The impact of wearable continuous vital sign monitoring on deterioration detection and clinical outcomes in hospitalised patients: a systematic review and meta-analysis

Continuous vital sign monitoring of patients recovering from surgery on general wards: a narrative review

Most postoperative deaths occur on general wards, often linked to complications associated with untreated changes in vital signs. Monitoring in these units is typically intermittent checks each shift or maximally every 4-6 h, which misses prolonged periods of subtle changes in physiology that can herald a critical downstream event. Continuous monitoring of vital signs is therefore intuitively necessary for patient safety. The past five decades have seen monitoring systems evolve rapidly, and today entirely wireless, wearable, and portable continuous surveillance of vital signs is possible on general wards. Introduction of this technology has the potential to modify both the sensing (afferent) and response (efferent) limbs of monitoring, and will allow earlier detection of vital signs perturbations. But this comes with challenges, including but not limited to issues with connectivity, data handling, alarm fatigue, information overload, and lack of meaningful clinical interventions. Evidence from before and after studies and retrospective propensity-matched data suggests that continuous ward monitoring decreases the risk of intensive care unit (ICU) admissions, rapid response calls, and in some instances, mortality. This review summarises the history of general ward monitoring and describes future directions, including opportunities to implement these devices using artificial intelligence, pattern detection, and user-friendly interfaces. Pragmatic, well designed and appropriately powered trials, and real-world implementation data are necessary to make continuous monitoring standard practice at every hospital bed.

Using Inertial Measurement Units and Machine Learning to Classify Body Positions of Adults in a Hospital Bed

In hospitals, timely interventions can prevent avoidable clinical deterioration. Early recognition of deterioration is vital to stopping further decline. Measuring the way patients position themselves in bed and change their positions may signal when further assessment is necessary. While inertial measurement units (IMUs) have been used in health research, their use inside hospitals has been limited. This study explores the use of IMUs with machine learning to continuously capture, classify and visualise patient positions in hospital beds. The participants attended a data collection session in a simulated hospital bedspace and were asked to adopt nine positions. Movement data were captured using five IMU Xsens DOTs attached to the forehead, wrists and ankles. Support Vector Machine (SVM) and K-Nearest Neighbours classifiers were trained using five different combinations of sensors (e.g., right wrist only, right and left wrist) to determine body positions. Data from 30 participants were analysed. The highest accuracy (87.7%) was achieved by SVM using forehead and wrist sensors. Adding data from ankle sensors reduced the accuracy. To preserve patient privacy in a hospital setting, a 3D visualisation was developed in Unity, offering a non-identifiable representation of patient positions. This system could help clinicians monitor changes in position which may signal clinical deterioration.

Digital technologies in nursing: An umbrella review

BACKGROUND

Digital technologies promise to reduce nurses' workload and increase quality of care. However, considering the plethora of single and review studies published to date, maintaining a comprehensive overview of digital technologies' impact on nursing and effectively utilizing available evidence is challenging.

OBJECTIVE

This review aims (i) to map published reviews on digital nursing technologies, based on their aims and the specific technologies investigated, to synthesize evidence on how these technologies' uses is associated with (ii) nurses' work-related and organizational factors, professional behavior, and health and work safety and (iii) ethically relevant outcomes for people in need of care.

DESIGN

Preregistered overview of reviews (PROSPERO-ID: CRD42023389751).

SETTING(S)

We searched for systematic reviews in eight databases, five key journals, and reference lists of included reviews published in English until May 21, 2024.

METHODS

We used the AMSTAR 2 checklist to assess the methodological quality of included reviews reporting associations with nursing outcomes. The extracted data were analyzed by their frequency and narratively synthesized.

RESULTS

We identified 213 reviews on digital technologies' uses in the nursing sector. Most of these focused on information and communication technologies. The most frequently reported research objectives encompass technology usage and/or general experiences with it and technology-related consequences for care recipients. Regarding work-related and organizational factors, beneficial impacts were found for the execution of nursing tasks, information management and job control. Depending on the technology type, reviews reported mixed effects for documentation activities, communication/collaboration and mainly negative effects on nurses' workload. Concerning occupational safety and health-related and further nurse outcomes, reviews reported mostly positive effects on nurses' job satisfaction and professional competence. Adverse effects related to mental and physical strain, such as increased frustration, fatigue, and burnout. Regarding ethically relevant outcomes, robotic and telecare technologies had the most reported findings. Most evidence concerned effects on the principles of beneficence/non-maleficence and respect for autonomy.

CONCLUSIONS

Digital nursing technologies' legitimacy hinges on their impact on patient outcomes and nurses' work, safety, and health. This review identifies a diverse array of these technologies, with both positive and negative effects. However, due to narrative limitations, meta-analysis was impractical. Future research should quantitatively assess the effects of various digital nursing technologies on work, safety, health, and ethical outcomes.

TWEETABLE ABSTRACT

Research on digital tech in nursing lacks focus on key work factors, occupational health and ethical outcomes. #NursingTech #ResearchGaps.

Time to detection of serious adverse events by continuous vital sign monitoring versus clinical practice

BACKGROUND

Continuous vital sign monitoring detects far more severe vital sign deviations (SVDs) than intermittent clinical rounds, and deviations are to some extent related to subsequent serious adverse events (SAEs). Early detection of SAEs is pivotal to allow for effective interventions but the time relationship between detection of SAEs by continuous vital sign monitoring versus clinical practice is not well-described at the general ward.

AIM

To quantify the time difference between detection of SAEs by continuous vital sign monitoring and clinical suspicion of deterioration (CSD) in major abdominal surgery patients.

