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Franco, Andrezza Serpa, Aline Affonso Luna, Flavia Giron Camerini, Danielle De Mendonça Henrique, Luana De Almeida Ferreira, and Roberto Carlos Lyra da Silva. "Segurança na utilização de bombas infusoras: análise dos alarmes." Revista de Enfermagem UFPE on line 12, no. 5 (2018): 1331. http://dx.doi.org/10.5205/1981-8963-v12i5a231286p1331-1337-2018.
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RESUMOObjetivo: analisar o perfil dos alarmes de bombas infusoras em uma unidade intensiva. Método: estudo quantitativo, descritivo, observacional, transversal e seccional, realizado em uma unidade cárdio intensiva, com amostra de 72 alarmes disparados de bombas infusoras, coletados em instrumento estruturado. Análise realizada com tabulação e tratamento estatístico no programa SPSS® versão 2.1. e apresentados em figuras. Resultados: observou-se que os alarmes mais disparados pelas bombas infusoras estão relacionados ao fim de infusão (41,7%) e o de manipulação pela equipe (29,2%). Em relação aos tempos dos alarmes, identificou-se a média de 109,8 segundos, caracterizados por quatro alarmes com maior tempo: “pré-alarme fim de infusão”, “fluxo baixo”, “fim de stand by” e “fim de infusão”. Conclusão: a caracterização dos alarmes auxilia o enfermeiro a planejar ações para minimizar o tempo estimulo - resposta, com a finalidade de melhorar a qualidade da assistência de enfermagem e de aumentar a segurança para o paciente. Descritores: Cuidados de Enfermagem; Segurança do Paciente; Alarmes Clínicos; Enfermagem; Bombas de Infusão.ABSTRACT Objective: to analyze the profile of the infusion pump alarms in an intensive unit. Method: this is a quantitative, descriptive, observational, cross-sectional and sectional study carried out in an intensive cardiogenic unit with a sample of 72 alarms fired from infusion pumps, collected in a structured instrument. The analysis was performed with tabulation and statistical treatment in SPSS® software version 2.1. and presented in figures. Results: it was observed that the alarms triggered by the infusion pumps are related to the end of infusion (41.7%) and the manipulation by the team (29.2%). Regarding the time of the alarms, the average of 109.8 seconds was identified, characterized by four alarms with more time: “pre-alarm end of infusion”, “low flow”, “end of standby” and “end of infusion”. Conclusion: the characterization of the alarms helps the nurse to plan actions to minimize the stimulus-response time, improving the quality of the nursing care and increasing the safety for the patient. Descriptors: Nursing Care; Patient Safety; Clinical Alarms; Nursing; Infusion Pumps; Healthcare.RESUMEN Objetivo: analizar el perfil de las alarmas de bombas de infusión en una unidad intensiva. Método: estudio cuantitativo, descriptivo, observacional, transversal y seccional, realizado en una unidad cardio-intensiva, con muestra de 72 alarmas disparadas de bombas de infusión, recolegidas en instrumento estructurado. El análisis fue realizado con tabulación y tratamiento estadístico en el programa SPSS® versión 2.1. y presentados en figuras. Resultados: se observó que las alarmas más disparadas por las bombas de infusión están relacionadas al fin de infusión (41,7%) y la de manipulación por el equipo (29,2%). En relación a los tiempos de las alarmas, se identificó la media de 109,8 segundos, caracterizados por cuatro alarmas con mayor tiempo: “pre-alarma fin de infusión”, “flujo bajo”, “fin de stand by” y “fin de infusión”. Conclusão: la caracterización de las alarmas auxilia al enfermero a planear acciones para minimizar el tiempo estimulo - respuesta, con la finalidad de mejorar la calidad de la asistencia de enfermería y de aumentar la seguridad para el paciente. Descriptores: Atención de Enfermería; Seguridad del Paciente; Alarmas Clínicas; Enfermería; Bombas de Infusión.
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Bonafide, Christopher P., Miriam Zander, Christian Sarkis Graham, et al. "Video Methods for Evaluating Physiologic Monitor Alarms And Alarm Responses." Biomedical Instrumentation & Technology 48, no. 3 (2014): 220–30. http://dx.doi.org/10.2345/0899-8205-48.3.220.
