Cost utility analysis of continuous and intermittent versus intermittent vital signs monitoring in patients admitted to surgical wards

Effectiveness of Remote Patient Monitoring Equipped With an Early Warning System in Tertiary Care Hospital Wards: Retrospective Cohort Study

BACKGROUND

Monitoring vital signs in hospitalized patients is crucial for evaluating their clinical condition. While early warning scores like the modified early warning score (MEWS) are typically calculated 3 to 4 times daily through spot checks, they might not promptly identify early deterioration. Leveraging technologies that provide continuous monitoring of vital signs, combined with an early warning system, has the potential to identify clinical deterioration sooner. This approach empowers health care providers to intervene promptly and effectively.

OBJECTIVE

This study aimed to assess the impact of a Remote Patient Monitoring System (RPMS) with an automated early warning system (R-EWS) on patient safety in noncritical care at a tertiary hospital. R-EWS performance was compared with a simulated Modified Early Warning System (S-MEWS) and a simulated threshold-based alert system (S-Threshold).

METHODS

Patient outcomes, including intensive care unit (ICU) transfers due to deterioration and discharges for nondeteriorating cases, were analyzed in Ramaiah Memorial Hospital's general wards with RPMS. Sensitivity, specificity, chi-square test for alert frequency distribution equality, and the average time from the first alert to ICU transfer in the last 24 hours was determined. Alert and patient distribution by tiers and vitals in R-EWS groups were examined.

RESULTS

Analyzing 905 patients, including 38 with deteriorations, R-EWS, S-Threshold, and S-MEWS generated more alerts for deteriorating cases. R-EWS showed high sensitivity (97.37%) and low specificity (23.41%), S-Threshold had perfect sensitivity (100%) but low specificity (0.46%), and S-MEWS demonstrated moderate sensitivity (47.37%) and high specificity (81.31%). The average time from initial alert to clinical deterioration was at least 18 hours for RPMS and S-Threshold in deteriorating participants. R-EWS had increased alert frequency and a higher proportion of critical alerts for deteriorating cases.

CONCLUSIONS

This study underscores R-EWS role in early deterioration detection, emphasizing timely interventions for improved patient outcomes. Continuous monitoring enhances patient safety and optimizes care quality.

Economic impact of a vision-based patient monitoring system across five NHS mental health trusts

A vision-based patient monitoring system (VBPMS), Oxevision, has been introduced in approximately half of National Health Service (NHS) mental health trusts in England. A VBPMS is an assistive tool that supports patient safety by enabling non-contact physiological and physical monitoring. The system aims to help staff deliver safer, higher-quality and more efficient care. This paper summarises the potential health economic impact of using a VBPMS to support clinical practice in two inpatient settings: acute mental health and older adult mental health services. The economic model used a cost calculator approach to evaluate the potential impact of introducing a VBPMS into clinical practice, compared with clinical practice without a VBPMS. The analysis captured the cost differences in night-time observations, one-to-one continuous observations, self-harm incidents, and bedroom falls at night, including those resulting in A&E visits and emergency service callouts. The analysis is based on before and after studies conducted at five mental health NHS trusts, including acute mental health and older adult mental health services. Our findings indicate that the use of a VBPMS results in more efficient night-time observations and reductions in one-to-one observations, self-harm incidents, bedroom falls at night, and A&E visits and emergency service callouts from night-time falls. Substantial staff time in acute mental health and older adult mental health services is spent performing night-time observations, one-to-one observations, and managing incidents. The use of a VBPMS could lead to cost savings and a positive return on investment for NHS mental health trusts. The results do not incorporate all of the potential benefits associated with the use of a VBPMS, such as reductions in medication and length of hospital stay, plus the potential to avoid adverse events which would otherwise have a detrimental impact on a patient's quality of life.

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.

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.

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.

Feasibility, performance and acceptability of an innovative vital signs monitor for sick newborns in Western Kenya: A mixed-methods study

Introduction

Low- and middle-income countries (LMICs) account for 99% of the global neonatal mortality. Limited access to advanced technology, such as bedside patient monitors contributes to disproportionately poor outcomes for critically ill newborns in LMICs. We designed a study to assess the feasibility, performance, and acceptability of a low-cost wireless wearable technology for continuous monitoring of sick newborns in resource-limited settings.