METHODS

Five hundred and five patients had their vital signs continuously monitored in combination with usual clinical practice consisting of National Early Warning Score assessments at least every 8'th hour, assessments during rounds, and other kinds of staff-patient interactions. The primary outcome was the time difference between the first chart note of CSD versus the first SVD, detected by continuous vital sign monitoring, in patients with a subsequent confirmed SAE during or up to 48 h after end of continuous vital sign monitoring.

RESULTS

Out of the 505 continuously monitored patients, 142 patients had a combination of both postoperative SAE, CSD and SVD, and thus were included in the primary analysis. The median time from the first SVD to SAE was 42.8 h (interquartile range 19.8-72.1 h) compared to 13 minutes (interquartile range - 4.8 to 3.5 h) for CSD with a median difference of 48.1 h (95% confidence interval 43.0-54.8 h), p-value < .001.

CONCLUSION

Continuous vital sign monitoring detects signs of oncoming SAEs in the form of SVD hours before CSD, potentially allowing for earlier and more effective treatments to reduce the extent of SAEs.

Discrepancies between Promised and Actual AI Capabilities in the Continuous Vital Sign Monitoring of In-Hospital Patients: A Review of the Current Evidence

Continuous vital sign monitoring (CVSM) with wireless sensors in general hospital wards can enhance patient care. An artificial intelligence (AI) layer is crucial to allow sensor data to be managed by clinical staff without over alerting from the sensors. With the aim of summarizing peer-reviewed evidence for AI support in CVSM sensors, we searched PubMed and Embase for studies on adult patients monitored with CVSM sensors in general wards. Peer-reviewed evidence and white papers on the official websites of CVSM solutions were also included. AI classification was based on standard definitions of simple AI, as systems with no memory or learning capabilities, and advanced AI, as systems with the ability to learn from past data to make decisions. Only studies evaluating CVSM algorithms for improving or predicting clinical outcomes (e.g., adverse events, intensive care unit admission, mortality) or optimizing alarm thresholds were included. We assessed the promised level of AI for each CVSM solution based on statements from the official product websites. In total, 467 studies were assessed; 113 were retrieved for full-text review, and 26 studies on four different CVSM solutions were included. Advanced AI levels were indicated on the websites of all four CVSM solutions. Five studies assessed algorithms with potential for applications as advanced AI algorithms in two of the CVSM solutions (50%), while 21 studies assessed algorithms with potential as simple AI in all four CVSM solutions (100%). Evidence on algorithms for advanced AI in CVSM is limited, revealing a discrepancy between promised AI levels and current algorithm capabilities.

Feasibility and Accuracy of Wrist-Worn Sensors for Perioperative Monitoring During and After Major Abdominal Surgery: An Observational Study

INTRODUCTION

Continuous, ambulatory perioperative monitoring using wearable devices has shown promise for earlier detection of physiological deterioration and postoperative complications, preventing 'failure-to-rescue'. This study aimed to compare the accuracy of vital signs measured by wrist-based wearables with gold standard measurements from vital signs monitors or nurse assessments in major abdominal surgery.

METHODS

Adult patients were eligible for inclusion in this prospective observational study validating the Empatica E4 wrist sensor intraoperatively and postoperatively. The primary outcomes were the 95% limits of agreement (LoA) between manual and device recordings of heart rate (HR) and temperature evaluated via Bland-Altman analysis. Secondary analysis was conducted using Clarke-Error grid analysis.

RESULTS

Overall, 31 patients were recruited, and 27 patients completed the study. The median duration of recording per patient was 70.3 h, and a total of 2112 h of data recording were completed. Wrist-based HR measurement was accurate and moderately precise (bias: 0.3 bpm; 95% LoA -15.5 to 17.1), but temperature measurement was neither accurate nor precise (bias -2.2°C; 95% LoA -6.0 to 1.6). On Clarke-Error grid analysis, 74.5% and 29.6% of HR and temperature measurements, respectively, fell within the acceptable range of reference standards.

CONCLUSIONS

Continuous perioperative monitoring of HR and temperature after major abdominal surgery using wrist-based sensors is feasible but was limited in this study by low precision. While wrist-based devices offer promise for the continuous monitoring of high-risk surgical patients, current technology is inadequate. Ongoing device hardware and software innovation with robust validation is required before such technologies can be routinely adopted in clinical practice.

Early detection of deteriorating patients in general wards through continuous contactless vital signs monitoring

Objective

To assess the efficacy of continuous contactless vital signs monitoring with an automated Early Warning System (EWS) in detecting clinical deterioration among patients in general wards.

Methods

A prospective observational cohort study was conducted in the medical unit of a tertiary care hospital in India, involving 706 patients over 84,448 monitoring hours. The study used a contactless ballistocardiography system (Dozee system) to continuously monitor heart rate, respiratory rate, and blood pressure. The study assessed total, mean, and median alerts at 24, 48, 72, 96, 120 h, and length of stay (LOS) before patient deterioration or discharge. It analyzed alert sensitivity and specificity, average time from initial alert to deterioration, and healthcare practitioners (HCP) activity. Study was registered with the Clinical Trials Registry-India CTRI/2022/10/046404.

Results

Out of 706 patients, 33 (5%) experienced clinical deterioration, while 673 (95%) did not. The deterioration group consistently had a higher number of alerts compared to those who were discharged normally, across all time-points. On average, the time between the initial alert and clinical deterioration was 16 h within the last 24 h preceding the event. The sensitivity of the Dozee-EWS varied between 67% and 94%. HCP spend 10% of their time on vital signs check and documentation.

