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Acta Obstetricia Et Gynecologica... Jul 2017Continuous intrapartum fetal monitoring remains a significant clinical challenge. We propose using cohorts of routinely collected data. We aim to combine non-classical...
INTRODUCTION
Continuous intrapartum fetal monitoring remains a significant clinical challenge. We propose using cohorts of routinely collected data. We aim to combine non-classical (data-driven) and classical cardiotocography features with clinical features into a system (OxSys), which generates automated alarms for the fetus at risk of intrapartum hypoxia. We hypothesize that OxSys can outperform clinical diagnosis of "fetal distress", when optimized and tested over large retrospective data sets.
MATERIAL AND METHODS
We studied a cohort of 22 790 women in labor (≥36 weeks of gestation). Paired umbilical blood analyses were available. Perinatal outcomes were defined by objective criteria (normal; severe, moderate or mild compromise). We used the data retrospectively to develop a prototype of OxSys, by relating its alarms to perinatal outcome, and comparing its performance against standards achieved by bedside diagnosis.
RESULTS
OxSys1.5 triggers an alarm if the initial trace is nonreactive or the decelerative capacity (a nonclassical cardiotocography feature), exceeds a threshold, adjusted for preeclampsia and thick meconium. There were 187 newborns with severe, 613 with moderate and 3197 with mild compromise; and 18 793 with normal outcome. OxSys1.5 increased the sensitivity for compromise detection: 43.3% vs. 38.0% for severe (p = 0.3) and 36.1% vs. 31.0% for moderate (p = 0.06); and reduced the false-positive rate (14.4% vs. 16.3%, p < 0.001).
CONCLUSIONS
Large historic cohorts can be used to develop and optimize computerized cardiotocography monitoring, combining clinical and cardiotocography risk factors. Our simple prototype has demonstrated the principle of using such data to trigger alarms, and compares well with clinical judgment.
Topics: Cardiotocography; Cohort Studies; Decision Support Systems, Clinical; Diagnosis, Computer-Assisted; Female; Fetal Blood; Fetal Distress; Humans; Labor Presentation; Predictive Value of Tests; Pregnancy; Prenatal Care
PubMed: 28369712
DOI: 10.1111/aogs.13136 -
Dementia (London, England) Oct 2018The aim of this study was to assess in practice whether assistive technologies support and facilitate the work of a family caregiver or care staff, and whether these...
The aim of this study was to assess in practice whether assistive technologies support and facilitate the work of a family caregiver or care staff, and whether these technologies support the independence of a person with a memory disorder. A comprehensive set of supportive devices and alarm systems were experimentally tested in the care of five test subjects in an assisted living facility by eight nurses, and in the care of four test subjects in a home environment by three family caregivers and one care team. Questionnaires, diaries and logged data were used to evaluate the benefits of the devices. Simple aids and alarm systems that did not need much adjusting were considered most useful by caregivers and nurses, though multiple false alarms occurred during the test period. Technical connection problems, complex user interface, and inadequate sound quality were the primary factors reducing the utility of the tested devices. Further experimental research is needed to evaluate the utility of assistive technologies in different stages of a memory disorder.
Topics: Adult; Aged; Aged, 80 and over; Assisted Living Facilities; Caregivers; Consumer Behavior; Dementia; Family; Female; Home Care Services; Humans; Independent Living; Male; Memory Disorders; Middle Aged; Nurses; Reminder Systems; Self-Help Devices
PubMed: 27765896
DOI: 10.1177/1471301216674816 -
Scandinavian Journal of Trauma,... Aug 2023Organized volunteer initiatives can reduce response times and improve outcomes in emergencies such as cardiac arrests or fires. Retention of volunteers is important to...
BACKGROUND
Organized volunteer initiatives can reduce response times and improve outcomes in emergencies such as cardiac arrests or fires. Retention of volunteers is important to maintain good coverage and capabilities. The current study explores factors underlying volunteers' motivation to continue as volunteers.
