Evaluation of standard versus nonstandard vital signs monitors in the prehospital and emergency departments: results and lessons learned from a trauma patient care protocol

Applications of Artificial Intelligence in Helicopter Emergency Medical Services: A Scoping Review

OBJECTIVE

Recent systematic reviews of acute care medicine applications of artificial intelligence (AI) have focused on hospital and general prehospital uses. The purpose of this scoping review was to identify and describe the literature on AI use with a focus on applications in helicopter emergency medical services (HEMS).

METHODS

A literature search was performed with specific inclusion and exclusion criteria. Articles were grouped by characteristics such as publication year and general subject matter with categoric and temporal trend analyses.

RESULTS

We identified 21 records focused on the use of AI in HEMS. These applications included both clinical and triage uses and nonclinical uses. The earliest study appeared in 2006, but over one third of the identified studies have been published in 2021 or later. The passage of time has seen an increased likelihood of HEMS AI studies focusing on nonclinical issues; for each year, the likelihood of a nonclinical focus had an odds ratio of 1.3.

CONCLUSION

This scoping review provides overview and hypothesis-generating information regarding AI applications specific to HEMS. HEMS AI may be ultimately deployed in nonclinical arenas as much as or more than for clinical decision support. Future studies will inform future decisions as to how AI may improve HEMS systems design, asset deployment, and clinical care.

Clinical application of a body area network-based smart bracelet for pre-hospital trauma care

Objective

This study aims to explore the efficiency and effectiveness of a body area network-based smart bracelet for trauma care prior to hospitalization.

Methods

To test the efficacy of the bracelet, an observational cohort study was conducted on the clinical data of 140 trauma patients pre-admission to the hospital. This study was divided into an experimental group receiving smart bracelets and a control group receiving conventional treatment. Both groups were randomized using a random number table. The primary variables of this study were as follows: time to first administration of life-saving intervention, time to first administration of blood transfusion, time to first administration of hemostatic drugs, and mortality rates within 24 h and 28 days post-admission to the hospital. The secondary outcomes included the amount of time before trauma team activation and the overall length of patient stay in the emergency room.

Results

The measurement results for both the emergency smart bracelet as well as traditional equipment showed high levels of consistency and accuracy. In terms of pre-hospital emergency life-saving intervention, there was no significant statistical difference in the mortality rates between both groups within 224 h post-admission to the hospital or after 28-days of treatment in the emergency department. Furthermore, the treatment efficiency for the group of patients wearing smart bracelets was significantly better than that of the control group with regard to both the primary and secondary outcomes of this study. These results indicate that this smart bracelet has the potential to improve the efficiency and effectiveness of trauma care and treatment.

Conclusion

A body area network-based smart bracelet combined with remote 5G technology can assist the administration of emergency care to trauma patients prior to hospital admission, shorten the timeframe in which life-saving interventions are initiated, and allow for a quick trauma team response as well as increased efficiency upon administration of emergency care.

Remote Monitoring of Chronic Critically Ill Patients after Hospital Discharge: A Systematic Review

Background: Over the past few decades, critical care has seen many advancements. These advancements resulted in a considerable increase in the prevalence of chronically critically ill patients requiring prolonged medical care, which led to a massive increase in healthcare utilization. Methods: We performed a search for suitable articles using PubMed and Google Scholar from the inception of these databases to 15 May 2021. Results: Thirty-four articles were included in the review and analyzed. We described the following characteristics and problems with chronic critically ill patient management: the patient population, remote monitoring, the monitoring of physiological parameters in chronic critically ill patients, the anatomical location of sensors, the barriers to implementation, and the main technology-related issues. The main challenges in the management of these patients are (1) the shortage of caretakers, (2) the periodicity of vital function monitoring (e.g., episodic measuring of blood pressure leads to missing important critical events such as hypertension, hypotension, and hypoxia), and (3) failure to catch and manage critical physiological events at the right time, which can result in poor outcomes. Conclusions: The prevalence of critically ill patients is expected to grow. Technical solutions can greatly assist medical personnel and caregivers. Wearable devices can be used to monitor blood pressure, heart rate, pulse, respiratory rate, blood oxygen saturation, metabolism, and central nervous system function. The most important points that should be addressed in future studies are the performance of the remote monitoring systems, safety, clinical and economic outcomes, as well as the acceptance of the devices by patients, caretakers, and healthcare professionals.

Continuous Monitoring of Respiratory Rate with Wearable Sensor in Patients Admitted to Hospital with Pneumonia Compared with Intermittent Nurse-Led Monitoring in the United Kingdom: A Cost-Utility Analysis

BACKGROUND

Respiratory rate (RR) is one of the most important physiologic measures for predicting patients' deterioration of clinical condition and final prognosis. In several studies, RR has been the most important predictor of patients' prognoses.

OBJECTIVES

The objective of this study was to conduct a cost-utility analysis to estimate the cost and effectiveness of automatic respiratory rate monitoring (ARRM) with a non-invasive sensor (RespiraSense™) plus intermittent nurse-led RR monitoring (ARRM strategy) compared with intermittent nurse-led RR monitoring (IM strategy) in patients admitted to hospital in the UK with pneumonia.