Conclusions

This study suggests that utilizing contactless continuous vital signs monitoring with Dozee-EWS in general ward holds promise for enhancing the early detection of clinical deterioration. Further research is essential to evaluate the effectiveness across a wider range of clinical settings.

Remote Vital Sign Monitoring in Admission Avoidance Hospital at Home: A Systematic Review

OBJECTIVES

To examine randomized controlled trials (RCTs) of "hospital at home" (HAH) for admission avoidance in adults presenting with acute physical illness to identify the use of vital sign monitoring approaches and evidence for their effectiveness.

DESIGN

Systematic review.

SETTING AND PARTICIPANTS

This review compared strategies for vital sign monitoring in admission avoidance HAH for adults presenting with acute physical illness. Vital sign monitoring can support HAH acute multidisciplinary care by contributing to safety, determining requirement of further assessment, and guiding clinical decisions. There are a wide range of systems currently available, including reliable and automated continuous remote monitoring using wearable devices.

METHODS

Eligible studies were identified through updated database and trial registries searches (March 2, 2016, to February 15, 2023), and existing systematic reviews. Risk of bias was assessed using the Cochrane risk of bias 2 tool. Random effects meta-analyses were performed, and narrative summaries provided stratified by vital sign monitoring approach.

RESULTS

Twenty-one eligible RCTs (3459 participants) were identified. Two approaches to vital sign monitoring were characterized: manual and automated. Reporting was insufficient in the majority of studies for classification. For HAH compared to hospital care, 6-monthly mortality risk ratio (RR) was 0.94 (95% CI 0.78-1.12), 3-monthly readmission to hospital RR 1.02 (0.77-1.35), and length of stay mean difference 1.91 days (0.71-3.12). Readmission to hospital was reduced in the automated monitoring subgroup (RR 0.30 95% CI 0.11-0.86).

CONCLUSIONS AND IMPLICATIONS

This review highlights gaps in the reporting and evidence base informing remote vital sign monitoring in alternatives to admission for acute illness, despite expanding implementation in clinical practice. Although continuous vital sign monitoring using wearable devices may offer added benefit, its use in existing RCTs is limited. Recommendations for the implementation and evaluation of remote monitoring in future clinical trials are proposed.

Intensive Care Unit Without Walls

Critical illness is a continuum with different phases and trajectories. The "Intensive Care Unit (ICU) without walls" concept refers to a model whereby care is adjusted in response to the patient's needs, priorities, and preferences at each stage from detection, escalation, early decision making, treatment and organ support, followed by recovery and rehabilitation, within which all healthcare staff, and the patient are equal partners. The rapid response system incorporates monitoring and alerting tools, a multidisciplinary critical care outreach team and care bundles, supported with education and training, analytical and governance functions, which combine to optimise outcomes of critically ill patients, independent of location.

Wearable wireless continuous vital signs monitoring on the general ward

PURPOSE OF REVIEW

Wearable wireless sensors for continuous vital signs monitoring (CVSM) offer the potential for early identification of patient deterioration, especially in low-intensity care settings like general wards. This study aims to review advances in wearable CVSM - with a focus on the general ward - highlighting the technological characteristics of CVSM systems, user perspectives and impact on patient outcomes by exploring recent evidence.

RECENT FINDINGS

The accuracy of wearable sensors measuring vital signs exhibits variability, especially notable in ambulatory patients within hospital settings, and standard validation protocols are lacking. Usability of CMVS systems is critical for nurses and patients, highlighting the need for easy-to-use wearable sensors, and expansion of the number of measured vital signs. Current software systems lack integration with hospital IT infrastructures and workflow automation. Imperative enhancements involve nurse-friendly, less intrusive alarm strategies, and advanced decision support systems. Despite observed reductions in ICU admissions and Rapid Response Team calls, the impact on patient outcomes lacks robust statistical significance.

SUMMARY

Widespread implementation of CVSM systems on the general ward and potentially outside the hospital seems inevitable. Despite the theoretical benefits of CVSM systems in improving clinical outcomes, and supporting nursing care by optimizing clinical workflow efficiency, the demonstrated effects in clinical practice are mixed. This review highlights the existing challenges related to data quality, usability, implementation, integration, interpretation, and user perspectives, as well as the need for robust evidence to support their impact on patient outcomes, workflow and cost-effectiveness.

Enhancing discharge decision-making through continuous monitoring in an acute admission ward: a randomized controlled trial

In Acute Admission Wards, vital signs are commonly measured only intermittently. This may result in failure to detect early signs of patient deterioration and impede timely identification of patient stability, ultimately leading to prolonged stays and avoidable hospital admissions. Therefore, continuous vital sign monitoring may improve hospital efficacy. The objective of this randomized controlled trial was to evaluate the effect of continuous monitoring on the proportion of patients safely discharged home directly from an Acute Admission Ward. Patients were randomized to either the control group, which received usual care, or the sensor group, which additionally received continuous monitoring using a wearable sensor. The continuous measurements could be considered in discharge decision-making by physicians during the daily bedside rounds. Safe discharge was defined as no unplanned readmissions, emergency department revisits or deaths, within 30 days after discharge. Additionally, length of stay, the number of Intensive Care Unit admissions and Rapid Response Team calls were assessed. In total, 400 patients were randomized, of which 394 completed follow-up, with 196 assigned to the sensor group and 198 to the control group. The proportion of patients safely discharged home was 33.2% in the sensor group and 30.8% in the control group (p = 0.62). No significant differences were observed in secondary outcomes. The trial was terminated prematurely due to futility. In conclusion, continuous monitoring did not have an effect on the proportion of patients safely discharged from an Acute Admission Ward. Implementation challenges of continuous monitoring may have contributed to the lack of effect observed. Trial registration: https://clinicaltrials.gov/ct2/show/NCT05181111 . Registered: January 6, 2022.

