setting. The tool and associated documentation were found to be easy to use, and there was a high level of agreement in measurements by different observers.

CONCLUSION

The authors' methodology can be used to reliably measure the time involved in taking vital signs.

IMPLICATIONS FOR PRACTICE

Using the QI tool may increase precision when timing and classifying nursing activities concerning observing vital signs. The authors anticipate that it could be adapted effectively to measure several other nursing activities and so support researchers interested in capturing different aspects of nurses' work.

What is the nursing time and workload involved in taking and recording patients' vital signs? A systematic review

AIMS AND OBJECTIVES

To synthesise evidence regarding the time nurses take to monitor and record vital signs observations and to calculate early warning scores.

BACKGROUND

While the importance of vital signs' monitoring is increasingly highlighted as a fundamental means of maintaining patient safety and avoiding patient deterioration, the time and associated workload involved in vital signs activities for nurses are currently unknown.

DESIGN

Systematic review.

METHODS

A literature search was performed up to 17 December 2019 in CINAHL, Medline, EMBASE and the Cochrane Library using the following terms: vital signs; monitoring; surveillance; observation; recording; early warning scores; workload; time; and nursing. We included studies performed in secondary or tertiary ward settings, where vital signs activities were performed by nurses, and we excluded qualitative studies and any research conducted exclusively in paediatric or maternity settings. The study methods were compliant with the PRISMA checklist.

RESULTS

Of 1,277 articles, we included 16 papers. Studies described taking vital signs observations as the time to measure/collect vital signs and time to record/document vital signs. As well as mean times being variable between studies, there was considerable variation in the time taken within some studies as standard deviations were high. Documenting vital signs observations electronically at the bedside was faster than documenting vital signs away from the bed.

CONCLUSIONS

Variation in the method(s) of vital signs measurement, the timing of entry into the patient record, the method of recording and the calculation of early warning scores values across the literature make direct comparisons of their influence on total time taken difficult or impossible.

RELEVANCE TO CLINICAL PRACTICE

There is a very limited body of research that might inform workload planning around vital signs observations. This uncertainty means the resource implications of any recommendation to change the frequency of observations associated with early warning scores are unknown.

Impact of using data from electronic protocols in nursing performance management: A qualitative interview study

Aim

To explore the impact of using electronic data in performance management to improve nursing compliance with a protocol.

Background

Electronic data are increasingly used to monitor protocol compliance but little is known about the impact on nurses’ practice in hospital wards.

Method

Seventeen acute hospital nursing staff participated in semi‐structured interviews about compliance with an early warning score (EWS) protocol delivered by a bedside electronic handheld device.

Results

Before electronic EWS data was used to monitor compliance, staff combined protocol‐led actions with clinical judgement. However, some observations were missed to reduce noise and disruption at night. After compliance monitoring was introduced, observations were sometimes covertly omitted using a loophole. Interviewees described a loss of autonomy but acknowledged the EWS system sometimes flagged unexpected patient deterioration.

Conclusions

Introducing automated electronic systems to support nursing tasks can decrease nursing burden but remove the ability to record legitimate reasons for missing observations. This can result in covert resistance that could reduce patient safety.

Implications for nursing management

Providing the ability to log legitimate reasons for missing observations would allow nurses to balance professional judgement with the use of electronic data in performance management of protocol compliance.

The association between nurse staffing levels and the timeliness of vital signs monitoring: a retrospective observational study in the UK

OBJECTIVES

Omissions and delays in delivering nursing care are widely reported consequences of staffing shortages, with potentially serious impacts on patients. However, studies so far have relied almost exclusively on nurse self-reporting. Monitoring vital signs is a key part of nursing work and electronic recording provides an opportunity to objectively measure delays in care. This study aimed to determine the association between registered nurse (RN) and nursing assistant (NA) staffing levels and adherence to a vital signs monitoring protocol.

DESIGN

Retrospective observational study.

SETTING

32 medical and surgical wards in an acute general hospital in England.

PARTICIPANTS

538 238 nursing shifts taken over 30 982 ward days.