METHODS
Data from 5347 active volunteers were collected through an online survey. An exploratory factor analysis was used to identify underlying factors that were then used in a regression analysis to predict intention to continue as a volunteer. Group differences based on, among others, number of alarms and prior professional experience in emergency response were explored.
RESULTS
The results showed that the factors community, self-image, and competence were the strongest positive predictors for the motivation to continue, whereas alarm fatigue and negative experience were the strongest negative predictors. Volunteers with professional background had higher competence and lower Alarm fatigue. Volunteers from rural areas and small cities had higher community than those in large cities.
CONCLUSIONS
Alarm fatigue can make it hard to retain volunteers, which could be addressed using improved dispatch algorithms. Support after dispatch is important to prevent negative experiences. Finally, increased competence, e.g. through education and training, can improve volunteer's motivation to continue.
Topics: Humans; Volunteers; Educational Status; Motivation; Algorithms; Factor Analysis, Statistical
PubMed: 37568197
DOI: 10.1186/s13049-023-01101-0 -
Australian Critical Care : Official... Mar 2024Excessive number of alarms and false and nonactionable alarms may lead to alarm fatigue. Alarm fatigue could easily contribute to burnout. Burnout may reduce nurses'...
BACKGROUND
Excessive number of alarms and false and nonactionable alarms may lead to alarm fatigue. Alarm fatigue could easily contribute to burnout. Burnout may reduce nurses' sensitivity to alarms, thus affecting patients' safety due to insufficient response to the alarms. However, no study has examined nurses' alarm fatigue in Ghana.
OBJECTIVES
The objective of this study was to investigate the level of alarm fatigue and its associated factors, as well as determine its relationship with burnout among nurses working in the critical care units of hospitals in Ghana.
METHODS
The cross-sectional study was conducted in critical care units of five hospitals in Ghana from November 2021 to January 2022. A total of 364 nurses were recruited and completed the questionnaire. Alarm fatigue was assessed by the alarm fatigue questionnaire, which was originally developed in Chinese and was translated into English using a standard protocol. Burnout was assessed using the Maslach Burnout Inventory.
RESULTS
The overall alarm fatigue score was 76.43 ± 27.80 out of 124. Longer years working at the critical care unit (B = -2.50, 95% confidence interval [CI]: -4.62, -0.37) and having policies related to alarm management (B = -10.77, 95% CI: -3.50, -18.04) were associated with a decreased risk of alarm fatigue, while working in neonatal intensive care unit (B = 16.35, 95% CI: 2.48, 30.21) and postanesthesia care unit (B = 15.16; 95% CI: 0.32, 30.01), and having anxiety and stress (B = 8.15, 95% CI: 1.30, 15.00) were associated with an increased risk of alarm fatigue. In addition, alarm fatigue was positively associated with emotional exhaustion (r = 0.52, P < 0.001) and depersonalisation (r = 0.43, P < 0.001) but not personal accomplishment (r = -0.09, P = 0.100).
CONCLUSION
Critical care nurses in Ghana experienced higher levels of alarm fatigue, which is affected by multiple factors. There is a significant link between nurses' alarm fatigue and burnout. Our findings provide important guidance for future intervention programs to improve critical care nurses' alarm fatigue by introducing policies on alarm management and improving nurses' psychological health, with a special focus on nurses with shorter working years and working in neonatal intensive care unit and postanesthesia care unit.
Topics: Infant, Newborn; Humans; Cross-Sectional Studies; Alert Fatigue, Health Personnel; Clinical Alarms; Burnout, Professional; Critical Care; Intensive Care Units, Neonatal; Nurses; Psychological Tests; Self Report
PubMed: 37580238
DOI: 10.1016/j.aucc.2023.06.010 -
Scientific Reports Apr 2016Nearby collinear flankers increase the false alarm rate (reports of the target being present when it is not) in a Yes-No experiment. This effect has been attributed to...