Unexpected intensive care unit admission after surgery: impact on clinical outcome

PURPOSE OF REVIEW

This review is focused on providing insights into unplanned admission to the intensive care unit (ICU) after surgery, including its causes, effects on clinical outcome, and potential strategies to mitigate the strain on healthcare systems.

RECENT FINDINGS

Postoperative unplanned ICU admission results from a combination of several factors including patient's clinical status, the type of surgical procedure, the level of supportive care and clinical monitoring outside the ICU, and the unexpected occurrence of major perioperative and postoperative complications. The actual impact of unplanned admission to ICU after surgery on clinical outcome remains uncertain, given the conflicting results from several observational studies and recent randomized clinical trials. Nonetheless, unplanned ICU admission after surgery results a significant strain on hospital resources. Consequently, this issue should be addressed in hospital policy with the aim of implementing preoperative risk assessment and patient evaluation, effective communication, vigilant supervision, and the promotion of cooperative healthcare.

SUMMARY

Unplanned ICU admission after surgery is a multifactorial phenomenon that imposes a significant burden on healthcare systems without a clear impact on clinical outcome. Thus, the early identification of patient necessitating ICU interventions is imperative.

Impact of continuous and wireless monitoring of vital signs on clinical outcomes: a propensity-matched observational study of surgical ward patients

BACKGROUND

Continuous and wireless vital sign monitoring is superior to intermittent monitoring in detecting vital sign abnormalities; however, the impact on clinical outcomes has not been established.

METHODS

We performed a propensity-matched analysis of data describing patients admitted to general surgical wards between January 2018 and December 2019 at a single, tertiary medical centre in the USA. The primary outcome was a composite of in-hospital mortality or ICU transfer during hospitalisation. Secondary outcomes were the odds of individual components of the primary outcome, and heart failure, myocardial infarction, acute kidney injury, and rapid response team activations. Data are presented as odds ratios (ORs) with 95% confidence intervals (CIs) and n (%).

RESULTS

We initially screened a population of 34,636 patients (mean age 58.3 (Range 18-101) yr, 16,456 (47.5%) women. After propensity matching, intermittent monitoring (n=12 345) was associated with increased risk of a composite of mortality or ICU admission (OR 3.42, 95% CI 3.19-3.67; P<0.001), and heart failure (OR 1.48, 95% CI 1.21-1.81; P<0.001), myocardial infarction (OR 3.87, 95% CI 2.71-5.71; P<0.001), and acute kidney injury (OR 1.32, 95% CI 1.09-1.57; P<0.001) compared with continuous wireless monitoring (n=7955). The odds of rapid response team intervention were similar in both groups (OR 0.86, 95% CI 0.79-1.06; P=0.726).

CONCLUSIONS

Patients who received continuous ward monitoring were less likely to die or be admitted to ICU than those who received intermittent monitoring. These findings should be confirmed in prospective randomised trials.

Workload associated with manual assessment of vital signs as compared with continuous wireless monitoring

BACKGROUND

Vital sign monitoring is considered an essential aspect of clinical care in hospitals. In general wards, this relies on intermittent manual assessments performed by clinical staff at intervals of up to 12 h. In recent years, continuous monitoring of vital signs has been introduced to the clinic, with improved patient outcomes being one of several potential benefits. The aim of this study was to determine the workload difference between continuous monitoring and manual monitoring of vital signs as part of the National Early Warning Score (NEWS).

METHODS

Three wireless sensors continuously monitored blood pressure, heart rate, respiratory rate, and peripheral oxygen saturation in 20 patients admitted to the general hospital ward. The duration needed for equipment set-up and maintenance for continuous monitoring in a 24-h period was recorded and compared with the time spent on manual assessments and documentation of vital signs performed by clinical staff according to the NEWS.

RESULTS

The time used for continuous monitoring was 6.0 (IQR 3.2; 7.2) min per patient per day vs. 14 (9.7; 32) min per patient per day for the NEWS. Median difference in duration for monitoring of vital signs was 9.9 (95% CI 5.6; 21) min per patient per day between NEWS and continuous monitoring (p < .001). Time used for continuous monitoring in isolated patients was 6.6 (4.6; 12) min per patient per day as compared with 22 (9.7; 94) min per patient per day for NEWS.

CONCLUSION

The use of continuous monitoring was associated with a significant reduction in workload in terms of time for monitoring as compared with manual assessment of vital signs.

Outcomes in patients receiving continuous monitoring of vital signs on general wards: A systematic review and meta-analysis of randomised controlled trials

Objective

The timely identification of deterioration on general wards is crucial to patient care with each hour of delay independently associated with increased risk of death. The introduction of continuous monitoring of patient vital signs on general wards, currently not standard care, may improve patient outcomes. Our aim was to investigate whether patients on general wards receiving continuous vital signs monitoring have better outcomes than patients receiving usual care.

Methods

Meta-analysis of randomised controlled trials comparing non-critical care patients receiving continuous monitoring of vital signs to usual care. We searched Medline, Embase, and Web of Science, and assessed risk of bias with version 2 of the Cochrane risk-of-bias tool for randomised trials. In addition to measures related to the early detection of deterioration, we planned to present all patient outcomes reported by the clinical trials included.