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False physiologic monitor alarms are extremely common in the hospital environment. High false alarm rates have the potential to lead to alarm fatigue, leading nurses to delay their responses to alarms, ignore alarms, or disable them entirely. Recent evidence from the U.S. Food and Drug Administration (FDA) and The Joint Commission has demonstrated a link between alarm fatigue and patient deaths. Yet, very little scientific effort has focused on the rigorous quantitative measurement of alarms and responses in the hospital setting. We developed a system using multiple temporarily mounted, minimally obtrusive video cameras in hospitalized patients' rooms to characterize physiologic monitor alarms and nurse responses as a proxy for alarm fatigue. This allowed us to efficiently categorize each alarm's cause, technical validity, actionable characteristics, and determine the nurse's response time. We describe and illustrate the methods we used to acquire the video, synchronize and process the video, manage the large digital files, integrate the video with data from the physiologic monitor alarm network, archive the video to secure servers, and perform expert review and annotation using alarm “bookmarks.” We discuss the technical and logistical challenges we encountered, including the root causes of hardware failures as well as issues with consent, confidentiality, protection of the video from litigation, and Hawthorne-like effects. The description of this video method may be useful to multidisciplinary teams interested in evaluating physiologic monitor alarms and alarm responses to better characterize alarm fatigue and other patient safety issues in clinical settings.
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Ruppel, Halley, Marjorie Funk, and Robin Whittemore. "Measurement of Physiological Monitor Alarm Accuracy and Clinical Relevance in Intensive Care Units." American Journal of Critical Care 27, no. 1 (2018): 11–21. http://dx.doi.org/10.4037/ajcc2018385.
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Background Alarm fatigue threatens patient safety by delaying or reducing clinician response to alarms, which can lead to missed critical events. Interventions to reduce alarms without jeopardizing patient safety target either inaccurate or clinically irrelevant alarms, so assessment of alarm accuracy and clinical relevance may enhance the rigor of alarm intervention studies done in clinical units. Objectives To (1) examine approaches used to measure accuracy and/or clinical relevance of physiological monitor alarms in intensive care units and (2) compare the proportions of inaccurate and clinically irrelevant alarms. Methods An integrative review was used to systematically search the literature and synthesize resulting articles. Results Twelve studies explicitly measuring alarm accuracy and/or clinical relevance on a clinical unit were identified. In the most rigorous studies, alarms were annotated retrospectively by obtaining alarm data and parameter waveforms rather than being annotated in real time. More than half of arrhythmia alarms in recent studies were inaccurate. However, contextual data were needed to determine alarms’ clinical relevance. Proportions of clinically irrelevant alarms were high, but definitions of clinically irrelevant alarms often included inaccurate alarms. Conclusions Future studies testing interventions on clinical units should include alarm accuracy and/or clinical relevance as outcome measures. Arrhythmia alarm accuracy should improve with advances in technology. Clinical interventions should focus on reducing clinically irrelevant alarms, with careful consideration of how clinical relevance is defined and measured.
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Jämsä, Juho O., Kimmo H. Uutela, Anna-Maija Tapper, and Lasse Lehtonen. "Clinical Alarms in a Gynaecological Surgical Unit: A Retrospective Data Analysis." International Journal of Environmental Research and Public Health 20, no. 5 (2023): 4193. http://dx.doi.org/10.3390/ijerph20054193.
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Alarm fatigue refers to the desensitisation of medical staff to patient monitor clinical alarms, which may lead to slower response time or total ignorance of alarms and thereby affects patient safety. The reasons behind alarm fatigue are complex; the main contributing factors include the high number of alarms and the poor positive predictive value of alarms. The study was performed in the Surgery and Anaesthesia Unit of the Women’s Hospital, Helsinki, by collecting data from patient monitoring device clinical alarms and patient characteristics from surgical operations. We descriptively analysed the data and statistically analysed the differences in alarm types between weekdays and weekends, using chi-squared, for a total of eight monitors with 562 patients. The most common operational procedure was caesarean section, of which 149 were performed (15.7%). Statistically significant differences existed in alarm types and procedures between weekdays and weekends. The number of alarms produced was 11.7 per patient. In total, 4698 (71.5%) alarms were technical and 1873 (28.5%) were physiological. The most common physiological alarm type was low pulse oximetry, with a total of 437 (23.3%). Of all the alarms, the number of alarms either acknowledged or silenced was 1234 (18.8%). A notable phenomenon in the study unit was alarm fatigue. Greater customisation of patient monitors for different settings is needed to reduce the number of alarms that do not have clinical significance.