Methods

This was a mixed-methods implementation study conducted between March and April 2021 at two health facilities in Western Kenya. Inclusion criteria for newborns monitored included: age 0 to 28 days, birthweight ≥2.0 kg, low-to-moderate severity of illness at admission and the guardian's willingness to provide informed consent. Medical staff who participated in monitoring the newborns were surveyed about their experience with the technology. We used descriptive statistics to summarize our quantitative findings and qualitative data was coded and analyzed as an iterative process to summarize quotes on user acceptability.

Results

The results of the study demonstrated that adoption of neoGuard was feasible and acceptable in this setting. Medical staff described the technology as safe, user-friendly and efficient, after successfully monitoring 134 newborns. Despite the positive user experience, we did observe some notable technology performance issues such as a high percentage of missing vital signs data.

Conclusion

The results of this study were critical in informing the iterative process of refining and validating an innovative vital signs monitor for patients in resource-limited settings. Further research and development are underway to optimize neoGuard's performance and to examine its clinical impact and cost effectiveness.

Effect of Intelligent Vital Sign Monitoring System on Postoperative Nursing Care of Severe Patients

In order to study the observation of postoperative vital sign data of critically ill patients, this paper developed a set of vital sign data acquisition system based on intelligence and realized the design of vital sign data acquisition system APP based on Android Studio programming software, which was used to realize the information collection of vital sign data of patients. PDA is connected with a vital sign measuring equipment through Bluetooth. The patient's wristband is scanned with PDA to read the patient's information, and then the measured vital sign data are obtained automatically by measuring APP. The initial alarm value is set to be greater than 1%, and it needs more than 60 and less than or equal to 120 RR interval data to judge apnea. Information collection of intelligent vital sign detection can not only save the time of nursing staff but also improve the nursing quality.

Beyond wellness monitoring: Continuous multiparameter remote automated monitoring of patients

The pursuit of more efficient patient-friendly health systems and reductions in tertiary health services use has seen enormous growth in the application and study of remote patient monitoring systems for cardiovascular patient care. While there are many consumer-grade products available to monitor patient wellness, the regulation of these technologies varies considerably, with most products having little to no evaluation data. As the science and practice of virtual care continues to evolve, clinicians and researchers can benefit from an understanding of more comprehensive solutions, capable of monitoring three or more biophysical parameters (e.g., oxygen saturation, heart rate) continuously and simultaneously. These devices, herein referred to as continuous multiparameter remote automated monitoring (CM-RAM) devices, have the potential to revolutionize virtual patient care. Through seamless integration of multiple biophysical signals, CM-RAM technologies can allow for the acquisition of high-volume big data for the development of algorithms to facilitate early detection of negative changes in patient health status and timely clinician response. In this article, we review key principles, architecture, and components of CM-RAM technologies. Work to date in this field and related implications are also presented, including strategic priorities for advancing the science and practice of CM-RAM.

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

BACKGROUND

Timely recognition of the deteriorating inpatient remains challenging. Wearable monitoring systems (WMS) may augment current monitoring practices. However, there are many barriers to implementation in the hospital environment, and evidence describing the clinical impact of WMS on deterioration detection and patient outcome remains unclear.

OBJECTIVE

To assess the impact of vital-sign monitoring on detection of deterioration and related clinical outcomes in hospitalised patients using WMS, in comparison with standard care.

METHODS

A systematic search was conducted in August 2020 using MEDLINE, Embase, CINAHL, Cochrane Database of Systematic Reviews, CENTRAL, Health Technology Assessment databases and grey literature. Studies comparing the use of WMS against standard care for deterioration detection and related clinical outcomes in hospitalised patients were included. Deterioration related outcomes (primary) included unplanned intensive care admissions, rapid response team or cardiac arrest activation, total and major complications rate. Other clinical outcomes (secondary) included in-hospital mortality and hospital length of stay. Exploratory outcomes included alerting system parameters and clinical trial registry information.