Results

We included seven trials involving 1284 participants. There were no statistically significant differences in the four outcomes pooled. Comparing continuously monitored to normal care, the pooled odds for hospital mortality, major event/complication, and HDU/ICU admission was 0.95 (95% CI 0.59-1.53, p = 0.84; 660 participants, 3 studies), 0.71 (95% CI 0.38-1.31, p = 0.27; 948 participants, 4 studies) and 0.82 (95% CI 0.25-2.67, p = 0.74; 655 participants, 4 studies), respectively. The mean difference for length of stay was 2.12 days lower (95% CI -5.56 to 1.32, p = 0.23; 1034 participants, 6 studies).

Conclusion

We found no significant improvements in outcomes for patients continuously monitored compared to usual care. Further research is needed to understand what modalities of continuous monitoring may influence outcomes and investigate the implications of a telepresence service and multi-parameter scoring system.

Registration

PROSPERO CRD42023458656.

Simple, miniaturized biosensors for wireless mapping of thermoregulatory responses

Temperature is the most commonly collected vital sign in all of clinical medicine; it plays a critical role in care decisions related to topics ranging from infection to inflammation, sleep, and fertility. Most assessments of body temperature occur at isolated anatomical locations (e.g. axilla, rectum, temporal artery, or oral cavity). Even this relatively primitive mode for monitoring can be challenging with vulnerable patient populations due to physical encumbrances and artifacts associated with the sizes, weights, shapes and mechanical properties of the sensors and, for continuous monitoring, their hard-wired interfaces to data collection units. Here, we introduce a simple, miniaturized, lightweight sensor as a wireless alternative, designed to address demanding applications such as those related to the care of neonates in high ambient humidity environments with radiant heating found in incubators in intensive care units. Such devices can be deployed onto specific anatomical locations of premature infants for homeostatic assessments. The estimated core body temperature aligns, to within 0.05 °C, with clinical grade, wired sensors, consistent with regulatory medical device requirements. Time-synchronized, multi-device operation across multiple body locations supports continuous, full-body measurements of spatio-temporal variations in temperature and additional modes of determining tissue health status in the context of sepsis detection and various environmental exposures. In addition to thermal sensing, these same devices support measurements of a range of other essential vital signs derived from thermo-mechanical coupling to the skin, for applications ranging from neonatal and infant care to sleep medicine and even pulmonary medicine.

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.

Implementing Wearable Sensors for Clinical Application at a Surgical Ward: Points to Consider before Starting

Incorporating technology into healthcare processes is necessary to ensure the availability of high-quality care in the future. Wearable sensors are an example of such technology that could decrease workload, enable early detection of patient deterioration, and support clinical decision making by healthcare professionals. These sensors unlock continuous monitoring of vital signs, such as heart rate, respiration rate, blood oxygen saturation, temperature, and physical activity. However, broad and successful application of wearable sensors on the surgical ward is currently lacking. This may be related to the complexity, especially when it comes to replacing manual measurements by healthcare professionals. This report provides practical guidance to support peers before starting with the clinical application of wearable sensors in the surgical ward. For this purpose, the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework of technology adoption and innovations in healthcare organizations is used, combining existing literature and our own experience in this field over the past years. Specifically, the relevant topics are discussed per domain, and key lessons are subsequently summarized.

Continuous monitoring of patients in and after the acute admission ward to improve clinical pathways: study protocol for a randomized controlled trial (Optimal-AAW)

BACKGROUND

Because of high demand on hospital beds, hospitals seek to reduce patients' length of stay (LOS) while preserving the quality of care. In addition to usual intermittent vital sign monitoring, continuous monitoring might help to assess the patient's risk of deterioration, in order to improve the discharge process and reduce LOS. The primary aim of this monocenter randomized controlled trial is to assess the effect of continuous monitoring in an acute admission ward (AAW) on the percentage of patients who are discharged safely.

METHODS

A total of 800 patients admitted to the AAW, for whom it is equivocal whether they can be discharged directly after their AAW stay, will be randomized to either receive usual care without (control group) or with additional continuous monitoring of heart rate, respiratory rate, posture, and activity, using a wearable sensor (sensor group). Continuous monitoring data are provided to healthcare professionals and used in the discharge decision. The wearable sensor keeps collecting data for 14 days. After 14 days, all patients fill in a questionnaire to assess healthcare use after discharge and, if applicable, their experience with the wearable sensor. The primary outcome is the difference in the percentage of patients who are safely discharged home directly from the AAW between the control and sensor group. Secondary outcomes include hospital LOS, AAW LOS, intensive care unit (ICU) admissions, Rapid Response Team calls, and unplanned readmissions within 30 days. Furthermore, facilitators and barriers for implementing continuous monitoring in the AAW and at home will be investigated.

DISCUSSION

Clinical effects of continuous monitoring have already been investigated in specific patient populations for multiple purposes, e.g., in reducing the number of ICU admissions. However, to our knowledge, this is the first Randomized Controlled Trial to investigate effects of continuous monitoring in a broad patient population in the AAW.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT05181111 . Registered on 6 January 2022. Start of recruitment: 7 December 2021.

NURSE-LED proactive rounding and automatic early-warning score systems to prevent resuscitation incidences among Adults in ward-based Hospitalised patients

Objectives

In this study, we investigated the impact of critical care outreach implemented to overcome the problem of rapid response system (RRS) activation. The aim was to evaluate the impact of nurse-led proactive rounding on the rate of adverse events in a hospital setting using an automatic early-warning score system, without a call-activated team.