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Busch-Vishniac, Ilene. "A Model of Clinical Alarm Errors in Hospital." Biomedical Instrumentation & Technology 49, no. 4 (2015): 280–91. http://dx.doi.org/10.2345/0899-8205-49.4.280.
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Although there has been much attention paid recently to clinical alarms, research has primarily focused on particular aspects of the clinical alarm problem, such as how to reduce nuisance alarms. This paper takes a broad view of clinical alarms and develops a model of errors in alarm handling and how they affect patients directly. Based on reports in the literature, I estimate that alarms that should sound by current standards do not sound about 9% of the time. Additionally, about 3% of alarms that are clinically significant are ignored, either intentionally or because they were inaudible. However, these errors produce a very low rate of reported alarmrelated deaths and other adverse effects (on the order of a couple adverse effects per 10 million alarm errors). While it is not yet possible to estimate the probabilities of clinical alarms having an adverse impact on patients other than the patient whose alarm is sounding, such indirect adverse effects likely occur at a low level as a result of disruption of staff workflow, creation of a noisy hospital environment, and contribution to communication difficulties. Consideration of alarms should include not only the patient connected to the device that is sounding, but also the impact of the alarm on other patients in the vicinity.
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Cosper, Pam, Mary Zellinger, Allen Enebo, Samantha Jacques, Lynn Razzano, and Marilyn Neder Flack. "Improving Clinical Alarm Management: Guidance and Strategies." Biomedical Instrumentation & Technology 51, no. 2 (2017): 109–15. http://dx.doi.org/10.2345/0899-8205-51.2.109.
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This article focuses on the type of problems that lead to false or nonactionable clinical alarms and the type of data that can help identify which of these alarms are most prevalent in specific units in healthcare facilities. The process of identifying necessary data is first described, as this activity will drive later choices on capturing data. This article also discusses how to use the data collected in alarm reports to help determine which alarms should be targeted first for improved management in a pilot environment. Suggestions are provided on how to reduce false and nonactionable alarm signals and how to monitor to ensure no untoward consequences occur from new alarm default settings. The information provided here can be individualized to hospitals and units to enhance alarm management with physiological monitor alarms. It also can be adapted to reduce nonactionable alarm signals occurring from other medical devices.
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Sendelbach, Sue, and Marjorie Funk. "Alarm Fatigue." AACN Advanced Critical Care 24, no. 4 (2013): 378–86. http://dx.doi.org/10.4037/nci.0b013e3182a903f9.
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Research has demonstrated that 72% to 99% of clinical alarms are false. The high number of false alarms has led to alarm fatigue. Alarm fatigue is sensory overload when clinicians are exposed to an excessive number of alarms, which can result in desensitization to alarms and missed alarms. Patient deaths have been attributed to alarm fatigue. Patient safety and regulatory agencies have focused on the issue of alarm fatigue, and it is a 2014 Joint Commission National Patient Safety Goal. Quality improvement projects have demonstrated that strategies such as daily electrocardiogram electrode changes, proper skin preparation, education, and customization of alarm parameters have been able to decrease the number of false alarms. These and other strategies need to be tested in rigorous clinical trials to determine whether they reduce alarm burden without compromising patient safety.
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Sharma Timilsina, Sunita. "Nurses perception and practices regarding clinical alarm in critical care units." Civil Medical Journal 2, no. 2 (2025): 16–21. https://doi.org/10.59338/cmj.24.