RESULTS

Of 8706 citations, 10 studies with different designs met the inclusion criteria, of which 7 were included in the meta-analyses. Overall study quality was moderate. The meta-analysis indicated that the WMS, when compared with standard care, was not associated with significant reductions in intensive care transfers (risk ratio, RR 0.87; 95% confidence interval, CI 0.66-1.15), rapid response or cardiac arrest team activation (RR 0.84; 95% CI 0.69-1.01), total (RR 0.77; 95% CI 0.44-1.32) and major (RR 0.55; 95% CI 0.24-1.30) complications prevalence. There was also no statistically significant association with reduced mortality (RR 0.48; 95% CI 0.18-1.29) and hospital length of stay (mean difference, MD - 0.09; 95% CI - 0.43 to 0.44).

CONCLUSION

This systematic review indicates that there is no current evidence that implementation of WMS impacts early deterioration detection and associated clinical outcomes, as differing design/quality of available studies and diversity of outcome measures make it difficult to reach a definite conclusion. Our narrative findings suggested that alarms should be adjusted to minimise false alarms and promote rapid clinical action in response to deterioration. PROSPERO Registration number: CRD42020188633 .

Protocol for a systematic review assessing ambulatory vital sign monitoring impact on deterioration detection and related clinical outcomes in hospitalised patients

INTRODUCTION

Ambulatory monitoring systems (AMS) can facilitate early detection of clinical deterioration, and have the potential to improve hospitalised patient outcomes. The objective of this systematic review is to assess the impact of vital signs monitoring on detection of deterioration and related outcomes in hospitalised patients using AMS, in comparison with standard care.

METHODS AND ANALYSIS

A systematic search was conducted on 27 August 2020 in MEDLINE, Embase, CINAHL, Cochrane Database of Systematic Reviews, CENTRAL and Health Technology Assessment databases, as well as grey literature. Search results will be reviewed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis checklist for systematic reviews. Studies comparing the use of ambulatory monitoring devices against standard care for deterioration detection and related clinical outcomes in hospitalised patients will be included and further clinical and other outcomes will also be explored. Deterioration-related outcomes may include (but not limited to) unplanned intensive care admissions, rapid response team activation and unscheduled emergency interventions, as defined by the included studies. Two reviewers will independently extract study data and assess the quality and risk of bias of included studies. Where possible, a meta-analysis will be conducted and quantitative results presented. Alternatively, a narrative synthesis will be reported.

ETHICS AND DISSEMINATION

Ethical approval is not required for this study as no primary data will be collected. This study is part of our virtual High Dependency Unit project and will be disseminated through peer-reviewed publications, public and scientific conference presentations.

PROSPERO REGISTRATION NUMBER

CRD42020188633.

Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology

In this prospective, interventional, international study, we investigate continuous monitoring of hospitalised patients' vital signs using wearable technology as a basis for real-time early warning scores (EWS) estimation and vital signs time-series prediction. The collected continuous monitored vital signs are heart rate, blood pressure, respiration rate, and oxygen saturation of a heterogeneous patient population hospitalised in cardiology, postsurgical, and dialysis wards. Two aspects are elaborated in this study. The first is the high-rate (every minute) estimation of the statistical values (e.g., minimum and mean) of the vital signs components of the EWS for one-minute segments in contrast with the conventional routine of 2 to 3 times per day. The second aspect explores the use of a hybrid machine learning algorithm of kNN-LS-SVM for predicting future values of monitored vital signs. It is demonstrated that a real-time implementation of EWS in clinical practice is possible. Furthermore, we showed a promising prediction performance of vital signs compared to the most recent state of the art of a boosted approach of LSTM. The reported mean absolute percentage errors of predicting one-hour averaged heart rate are 4.1, 4.5, and 5% for the upcoming one, two, and three hours respectively for cardiology patients. The obtained results in this study show the potential of using wearable technology to continuously monitor the vital signs of hospitalised patients as the real-time estimation of EWS in addition to a reliable prediction of the future values of these vital signs is presented. Ultimately, both approaches of high-rate EWS computation and vital signs time-series prediction is promising to provide efficient cost-utility, ease of mobility and portability, streaming analytics, and early warning for vital signs deterioration.