PRIMARY AND SECONDARY OUTCOME MEASURES

Vital signs observations were scheduled according to a protocol based on the National Early Warning Score (NEWS). The primary outcome was the daily rate of missed vital signs (overdue by ≥67% of the expected time to next observation). The secondary outcome was the daily rate of late vital signs observations (overdue by ≥33%). We undertook subgroup analysis by stratifying observations into low, medium and high acuity using NEWS.

RESULTS

Late and missed observations were frequent, particularly in high acuity patients (median=44%). Higher levels of RN staffing, measured in hours per patient per day (HPPD), were associated with a lower rate of missed observations in all (IRR 0.983, 95% CI 0.979 to 0.987) and high acuity patients (0.982, 95% CI 0.972 to 0.992). However, levels of NA staffing were only associated with the daily rate (0.954, CI 0.949 to 0.958) of all missed observations.

CONCLUSIONS

Adherence to vital signs monitoring protocols is sensitive to levels of nurse and NA staffing, although high acuity observations appeared unaffected by levels of NAs. We demonstrate that objectively measured omissions in care are related to nurse staffing levels, although the absolute effects are small.

STUDY REGISTRATION

The data and analyses presented here were part of the larger Missed Care study (ISRCTN registration: 17930973).

The value of vital sign trends in predicting and monitoring clinical deterioration: A systematic review

BACKGROUND

Vital signs, i.e. respiratory rate, oxygen saturation, pulse, blood pressure and temperature, are regarded as an essential part of monitoring hospitalized patients. Changes in vital signs prior to clinical deterioration are well documented and early detection of preventable outcomes is key to timely intervention. Despite their role in clinical practice, how to best monitor and interpret them is still unclear.

OBJECTIVE

To evaluate the ability of vital sign trends to predict clinical deterioration in patients hospitalized with acute illness.

DATA SOURCES

PubMed, Embase, Cochrane Library and CINAHL were searched in December 2017.

STUDY SELECTION

Studies examining intermittently monitored vital sign trends in acutely ill adult patients on hospital wards and in emergency departments. Outcomes representing clinical deterioration were of interest.

DATA EXTRACTION

Performed separately by two authors using a preformed extraction sheet.

RESULTS

Of 7,366 references screened, only two were eligible for inclusion. Both were retrospective cohort studies without controls. One examined the accuracy of different vital sign trend models using discrete-time survival analysis in 269,999 admissions. One included 44,531 medical admissions examining trend in Vitalpac Early Warning Score weighted vital signs. They stated that vital sign trends increased detection of clinical deterioration. Critical appraisal was performed using evaluation tools. The studies had moderate risk of bias, and a low certainty of evidence. Additionally, four studies examining trends in early warning scores, otherwise eligible for inclusion, were evaluated.

CONCLUSIONS

This review illustrates a lack of research in intermittently monitored vital sign trends. The included studies, although heterogeneous and imprecise, indicates an added value of trend analysis. This highlights the need for well-controlled trials to thoroughly assess the research question.

Nurse staffing levels, missed vital signs and mortality in hospitals: retrospective longitudinal observational study

Background

Low nurse staffing levels are associated with adverse patient outcomes from hospital care, but the causal relationship is unclear. Limited capacity to observe patients has been hypothesised as a causal mechanism.

Objectives

This study determines whether or not adverse outcomes are more likely to occur after patients experience low nurse staffing levels, and whether or not missed vital signs observations mediate any relationship.

Design

Retrospective longitudinal observational study. Multilevel/hierarchical mixed-effects regression models were used to explore the association between registered nurse (RN) and health-care assistant (HCA) staffing levels and outcomes, controlling for ward and patient factors.

Setting and participants

A total of 138,133 admissions to 32 general adult wards of an acute hospital from 2012 to 2015.

Main outcomes

Death in hospital, adverse event (death, cardiac arrest or unplanned intensive care unit admission), length of stay and missed vital signs observations.

Data sources

Patient administration system, cardiac arrest database, eRoster, temporary staff bookings and the Vitalpac system (System C Healthcare Ltd, Maidstone, Kent; formerly The Learning Clinic Limited) for observations.