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Introduction: Clinical alarm are the alarm systems that are built in medical equipment which alert health care worker to determine the patient condition and are mostly prevalent in critical care units. Exposure to excessive false or non-actionable alarms can lead to alarm fatigue that result in alarm desensitization. This eventually contributes to missing of fatal alarms and important changes in a patient’s condition resulting in patient negative outcome. This study aimed to identify the nurses’ perception and practices regarding clinical alarms in critical care units. Methods: A cross-sectional study design with total enumerative sampling technique was used to select 122 nurses working at different critical care units in Civil Service Hospital. The Health Technology Foundation 2011, Clinical Alarms Survey tool was used for the perception regarding clinical alarm whereas self-administered questionnaire was used for alarm management practice and alarm fatigue. To interpret data, descriptive (mean, median, quartiles, percentage and standard deviation) and in inferential statistics Pearsons’s correlation were used. Result: In this study, average perception score about clinical alarm was 70.88% and the average alarm management practice score was 78.99%. The median of alarm fatigue score was 16.66%. The majority of study respondents (76.2%) have lower level of fatigue. There is no significant correlation between alarm management practice and alarm fatigue. Conclusion: The majority of nurses in this study had good perception and management practice regarding clinical alarm. Although some nurses felt low level of alarm fatigue, they had good alarm management practice. Since alarm fatigue is directly related to patients’ safety, the effective management of medical device alarms can reduce alarm fatigue and prevent potentially dangerous outcomes.
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Varghese, Minimole, and Bincy Sunil Thomas. "Improving Compliance to Clinical Alarm Safety in Adult ICUs of a Tertiary Hospital in India." International Journal of Critical Care 18, no. 4 (2024): 18–19. https://doi.org/10.29173/ijcc1007.
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With increasing number of devices with alarms a corresponding increase in clinical alarm-related adverse events was witnessed in ICUs of given hospital. Events like missing of vital alarms, not responding promptly and indefinite suspending alarms, etc., were on rise. Checking alarm settings before admitting patient to ICU was not being routinely followed, at times alarm settings of previously admitted patients being followed for new patient. ICU audits revealed that alarm settings for vital equipment like cardiac monitors & Ventilators were inconsistently documented (only 60%). The absence of appropriate documentation was identified as a safety threat. For instance, for ICU patients transferred-out to wards on non-Invasive ventilator (BiPAP), healthcare providers were not able to effectively manage alarm triggers due to lack of clarity regarding device settings. A survey conducted among nurses (n-131) indicated that alarm fatigue had set in, indicating high numbers of false alarms, leading to actionable alarms not being promptly responded to. Another survey for ICU patients (n=20) elicited that 45% patients experienced unbearable noise levels with 75% citing high noise levels to equipment alarms. The need for streamlining gaps led to rigorous brainstorming by relevant team members and designing of a protocol for clinical alarm safety. It involved identification of devices that triggered vital alarms, standardization of volumes & tone of alarms as per urgency, creation of default settings for cardiac monitors & need for documentation of ventilator as well as BiPAP settings by Clinicians, including the change of settings. Central monitoring system was uniformly installed in ICUs. The protocol further required nurses to: (1) ensure adequate skin preparation before ECG lead application; (2) check all device alarm settings, leads and all connections on patient admission to the unit & start of every shift; (3) ensure updating of patient demographics on devices with each new patient, (4) change defective equipment & accessories as indicated; (5) escalate to Clinicians the need to change settings for acceptable deviation of patient’s vital parameters. ICU team was alerted against suspending alarms without valid Clinician’s prescription. Biomedical team performed weekly alarm checks and conducted equipment trainings with added focus on clinical alarm troubleshooting. Additionally, training was imparted on: possible reasons for alarms, priority-wise responding to alarms, escalation of patient condition as per need, monitoring and management of patients on transit with critical equipment support. Post implementation of protocol there was improvement in compliance to alarm safety in adult ICUs, which increased from 61.42% (Nov-2023) to 90.25% (April-20240). Alarm related incidents reduced from an average of 1.54 per month to 0 post implementation of protocol. The protocolling and standardization brought about improvement in clinical alarm safety in adult ICUs with zero instances of alarm-related adverse events. Considering the improvement in adult ICUs, the protocol was extended to pediatric ICUs with creation of age-based default device alarm settings.
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Lee, Soo-Joung, Yun-Mi Lee, Eun Ji Seo, and Youn-Jung Son. "Impact of Hospital Nurses’ Perception on Clinical Alarms and Patient Safety Culture on Alarm Management Practice." International Journal of Environmental Research and Public Health 18, no. 8 (2021): 4018. http://dx.doi.org/10.3390/ijerph18084018.