METHODS

A decision analytic model was developed based on a hypothetical cohort of patients who were admitted to hospital with pneumonia. After admission, the patients could be monitored with either ARRM or IM strategies. The outcomes of interest included total costs and total effectiveness of each strategy, including length of stay (LoS) in hospital, LoS in intensive care unit, quality-adjusted life-years (QALYs), deaths, and incremental cost per QALY gained. An incremental cost of £20,000 or less per QALY gained was considered cost effective. A lifetime time horizon (38 years) was used to capture the long-term benefits. Probabilistic and deterministic sensitivity analyses were performed.

RESULTS

Total costs of patient care in ARRM and IM strategies were £1986.9 million and £2079.4 million, respectively. Total incremental QALYs lived were 3548 higher in the intervention arm (ARRM), meaning that the ARRM strategy was dominant (i.e., less costly [£92.6 million less] and more effective). The results were stable in probabilistic and most of the deterministic sensitivity analyses. Results from threshold analysis indicated that a minimum of 7 and 10% improvement in percentage of early detection of respiratory compromise is required for ARRM to become cost effective and cost saving, respectively.

CONCLUSIONS

Our results indicate that ARRM using RespiraSense, in addition to intermittent nurse-led monitoring of RR, in patients admitted to the hospital with pneumonia could be a cost-saving and cost-effective intervention if the minimum clinical thresholds are met.

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.

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.

Current Evidence for Continuous Vital Signs Monitoring by Wearable Wireless Devices in Hospitalized Adults: Systematic Review

BACKGROUND

Continuous monitoring of vital signs by using wearable wireless devices may allow for timely detection of clinical deterioration in patients in general wards in comparison to detection by standard intermittent vital signs measurements. A large number of studies on many different wearable devices have been reported in recent years, but a systematic review is not yet available to date.

OBJECTIVE

The aim of this study was to provide a systematic review for health care professionals regarding the current evidence about the validation, feasibility, clinical outcomes, and costs of wearable wireless devices for continuous monitoring of vital signs.

METHODS

A systematic and comprehensive search was performed using PubMed/MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials from January 2009 to September 2019 for studies that evaluated wearable wireless devices for continuous monitoring of vital signs in adults. Outcomes were structured by validation, feasibility, clinical outcomes, and costs. Risk of bias was determined by using the Mixed Methods Appraisal Tool, quality assessment of diagnostic accuracy studies 2nd edition, or quality of health economic studies tool.

RESULTS

In this review, 27 studies evaluating 13 different wearable wireless devices were included. These studies predominantly evaluated the validation or the feasibility outcomes of these devices. Only a few studies reported the clinical outcomes with these devices and they did not report a significantly better clinical outcome than the standard tools used for measuring vital signs. Cost outcomes were not reported in any study. The quality of the included studies was predominantly rated as low or moderate.

CONCLUSIONS

Wearable wireless continuous monitoring devices are mostly still in the clinical validation and feasibility testing phases. To date, there are no high quality large well-controlled studies of wearable wireless devices available that show a significant clinical benefit or cost-effectiveness. Such studies are needed to help health care professionals and administrators in their decision making regarding implementation of these devices on a large scale in clinical practice or in-home monitoring.

Mobile wireless monitoring system for prehospital emergency care

BACKGROUND

Latest achievement technologies allow engineers to develop medical systems that medical doctors in the health care system could not imagine years ago. The development of signal theory, intelligent systems, biophysics and extensive collaboration between science and technology researchers and medical professionals, open up the potential for preventive, real-time monitoring of patients. With the recent developments of new methods in medicine, it is also possible to predict the trends of the disease development as well the systemic support in diagnose setting. Within the framework of the needs to track the patient health parameters in the hospital environment or in the case of road accidents, the researchers had to integrate the knowledge and experiences of medical specialists in emergency medicine who have participated in the development of a mobile wireless monitoring system designed for real-time monitoring of victim vital parameters. Emergency medicine responders are first point of care for trauma victim providing prehospital care, including triage and treatment at the scene of incident and transport from the scene to the hospital. Continuous monitoring of life functions allows immediate detection of a deterioration in health status and helps out in carrying out principle of continuous e-triage. In this study, a mobile wireless monitoring system for measuring and recording the vital parameters of the patient was presented and evaluated. Based on the measured values, the system is able to make triage and assign treatment priority for the patient. The system also provides the opportunity to take a picture of the injury, mark the injured body parts, calculate Glasgow Coma Score, or insert/record the medication given to the patient. Evaluation of the system was made using the Technology Acceptance Model (TAM). In particular we measured: perceived usefulness, perceived ease of use, attitude, intention to use, patient status and environmental status.