Nearby collinear flankers increase the false alarm rate (reports of the target being present when it is not) in a Yes-No experiment. This effect has been attributed to "filling-in" of the target location due to increased activity induced by the flankers. According to signal detection theory, false alarms are attributed to noise in the visual nervous system. Here we investigated the effect of external noise on the filling-in effect by adding white noise to a low contrast Gabor target presented between two collinear Gabor flankers at a range of target-flanker separations. External noise modulates the filling-in effect, reducing visual sensitivity (d') and increasing the filling-in effect (False Alarm rate). We estimated the amount of external noise at which the false alarm rate increases by the √2 (which we refer to as NFA). Across flank distances, both the false alarm rate and d' (with no external noise) are correlated with NFA. These results are consistent with the notion that nearby collinear flankers add both signal and noise to the target location. The increased signal results in higher d' values; the increased noise to higher false alarm rates (the filling effect).
Topics: Adult; Contrast Sensitivity; Humans; Perceptual Masking; Photic Stimulation; Sensory Thresholds; Visual Perception; Young Adult
PubMed: 27103594
DOI: 10.1038/srep24938 -
JMIR Biomedical Engineering May 2021Clinical decision support systems (CDSS) have the potential to lower the patient mortality and morbidity rates. However, signal artifacts present in physiological data...
BACKGROUND
Clinical decision support systems (CDSS) have the potential to lower the patient mortality and morbidity rates. However, signal artifacts present in physiological data affect the reliability and accuracy of the CDSS. Moreover, patient monitors and other medical devices generate false alarms while processing physiological data, further leading to alarm fatigue because of increased noise levels, staff disruption, and staff desensitization in busy critical care environments. This adversely affects the quality of care at the patient bedside. Hence, artifact detection (AD) algorithms play a crucial role in assessing the quality of physiological data and mitigating the impact of these artifacts.
OBJECTIVE
The aim of this study is to evaluate a novel AD framework for integrating AD algorithms with CDSS. We designed the framework with features that support real-time implementation within critical care. In this study, we evaluated the framework and its features in a false alarm reduction study. We developed static framework component models, followed by dynamic framework compositions to formulate four CDSS. We evaluated these formulations using neonatal patient data and validated the six framework features: flexibility, reusability, signal quality indicator standardization, scalability, customizability, and real-time implementation support.
METHODS
We developed four exemplar static AD components with standardized requirements and provisions interfaces that facilitate the interoperability of framework components. These AD components were mixed and matched into four different AD compositions to mitigate the artifacts' effects. We developed a novel static clinical event detection component that is integrated with each AD composition to formulate and evaluate a dynamic CDSS for peripheral oxygen saturation (SpO) alarm generation. This study collected data from 11 patients with diverse pathologies in the neonatal intensive care unit. Collected data streams and corresponding alarms include pulse rate and SpO measured from a pulse oximeter (Masimo SET SmartPod) integrated with an Infinity Delta monitor and the heart rate derived from electrocardiography leads attached to a second Infinity Delta monitor.
RESULTS
A total of 119 SpO alarms were evaluated. The lowest achievable SpO false alarm rate was 39%, with a sensitivity of 80%. This demonstrates the framework's utility in identifying the best possible dynamic composition to serve the clinical need for false SpO alarm reduction and subsequent alarm fatigue, given the limitations of a small sample size.
CONCLUSIONS
The framework features, including reusability, signal quality indicator standardization, scalability, and customizability, allow the evaluation and comparison of novel CDSS formulations. The optimal solution for a CDSS can then be hard-coded and integrated within clinical workflows for real-time implementation. The flexibility to serve different clinical needs and standardized component interoperability of the framework supports the potential for a real-time clinical implementation of AD.
PubMed: 38907382
DOI: 10.2196/23495 -
BMC Public Health Apr 2021Despite remarkable progress in the reduction of malaria incidence, this disease remains a public health threat to a significant portion of the world's population....