Methods

This observational study was conducted at a university hospital in Japan. Beginning in September 2019, critical care outreach via nurse-led proactive rounding of the general ward was conducted, using an automatic early-warning score system. We retrospectively assessed the computerised records of all inpatient days (N = 497,284) of adult inpatients admitted to the hospital from September 2017 to 2020. We compared the adverse event occurrences before and after implementation of the critical care outreach program. The main outcome measures were: unexpected death in the general ward, code blue (an in-hospital resuscitation request code directed towards all staff via broadcast) for non-intensive care unit inpatients and unexpected intensive care unit admissions from the general ward. The secondary outcome was the proportion of patients who received respiratory rate measurement.

Results

The incidence rate ratios of the occurrence of unexpected deaths (0.19, 95% confidence interval: 0.04-0.57) and code blue in the general ward (0.15, 95% confidence interval: 0.025-0.50) decreased. There was no change in unexpected intensive care unit admissions from the general ward (1.25, confidence interval: 0.84-1.82). The proportion of patients who received respiratory rate measurement increased (10.2% vs 16.2%).

Conclusion

Our results suggest that in RRSs, drastic control of the failure of the mechanism to activate a response team may produce positive outcomes. Proactive rounding that bypasses the mechanism to activate a response team component of RRSs may relieve ward nurses of activation failure responsibility and help them overcome the hierarchical hospital structure.

Interpretation of continuously measured vital signs data of COVID-19 patients by nurses and physicians at the general ward: A mixed methods study

BACKGROUND

Continuous monitoring of vital signs is introduced at general hospital wards to detect patient deterioration. Interpretation and response currently rely on experience and expert opinion. This study aims to determine whether consensus exist among hospital professionals regarding the interpretation of vital signs of COVID-19 patients. In addition, we assessed the ability to recognise respiratory insufficiency and evaluated the interpretation process.

METHODS

We performed a mixed methods study including 24 hospital professionals (6 nurses, 6 junior physicians, 6 internal medicine specialists, 6 ICU nurses). Each participant was presented with 20 cases of COVID-19 patients, including 4 or 8 hours of continuously measured vital signs data. Participants estimated the patient's situation ('improving', 'stable', or 'deteriorating') and the possibility of developing respiratory insufficiency. Subsequently, a semi-structured interview was held focussing on the interpretation process. Consensus was assessed using Krippendorff's alpha. For the estimation of respiratory insufficiency, we calculated the mean positive/negative predictive value. Interviews were analysed using inductive thematic analysis.

RESULTS

We found no consensus regarding the patient's situation (α 0.41, 95%CI 0.29-0.52). The mean positive predictive value for respiratory insufficiency was high (0.91, 95%CI 0.86-0.97), but the negative predictive value was 0.66 (95%CI 0.44-0.88). In the interviews, two themes regarding the interpretation process emerged. "Interpretation of deviations" included the strategies participants use to determine stability, focused on finding deviations in data. "Inability to see the patient" entailed the need of hospital professionals to perform a patient evaluation when estimating a patient's situation.

CONCLUSION

The interpretation of continuously measured vital signs by hospital professionals, and recognition of respiratory insufficiency using these data, is variable, which might be the result of different interpretation strategies, uncertainty regarding deviations, and not being able to see the patient. Protocols and training could help to uniform interpretation, but decision support systems might be necessary to find signs of deterioration that might otherwise go unnoticed.

Remote Home Monitoring of Continuous Vital Sign Measurements by Wearables in Patients Discharged After Colorectal Surgery: Observational Feasibility Study

BACKGROUND

Hospital stays after colorectal surgery are increasingly being reduced by enhanced recovery and early discharge protocols. As a result, postoperative complications may frequently manifest after discharge in the home setting, potentially leading to emergency room presentations and readmissions. Virtual care interventions after hospital discharge may capture clinical deterioration at an early stage and hold promise for the prevention of readmissions and overall better outcomes. Recent technological advances have enabled continuous vital sign monitoring by wearable wireless sensor devices. However, the potential of these devices for virtual care interventions for patients discharged after colorectal surgery is currently unknown.

OBJECTIVE

We aimed to determine the feasibility of a virtual care intervention consisting of continuous vital sign monitoring with wearable wireless sensors and teleconsultations for patients discharged after colorectal surgery.

METHODS

In a single-center observational cohort study, patients were monitored at home for 5 consecutive days after discharge. Daily vital sign trend assessments and telephone consultations were performed by a remote patient-monitoring department. Intervention performance was evaluated by analyzing vital sign trend assessments and telephone consultation reports. Outcomes were categorized as "no concern," "slight concern," or "serious concern." Serious concern prompted contact with the surgeon on call. In addition, the quality of the vital sign data was determined, and the patient experience was evaluated.

RESULTS

Among 21 patients who participated in this study, 104 of 105 (99%) measurements of vital sign trends were successful. Of these 104 vital sign trend assessments, 68% (n=71) did not raise any concern, 16% (n=17) were unable to be assessed because of data loss, and none led to contacting the surgeon. Of 62 of 63 (98%) successfully performed telephone consultations, 53 (86%) did not raise any concerns and only 1 resulted in contacting the surgeon. A 68% agreement was found between vital sign trend assessments and telephone consultations. Overall completeness of the 2347 hours of vital sign trend data was 46.3% (range 5%-100%). Patient satisfaction score was 8 (IQR 7-9) of 10.

CONCLUSIONS

A home monitoring intervention of patients discharged after colorectal surgery was found to be feasible, given its high performance and high patient acceptability. However, the intervention design needs further optimization before the true value of remote monitoring for early discharge protocols, prevention of readmissions, and overall patient outcomes can be adequately determined.

Process Evaluation of a Wireless Wearable Continuous Vital Signs Monitoring Intervention in 2 General Hospital Wards: Mixed Methods Study

BACKGROUND

Continuous monitoring of vital signs (CMVS) using wearable wireless sensors is increasingly available to patients in general wards and can improve outcomes and reduce nurse workload. To assess the potential impact of such systems, successful implementation is important. We developed a CMVS intervention and implementation strategy and evaluated its success in 2 general wards.