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This study aimed to identify the impact of nurses’ perception of clinical alarms and patient safety culture on alarm management. Additionally, we aimed to describe the importance of clinical alarm issues. The data were collected from 21 August to 10 September 2020. The study participants were 116 nurses working in a tertiary acute care hospital in Korea. The self-report questionnaire included general characteristics, clinical alarm issues, nurses’ alarm perception, patient safety culture, and alarm management practice. The mean age of nurses was 28.04 ± 4.06 years, with 5.71 ± 4.35 years of total clinical experience. For the importance of alarm issues, frequent false alarms leading to reduced attention or response was the most important issue. Hierarchical linear regression analysis revealed that a higher level of nurses’ perceived patient safety culture was the strongest predictor of better alarm management practice (p < 0.001), followed by their perception of clinical alarms (p = 0.034). In addition, female nurses (p = 0.004), charge nurses (p = 0.013), and nurses who work less than 40 h per week (p = 0.008) were more likely to work better in alarm management practice. Future studies are needed to develop standardized alarm management guidelines by improving nurses’ positive perceptions of clinical alarms and patient safety culture.
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Bosma, Stephanie, and Roberta Christopher. "Implementing a Unit-Based Alarm Management Bundle for Critical Care Nurses." Critical Care Nurse 43, no. 2 (2023): 36–45. http://dx.doi.org/10.4037/ccn2023418.
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Background Clinical alarms are designed to signal an unsatisfactory patient physiological state and alert staff members to malfunctioning medical equipment. Alarm desensitization and fatigue can occur when clinicians are exposed to an overwhelming number of clinical alarms, particularly nonactionable alarms. Local Problem Alarm fatigue and alarm management competency related to use of Philips monitoring systems were noted to be problematic among nurses working in the 27-bed surgical intensive care unit of a teaching hospital in northeastern Florida. Methods A quality improvement project was conducted to reduce alarm fatigue and improve nursing competency in managing alarms. The CEASE (Communication, Electrodes, Appropriateness, Setup, and Education) evidence-based alarm management bundle was implemented on the unit, and a representative from the alarm manufacturer conducted in-service training sessions. A clinical alarms survey developed by the Healthcare Technology Foundation was distributed both before and after the intervention to 115 nurses working in the unit. Descriptive and inferential statistics were used to assess for differences between the preintervention and postintervention periods. Results Nurse participants demonstrated improved alarm management competency, resulting in significant improvements in their perceptions of alarm functionality, settings, response time, and policy adherence. There was a statistically significant decrease in self-reported alarm fatigue, and the CEASE bundle was found to influence nursing practice. Conclusions The Joint Commission’s 2022 goal of improving clinical alarm safety remains a top priority nationwide. Implementation of the CEASE alarm management bundle was effective in reducing surgical intensive care unit nurses’ alarm fatigue and improving their alarm management practices.
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Ceylan, Burcu, Leyla Baran, and Ülkü Yapucu Güneş. "Frequency of Clinical Alarms in Intensive Care Units and Nurses’ Sensitivity to Them: An Observational Study." American Journal of Critical Care 30, no. 3 (2021): 186–92. http://dx.doi.org/10.4037/ajcc2021382.
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Background All clinical alarms require nurses to respond even if an intervention is not needed. Nurses are expected to respond appropriately to each alarm and establish priorities among their care practices accordingly. This study was conducted to examine the number and types of clinical device alarms used in intensive care units, the duration of their activation, and nurses’ degree of sensitivity to them. Methods This observational study was conducted in 4 intensive care units in a university hospital in Turkey. A total of 20 nurses (5 from each unit) were observed for a total of 80 hours. The alarms were categorized as valid, false, or technical. Results During the study observation period, the mean number of alarms sounding per hour per bed was 1.8. A total of 144 alarms were recorded, of which 70.8% were valid, 15.3% were false, and 13.9% were technical. The mean duration of alarm activation was 8 minutes for valid alarms, 14 minutes for false alarms, and 53 minutes for technical alarms. Conclusions Nurses’ responses to alarms differ depending on alarm type; for alarms that do not require an emergency intervention, nurses tend to respond late or not at all.