BACKGROUND
Despite remarkable progress in the reduction of malaria incidence, this disease remains a public health threat to a significant portion of the world's population. Surveillance, combined with early detection algorithms, can be an effective intervention strategy to inform timely public health responses to potential outbreaks. Our main objective was to compare the potential for detecting malaria outbreaks by selected event detection methods.
METHODS
We used historical surveillance data with weekly counts of confirmed Plasmodium falciparum (including mixed) cases from the Amhara region of Ethiopia, where there was a resurgence of malaria in 2019 following several years of declining cases. We evaluated three methods for early detection of the 2019 malaria events: 1) the Centers for Disease Prevention and Control (CDC) Early Aberration Reporting System (EARS), 2) methods based on weekly statistical thresholds, including the WHO and Cullen methods, and 3) the Farrington methods.
RESULTS
All of the methods evaluated performed better than a naïve random alarm generator. We also found distinct trade-offs between the percent of events detected and the percent of true positive alarms. CDC EARS and weekly statistical threshold methods had high event sensitivities (80-100% CDC; 57-100% weekly statistical) and low to moderate alarm specificities (25-40% CDC; 16-61% weekly statistical). Farrington variants had a wide range of scores (20-100% sensitivities; 16-100% specificities) and could achieve various balances between sensitivity and specificity.
CONCLUSIONS
Of the methods tested, we found that the Farrington improved method was most effective at maximizing both the percent of events detected and true positive alarms for our dataset (> 70% sensitivity and > 70% specificity). This method uses statistical models to establish thresholds while controlling for seasonality and multi-year trends, and we suggest that it and other model-based approaches should be considered more broadly for malaria early detection.
Topics: Antimalarials; Ethiopia; Humans; Incidence; Malaria; Malaria, Falciparum; Plasmodium falciparum
PubMed: 33894764
DOI: 10.1186/s12889-021-10850-5 -
PloS One 2023Clinical auditory alarms are often found in hospital wards and operating rooms. In these environments, regular daily tasks can result in having a multitude of concurrent...
Clinical auditory alarms are often found in hospital wards and operating rooms. In these environments, regular daily tasks can result in having a multitude of concurrent sounds (from staff and patients, building systems, carts, cleaning devices, and importantly, patient monitoring devices) which easily amount to a prevalent cacophony. The negative impact of this soundscape on staff and patients' health and well-being, as well as in their performance, demand for accordingly designed sound alarms. The recently updated IEC60601-1-8 standard, in guidance for medical equipment auditory alarms, proposed a set of pointers to distinctly convey medium or high levels of priority (urgency). However, conveying priority without compromising other features, such as ease of learnability and detectability, is an ongoing challenge. Electroencephalography, a non-invasive technique for measuring the brain response to a given stimulus, suggests that certain Event-Related Potentials (ERPs) components such as the Mismatch Negativity (MMN) and P3a may be the key to uncovering how sounds are processed at the pre-attentional level and how they may capture our attention. In this study, the brain dynamics in response to the priority pulses of the updated IEC60601-1-8 standard was studied via ERPs (MMN and P3a), for a soundscape characterised by the repetition of a sound (generic SpO2 "beep"), usually present in operating and recovery rooms. Additional behavioural experiments assessed the behavioural response to these priority pulses. Results showed that the Medium Priority pulse elicits a larger MMN and P3a peak amplitude when compared to the High Priority pulse. This suggests that, at least for the applied soundscape, the Medium Priority pulse is more easily detected and attended at the neural level. Behavioural data supports this indication, showing significantly shorter reaction times for the Medium Priority pulse. The results pose the possibility that priority pointers of the updated IEC60601-1-8 standard may not be successfully conveying their intended priority levels, which may not only be due to design properties but also to the soundscape in which these clinical alarms are deployed. This study highlights the need for intervention in both hospital soundscapes and auditory alarm design settings.