OBJECTIVE

We aimed to assess and compare intervention fidelity in 2 wards (internal medicine and general surgery) of a large teaching hospital.

METHODS

A mixed methods sequential explanatory design was used. After thorough training and preparation, CMVS was implemented-in parallel with the standard intermittent manual measurements-and executed for 6 months in each ward. Heart rate and respiratory rate were measured using a chest-worn wearable sensor, and vital sign trends were visualized on a digital platform. Trends were routinely assessed and reported each nursing shift without automated alarms. The primary outcome was intervention fidelity, defined as the proportion of written reports and related nurse activities in case of deviating trends comparing early (months 1-2), mid- (months 3-4), and late (months 5-6) implementation periods. Explanatory interviews with nurses were conducted.

RESULTS

The implementation strategy was executed as planned. A total of 358 patients were included, resulting in 45,113 monitored hours during 6142 nurse shifts. In total, 10.3% (37/358) of the sensors were replaced prematurely because of technical failure. Mean intervention fidelity was 70.7% (SD 20.4%) and higher in the surgical ward (73.6%, SD 18.1% vs 64.1%, SD 23.7%; P<.001). Fidelity decreased over the implementation period in the internal medicine ward (76%, 57%, and 48% at early, mid-, and late implementation, respectively; P<.001) but not significantly in the surgical ward (76% at early implementation vs 74% at midimplementation [P=.56] vs 70.7% at late implementation [P=.07]). No nursing activities were needed based on vital sign trends for 68.7% (246/358) of the patients. In 174 reports of 31.3% (112/358) of the patients, observed deviating trends led to 101 additional bedside assessments of patients and 73 consultations by physicians. The main themes that emerged during interviews (n=21) included the relative priority of CMVS in nurse work, the importance of nursing assessment, the relatively limited perceived benefits for patient care, and experienced mediocre usability of the technology.

CONCLUSIONS

We successfully implemented a system for CMVS at scale in 2 hospital wards, but our results show that intervention fidelity decreased over time, more in the internal medicine ward than in the surgical ward. This decrease appeared to depend on multiple ward-specific factors. Nurses' perceptions regarding the value and benefits of the intervention varied. Implications for optimal implementation of CMVS include engaging nurses early, seamless integration into electronic health records, and sophisticated decision support tools for vital sign trend interpretation.

Clinical prediction rules for adverse evolution in patients with COVID-19 by the Omicron variant

OBJECTIVE

We identify factors related to SARS-CoV-2 infection linked to hospitalization, ICU admission, and mortality and develop clinical prediction rules.

METHODS

Retrospective cohort study of 380,081 patients with SARS-CoV-2 infection from March 1, 2020 to January 9, 2022, including a subsample of 46,402 patients who attended Emergency Departments (EDs) having data on vital signs. For derivation and external validation of the prediction rule, two different periods were considered: before and after emergence of the Omicron variant, respectively. Data collected included sociodemographic data, COVID-19 vaccination status, baseline comorbidities and treatments, other background data and vital signs at triage at EDs. The predictive models for the EDs and the whole samples were developed using multivariate logistic regression models using Lasso penalization.

RESULTS

In the multivariable models, common predictive factors of death among EDs patients were greater age; being male; having no vaccination, dementia; heart failure; liver and kidney disease; hemiplegia or paraplegia; coagulopathy; interstitial pulmonary disease; malignant tumors; use chronic systemic use of steroids, higher temperature, low O2 saturation and altered blood pressure-heart rate. The predictors of an adverse evolution were the same, with the exception of liver disease and the inclusion of cystic fibrosis. Similar predictors were found to be related to hospital admission, including liver disease, arterial hypertension, and basal prescription of immunosuppressants. Similarly, models for the whole sample, without vital signs, are presented.

CONCLUSIONS

We propose risk scales, based on basic information, easily-calculable, high-predictive that also function with the current Omicron variant and may help manage such patients in primary, emergency, and hospital care.

The impact of continuous wireless monitoring on adverse device effects in medical and surgical wards: a review of current evidence

Novel technologies allow continuous wireless monitoring systems (CWMS) to measure vital signs and these systems might be favorable compared to intermittent monitoring regarding improving outcomes. However, device safety needs to be validated because uncertain evidence challenges the clinical implementation of CWMS. This review investigates the frequency of device-related adverse events in patients monitored with CWMS in general hospital wards. Systematic literature searches were conducted in PubMed and Embase. We included trials of adult patients in general hospital wards monitored with CWMS. Our primary outcome was the frequency of unanticipated serious adverse device effects (USADEs). Secondary outcomes were adverse device effects (ADEs) and serious adverse device effects (SADE). Data were extracted from eligible studies and descriptive statistics were applied to analyze the data. Seven studies were eligible for inclusion with a total of 1485 patients monitored by CWMS. Of these patients, 54 patients experienced ADEs (3.6%, 95% CI 2.8-4.7%) and no USADEs or SADEs were reported (0%, 95% CI 0-0.31%). The studies of the SensiumVitals® patch, the iThermonitor, and the ViSi Mobile® device reported 28 (9%), 25 (5%), and 1 (3%) ADEs, respectively. No ADEs were reported using the HealthPatch, WARD 24/7 system, or Coviden Alarm Management. Current evidence suggests that CWMS are safe to use but systematic reporting of all adverse device effects is warranted.