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McNeer, Richard R., Danielle Bodzin Horn, Christopher L. Bennett, Judy Reed Edworthy, and Roman Dudaryk. "Auditory Icon Alarms Are More Accurately and Quickly Identified than Current Standard Melodic Alarms in a Simulated Clinical Setting." Anesthesiology 129, no. 1 (2018): 58–66. http://dx.doi.org/10.1097/aln.0000000000002234.
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Abstract Background Current standard audible medical alarms are difficult to learn and distinguish from one another. Auditory icons represent a new type of alarm that has been shown to be easier to learn and identify in laboratory settings by lay subjects. In this study, we test the hypothesis that icon alarms are easier to learn and identify than standard alarms by anesthesia providers in a simulated clinical setting. Methods Twenty anesthesia providers were assigned to standard or icon groups. Experiments were conducted in a simulated intensive care unit. After a brief group-specific alarm orientation, subjects identified patient-associated alarm sounds during the simulation and logged responses via a tablet computer. Each subject participated in the simulation twice and was exposed to 32 alarm annunciations. Primary outcome measures were response accuracy and response times. Secondary outcomes included assessments of perceived fatigue and task load. Results Overall accuracy rate in the standard alarm group was 43% (mean) and in the icon group was 88% (mean). Subjects in the icon group were 26.1 (odds ratio [98.75% CI, 8.4 to 81.5; P &lt; 0.001]) times more likely to correctly identify an alarm. Response times in the icon group were shorter than in the standard alarm group (12 vs. 15 s, difference 3 s [98.75% CI ,1 to 5; P &lt; 0.001]). Conclusions Under our simulated conditions, anesthesia providers more correctly and quickly identified icon alarms than standard alarms. Subjects were more likely to perceive higher fatigue and task load when using current standard alarms than icon alarms.
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Vitoux, Rachel R., Catherine Schuster, Kevin R. Glover, and Mark Dekker. "Frequency and Duration of Infusion Pump Alarms: Establishing National Benchmarks." Biomedical Instrumentation & Technology 52, no. 6 (2018): 433–41. http://dx.doi.org/10.2345/0899-8205-52.6.433.
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Abstract Reduction of clinical alarms is a priority due to alarm fatigue and the high incidence of nonactionable alarms, especially those generated from physiological monitors. However, research on infusion pump alarm types and frequencies is limited. The purpose of this study was to establish a baseline for infusion pump alarm frequencies and duration in the hospital setting. Frequency and duration of alarms across 29 hospitals using 11,410 infusion pumps revealed 987,240 alarms associated with 568,164 infusions during a consecutive 60-day period. Pump alarms accounted for only 0.8% of infusion time, with an average of 1.74 alarms per delivery and 0.18 alarms per hour. Average alarm duration was 0:02:38 (h:min:s), with 60% of alarms being addressed within 0:01:08. The most frequent alarms were keep vein open (33.77%), hold expired (27.18%), and downstream occlusion (22.94%). The medical/surgical and intensive care unit (ICU) care areas had the highest number of alarms (41.66% and 39.70% of total alarms, respectively), but pediatrics/neonatal ICU had the highest frequency of alarms per delivery (4.91). Intravenous fluids accounted for 47.16% of total alarms, with an average of 3.03 alarms per delivery, whereas parenteral nutrition and propofol had 6.77 and 6.74 average alarms per delivery, respectively. A higher average number of alarms per delivery occurred on Saturdays (1.74) and Sundays (1.73) compared with weekdays. Infusion pump alarm data collected and analyzed were sufficient to establish a reasonable baseline of infusion pump alarm types and relative frequencies for the device.
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Leigher, Debbie, Paula Kemppainen, and David M. Neyens. "Skin Preparation and Electrode Replacement to Reduce Alarm Fatigue in a Community Hospital Intensive Care Unit." American Journal of Critical Care 29, no. 5 (2020): 390–95. http://dx.doi.org/10.4037/ajcc2020120.