METHODS

A functional prototype of a developed wireless sensor-based system was installed at the emergency medical (EM) department, and presented to the participants of this study. Thirty participants, paramedics and doctors from the emergency department participated in the study. Two scenarios common for the prehospital emergency routines were considered for the evaluation. Participants were asked to answer the questions referred to these scenarios by rating each of the items on a 5-point Likert scale.

RESULTS

Path coefficients between each measured variable were calculated. All coefficients were positive, but the statistically significant were only the following: patient status and perceive usefulness (β = 0.284, t = 2.097), environment (both urban a nd rural) and perceive usefulness (β = 0.247, t = 2.570; β = 0.329, t = 2.083, respectively), and perceive usefulness and behavioral intention (β = 0.621 t = 7.269). The variance of intention is 47.9%.

CONCLUSIONS

The study results show that the proposed system is well accepted by the EM personnel and can be used as a complementary system in EM department for continuous monitoring of patients' vital signs.

The association between abnormal vital sign groups and undesirable patient outcomes

Introduction:

To determine the association between both abnormal individual vital signs and abnormal vital sign groups in the emergency department, and undesirable patient outcomes: hospital admission, medical emergency team calls and death.

Method:

We undertook a prospective cohort study in a tertiary referral emergency department (February–May 2015). Vital signs were collected prospectively in the emergency department and undesirable outcomes from the medical records. The primary outcomes were undesirable outcomes for individual vital signs (multivariate logistic regression) and vital sign groups (univariate analyses).

Results:

Data from 1438 patients were analysed. Admission was associated with tachycardia, tachypnoea, fever, ≥1 abnormal vital sign on admission to the emergency department, ≥1 abnormal vital sign at any time in the emergency department, a persistently abnormal vital sign, and vital signs consistent with both sepsis (tachycardia/hypotension/abnormal temperature) and pneumonia (tachypnoea/fever) (p < 0.05). Medical emergency team calls were associated with tachycardia, tachypnoea, ≥1 abnormal vital sign on admission (odds ratio: 2.3, 95% confidence interval: 1.4–3.8), ≥2 abnormal vital signs at any time (odds ratio: 2.4, 95% confidence interval: 1.2–4.7), and a persistently abnormal vital sign (odds ratio: 2.7, 95% confidence interval: 1.6–4.6). Death was associated with Glasgow Coma Score ≤13 (odds ratio: 6.3, 95% confidence interval: 2.5–16.0), ≥1 abnormal vital sign on admission (odds ratio: 2.6, 95% confidence interval: 1.2–5.6), ≥2 abnormal vital signs at any time (odds ratio: 6.4, 95% confidence interval: 1.4–29.5), a persistently abnormal vital sign (odds ratio: 4.3, 95% confidence interval: 2.0–9.0), and vital signs consistent with pneumonia (odds ratio: 5.3, 95% confidence interval: 1.9–14.8).

Conclusion:

Abnormal vital sign groups are generally superior to individual vital signs in predicting undesirable outcomes. They could inform best practice management, emergency department disposition, and communication with the patient and family.

Inefficacy of standard vital signs for predicting mortality and the need for prehospital life-saving interventions in blunt trauma patients transported via helicopter: A repeated call for new measures

BACKGROUND

The aim of this study was to investigate the efficacy of traditional vital signs for predicting mortality and the need for prehospital lifesaving interventions (LSIs) in blunt trauma patients requiring helicopter transport to a Level I trauma center. Our hypothesis was that standard vital signs are not sufficient for identifying or determining treatment for those patients most at risk.

METHODS

This study involved prehospital trauma patients suffering from blunt trauma (motor vehicle/cycle collision) and transported from the point of injury via helicopter. Means and standard deviations for vital signs and Glasgow Coma Scale (GCS) scores were obtained for non-LSI versus LSI and survivor versus nonsurvivor patient groups and then compared using Wilcoxon statistical tests. Variables with statistically significant differences between patient groups were then used to develop multivariate logistic regression models for predicting mortality and/or the need for prehospital LSIs. Receiver-operating characteristic (ROC) curves were also obtained to compare these models.

RESULTS

A final cohort of 195 patients was included in the analysis. Thirty (15%) patients received a total of 39 prehospital LSIs. Of these, 12 (40%) died. In total, 33 (17%) patients died. Of these, 21 (74%) did not receive prehospital LSIs. Model variables were field heart rate, lowest systolic blood pressure, shock index, pulse pressure, and GCS components. Using vital signs alone, ROC curves demonstrated poor prediction of LSI needs, mortality, and nonsurvivors who did not receive LSIs (area under the curve [AUC], AUCs: 0.72, 0.65, and 0.61). When using both vital signs and GCS, ROC curves still demonstrated poor prediction of nonsurvivors overall and nonsurvivors who did not receive LSIs (AUCs: 0.67, 0.74).

CONCLUSION

The major implication of this study was that traditional vital signs cannot identify or determine treatment for many prehospital blunt trauma patients who are at great risk. This study reiterated the need for new measures to improve blunt trauma triage and prehospital care.

LEVEL OF EVIDENCE

Therapeutic/care management, level IV.