Prediction of intrapartum fever using continuously monitored vital signs and heart rate variability

Objectives

Neonatal early onset sepsis (EOS), bacterial infection during the first seven days of life, is difficult to diagnose because presenting signs are non-specific, but early diagnosis before birth can direct life-saving treatment for mother and baby. Specifically, maternal fever during labor from placental infection is the strongest predictor of EOS. Alterations in maternal heart rate variability (HRV) may precede development of intrapartum fever, enabling incipient EOS detection. The objective of this work was to build a predictive model for intrapartum fever.

Methods

Continuously measured temperature, heart rate, and beat-to-beat RR intervals were obtained from wireless sensors on women (n = 141) in labor; traditional manual vital signs were taken every 3-6 hours. Validated measures of HRV were calculated in moving 5-minute windows of RR intervals: standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive differences (RMSSD) between normal heartbeats.

Results

Fever (>38.0 °C) was detected by manual or continuous measurements in 48 women. Compared to afebrile mothers, average SDNN and RMSSD in febrile mothers decreased significantly (p < 0.001) at 2 and 3 hours before fever onset, respectively. This observed HRV divergence and raw recorded vitals were applied to a logistic regression model at various time horizons, up to 4-5 hours before fever onset. Model performance increased with decreasing time horizons, and a model built using continuous vital signs as input variables consistently outperformed a model built from episodic vital signs.

Conclusions

HRV-based predictive models could identify mothers at risk for fever and infants at risk for EOS, guiding maternal antibiotic prophylaxis and neonatal monitoring.

Nurses' experiences with continuous vital sign monitoring on the general surgical ward: a qualitative study based on the Behaviour Change Wheel

Background

To support early recognition of clinical deterioration on a general ward continuous vital signs monitoring (CMVS) systems using wearable devices are increasingly being investigated. Although nurses play a crucial role in successful implementation, reported nurse adoption and acceptance scores vary significantly. In-depth insight into the perspectives of nurses regarding CMVS is lacking. To this end, we applied a theoretical approach for behaviour change derived from the Behaviour Change Wheel (BCW).

Aim

To provide insight in the capability, opportunity and motivation of nurses working with CMVS, in order to inform future implementation efforts.

Methods

A qualitative study was conducted, including twelve nurses of a surgical ward in a tertiary teaching hospital with previous experience of working with CMVS. Semi-structured interviews were audiotaped, transcribed verbatim, and analysed using thematic analysis. The results were mapped onto the Capability, Opportunity, Motivation – Behaviour (COM-B) model of the BCW.

Results

Five key themes emerged. The theme ‘Learning and coaching on the job’ linked to Capability. Nurses favoured learning about CVSM by dealing with it in daily practice. Receiving bedside guidance and coaching was perceived as important. The theme ‘interpretation of vital sign trends’ also linked to Capability. Nurses mentioned the novelty of monitoring vital sign trends of patients on wards. The theme ‘Management of alarms’ linked to Opportunity. Nurses perceived the (false) alarms generated by the system as excessive resulting in feelings of irritation and uncertainty. The theme ‘Integration and compatibility with clinical workflow’ linked to Opportunity. CVSM was experienced as helpful and easy to use, although integration in mobile devices and the EMR was highly favoured and the management of clinical workflows would need improvement. The theme ‘Added value for nursing care’ linked to Motivation. All nurses recognized the potential added value of CVSM for postoperative care.

Conclusion

Our findings suggest all parts of the COM-B model should be considered when implementing CVSM on general wards. When the themes in Capability and Opportunity are not properly addressed by selecting interventions and policy categories, this may negatively influence the Motivation and may compromise successful implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12912-022-00837-x.

Feasibility of wireless continuous monitoring of vital signs without using alarms on a general surgical ward: A mixed methods study

Background

Wireless continuous vital sign monitoring by wearable devices have recently become available for patients on general wards to promote timely detection of clinical deterioration. Many continuous monitoring systems use conventional threshold alarm settings to alert nurses in case of deviating vital signs. However, frequent false alarms often lead to alarm fatigue and inefficiencies in the workplace. The aim of this study was to determine the feasibility of continuous vital sign monitoring without the use of alarms, thereby exclusively relying on interval trend monitoring.

Methods

This explanatory sequential mixed methods study was conducted at an abdominal surgical ward of a tertiary teaching hospital. Heart rate and respiratory rate of patients were measured every minute by a wearable sensor. Trends were visualized and assessed six times per day by nurses and once a day by doctors during morning rounds. Instead of using alarms we focused exclusively on regular vital sign trend analysis by nurses and doctors. Primary outcome was feasibility in terms of acceptability by professionals, assessed by the Usefulness, Satisfaction and Ease of Use questionnaire and further explored in two focus groups, as well as fidelity.

Results

A total of 56 patients were monitored and in 80.5% (n = 536) of nurses’ work shifts the trends assessments were documented. All deviating trends (n = 17) were recognized in time. Professionals (N = 46) considered continuous monitoring satisfying (4.8±1.0 on a 1–7 Likert-scale) and were willing to use the technology. Although insight into vital sign trends allowed faster anticipation and action upon changed patient status, professionals were neutral about usefulness (4.4±1.0). They found continuous monitoring easy to use (4.7±0.8) and easy to learn (5.3±1.0) but indicated the need for gaining practical experience. Nurses considered the use of alarms for deviating vital signs unnecessary, when trends were regularly assessed and reported.

Conclusion

We demonstrated that continuous vital signs trend monitoring without using alarms was feasible in the general ward setting, thereby avoiding unnecessary alarms and preventing alarm fatigue. When monitoring in a general ward setting, the standard use of alarms may therefore be reconsidered.