Results

Over the first 5 days of stay, each additional hour of RN care was associated with a 3% reduction in the hazard of death [hazard ratio (HR) 0.97, 95% confidence interval (CI) 0.94 to 1.0]. Days on which the HCA staffing level fell below the mean were associated with an increased hazard of death (HR 1.04, 95% CI 1.02 to 1.07), but the hazard of death increased as cumulative staffing exposures varied from the mean in either direction. Higher levels of temporary staffing were associated with increased mortality. Adverse events and length of stay were reduced with higher RN staffing. Overall, 16% of observations were missed. Higher RN staffing was associated with fewer missed observations in high-acuity patients (incidence rate ratio 0.98, 95% CI 0.97 to 0.99), whereas the overall rate of missed observations was related to overall care hours (RN + HCA) but not to skill mix. The relationship between low RN staffing and mortality was mediated by missed observations, but other relationships between staffing and mortality were not. Changing average skill mix and staffing levels to the levels planned by the Trust, involving an increase of 0.32 RN hours per patient day (HPPD) and a similar decrease in HCA HPPD, would be associated with reduced mortality, an increase in staffing costs of £28 per patient and a saving of £0.52 per patient per hospital stay, after accounting for the value of reduced stays.

Limitations

This was an observational study in a single site. Evidence of cause is not definitive. Variation in staffing could be influenced by variation in the assessed need for staff. Our economic analysis did not consider quality or length of life.

Conclusions

Higher RN staffing levels are associated with lower mortality, and this study provides evidence of a causal mechanism. There may be several causal pathways and the absolute rate of missed observations cannot be used to guide staffing decisions. Increases in nursing skill mix may be cost-effective for improving patient safety.

Future work

More evidence is required to validate approaches to setting staffing levels. Other aspects of missed nursing care should be explored using objective data. The implications of findings about both costs and temporary staffing need further exploration.

Trial registration

This study is registered as ISRCTN17930973.

Funding

This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 6, No. 38. See the NIHR Journals Library website for further project information.

Relationships between healthcare staff characteristics and the conduct of vital signs observations at night: Results of a survey and factor analysis

AIM

To explore the association of healthcare staff with factors relevant to completing observations at night.

DESIGN

Online survey conducted with registered nurses, midwives, healthcare support staff and student nurses who had worked at least one night shift in a National Health Service hospital in England.

METHODS

Exploratory factor analysis and mixed effects regression model adjusting for role, number of night shifts worked, experience and shift patterns.

RESULTS

Survey items were summarized into four factors: (a) workload and resources; (b) prioritization; (c) safety culture; (d) responsibility and control. Staff experience and role were associated with conducting surveillance tasks. Nurses with greater experience associated workload and resources with capacity to complete work at night. Responses of student nurses and midwives showed higher propensity to follow the protocol for conducting observations. Respondents working night shifts either exclusively or occasionally perceived that professional knowledge rather than protocol guided care tasks during night shifts.

A fundamental conflict of care: Nurses' accounts of balancing patients' sleep with taking vital sign observations at night

Aims and objectives

To explore why adherence to vital sign observations scheduled by an early warning score protocol reduces at night.

Background

Regular vital sign observations can reduce avoidable deterioration in hospital. early warning score protocols set the frequency of these observations by the severity of a patient's condition. Vital sign observations are taken less frequently at night, even with an early warning score in place, but no literature has explored why.

Design

A qualitative interpretative design informed this study.

Methods

Seventeen semi‐structured interviews with nursing staff working on wards with varying levels of adherence to scheduled vital sign observations. A thematic analysis approach was used.

Results

At night, nursing teams found it difficult to balance the competing care goals of supporting sleep with taking vital sign observations. The night‐time frequency of these observations was determined by clinical judgement, ward‐level expectations of observation timing and the risk of disturbing other patients. Patients with COPD or dementia could be under‐monitored, while patients nearing the end of life could be over‐monitored.

Conclusion

In this study, we found an early warning score algorithm focused on deterioration prevention did not account for long‐term management or palliative care trajectories. Nurses were therefore less inclined to wake such patients to take vital sign observations at night. However, the perception of widespread exceptions and lack of evidence regarding optimum frequency risks delegitimising the early warning score approach. This may pose a risk to patient safety, particularly patients with dementia or chronic conditions.

Relevance to clinical practice

Nurses should document exceptions and discuss these with the wider team. Hospitals should monitor why vital sign observations are missed at night, identify which groups are under‐monitored and provide guidance on prioritising competing expectations. early warning score protocols should take account of different care trajectories.