Topics: Humans; Clinical Alarms; Evoked Potentials; Attention; Electroencephalography; Reaction Time; Evoked Potentials, Auditory; Acoustic Stimulation; Auditory Perception
PubMed: 36795647
DOI: 10.1371/journal.pone.0281680 -
Ergonomics Jul 2017The aim of this study was to explore operator experience and performance for semantically congruent and incongruent auditory icons and abstract alarm sounds. It was...
The aim of this study was to explore operator experience and performance for semantically congruent and incongruent auditory icons and abstract alarm sounds. It was expected that performance advantages for congruent sounds would be present initially but would reduce over time for both alarm types. Twenty-four participants (12M/12F) were placed into auditory icon or abstract alarm groupings. For each group both congruent and incongruent alarms were used to represent different driving task scenarios. Once sounded, participants were required to respond to each alarm by selecting a corresponding driving scenario. User performance for all sound types improved over time, however even with experience a decrement in speed of response remained for the incongruent iconic sounds and in accuracy of performance for the abstract warning sounds when compared to the congruent auditory icons. Semantic congruency was found to be of more importance for auditory icons than for abstract sounds. Practitioner Summary: Alarms are used in many operating systems as emergency, alerting, or continuous monitoring signals for instance. This study found that the type and representativeness of an auditory warning will influence operator performance over time. Semantically congruent iconic sounds produced performance advantages over both incongruent iconic sounds and abstract warnings.
Topics: Acoustic Stimulation; Adult; Attention; Auditory Perception; Automobile Driving; Female; Humans; Male; Reaction Time; Semantics; Sound
PubMed: 27650392
DOI: 10.1080/00140139.2016.1237677 -
Respiratory Care Apr 2021Clinical alarms play an important role in monitoring physiological parameters, vital signs and medical device function in the hospital intensive care environment. Delays...
BACKGROUND
Clinical alarms play an important role in monitoring physiological parameters, vital signs and medical device function in the hospital intensive care environment. Delays in staff response to alarms are well documented as health care providers become desensitized to increased rates of nuisance alarms. Patients can be at increased risk of harm due to alarm fatigue. Current literature suggests alarms from ventilators contribute significantly to nonactionable alarms. A greater understanding of which specific ventilator alarms are most common and the rates at which they occur is fundamental to improving alarm management.
METHODS
A retrospective review was performed on alarms that occurred on the Avea and Servo-i ventilators used in the pediatric ICU and pediatric cardiothoracic ICU at a major metropolitan children's hospital. High- and medium-priority alarms, as classified by the manufacturer, were studied between June 1, 2017, and November 31, 2017. Descriptive data analysis and a 2-proportion z-test were performed to identify proportionality, cause, and prevalence rates in the pediatric ICU and the cardiothoracic ICU.
RESULTS
Eleven distinct ventilator alarms were identified during 2,091 d of mechanical ventilation. The Inspiratory Flow Overrange alarm (42.4%) on the Servo-i, Low V (20.4%; expiratory tidal volume) and Circuit Integrity alarm (20.0%) on the Avea were the most prevalent causes according to ventilator type. Medium-priority alarms comprised 68.7% of all Servo-i alarms, and high-priority alarms comprised 84% of all Avea alarms. The 2-sample test of proportions was significant for differences between both areas ( < .001). The overall alarm prevalence rate was 22.5 ventilator alarms per ventilator-day per patient.
CONCLUSIONS
The cause and proportion of alarms varied by ventilator and care unit. High-priority alarms were most common with the Avea and medium-priority alarms for the Servo-i. The overall combined ventilator alarm prevalence rate was 22.5 alarms per ventilator-day per patient.
Topics: Child; Clinical Alarms; Critical Care; Humans; Monitoring, Physiologic; Prevalence; Respiration, Artificial; Retrospective Studies; Ventilators, Mechanical
PubMed: 33293363
DOI: 10.4187/respcare.07200