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Background Nurses in intensive care units are exposed to hundreds of alarms during a shift, and research shows that most alarms are not clinically relevant. Alarm fatigue can occur when a nurse becomes desensitized to alarms. Alarm fatigue can jeopardize patient safety, and adverse alarm events can lead to patients dying. Objective To evaluate how a process intervention affects the number of alarms during an 8-hour shift in an intensive care unit. Methods A total of 62 patients from an intensive care unit were included in the study; 32 of these patients received the intervention, which included washing the patient’s chest with soap and water and applying new electrocardiography electrodes at the start of a shift. The number of alarms, clinical diagnoses, and demographic variables were collected for each patient. A Poisson regression model was used to evaluate the impact of the intervention on the overall number of clinical alarms during the shift, with no adjustments to the alarm settings or other interventions. Results After relevant covariates are controlled for, the results suggest that patients in the intervention group presented significantly fewer alarms than did patients in the control group. Conclusions Managing clinical alarms is a main issue in terms of both patient safety and staff workload management. The results of this study demonstrate that a relatively simple process-oriented strategy can decrease the number of alarms.
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Day, Mary Carol, and Christopher Young. "“This is your heart speaking. Call 911.”." Ergonomics in Design: The Quarterly of Human Factors Applications 20, no. 2 (2012): 4–12. http://dx.doi.org/10.1177/1064804611435652.
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Early warning for heart attacks could save many lives. We conducted three studies to design and evaluate multimodal alarms and patient training for an implanted heart attack detector. An implanted device provided vibrotactile alarms subcutaneously, and a pager-like device provided auditory and visual alarms. Temporal alarm patterns connoted an urgent emergency alarm (“Call 911”) and a less urgent alarm (“See your doctor”). In the third, clinical, study, most patients (94%) correctly responded to the alarms at 1, 3, and 6 months after device implantation. Subcutaneous vibrotactile alarms show great potential for use in critical medical applications.
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Greer, Jasmine M., Kendall J. Burdick, Arman R. Chowdhury, and Joseph J. Schlesinger. "Dynamic Alarm Systems for Hospitals (D.A.S.H.)." Ergonomics in Design: The Quarterly of Human Factors Applications 26, no. 4 (2018): 14–19. http://dx.doi.org/10.1177/1064804618769186.
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Hospital alarms today indicate urgent clinical need, but they are seldom “true.” False alarms are contributing to the ever-increasing issue of alarm fatigue, or desensitization, among doctors and nurses. Alarm fatigue is a high-priority health care concern because of its potential to compromise health care quality and inflict harm on patients. To address this concern, we have engineered Dynamic Alarm Systems for Hospitals (D.A.S.H.), a dynamic alarm system that self-regulates alarm loudness based on the environmental noise level and incorporates differentiable and learnable alarms. D.A.S.H., with its ability to adapt to environmental noise and encode nuanced physiological information, may improve patient safety and attenuate clinician alarm fatigue.
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Nguyen, Stella Chiu, Sukardi Suba, Xiao Hu, and Michele M. Pelter. "Double Trouble: Patients With Both True and False Arrhythmia Alarms." Critical Care Nurse 40, no. 2 (2020): 14–23. http://dx.doi.org/10.4037/ccn2020363.
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Background Patients with both true and false arrhythmia alarms pose a challenge because true alarms might be buried among a large number of false alarms, leading to missed true events. Objective To determine (1) the frequency of patients with both true and false arrhythmia alarms; (2) patient, clinical, and electrocardiographic characteristics associated with both true and false alarms; and (3) the frequency and types of true and false arrhythmia alarms. Methods This was a secondary analysis using data from an alarm study conducted at a tertiary academic medical center. Results Of 461 intensive care unit patients, 211 (46%) had no arrhythmia alarms, 12 (3%) had only true alarms, 167 (36%) had only false alarms, and 71 (15%) had both true and false alarms. Ventricular pacemaker, altered mental status, mechanical ventilation, and cardiac intensive care unit admission were present more often in patients with both true and false alarms than among other patients (P &lt; .001). Intensive care unit stays were longer in patients with only false alarms (mean [SD], 106 [162] hours) and those with both true and false alarms (mean [SD], 208 [333] hours) than in other patients. Accelerated ventricular rhythm was the most common alarm type (37%). Conclusions An awareness of factors associated with arrhythmia alarms might aid in developing solutions to decrease alarm fatigue. To improve detection of true alarms, further research is needed to build and test electrocardiographic algorithms that adjust for clinical and electrocardiographic characteristics associated with false alarms.
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Pelter, Michele M., David Mortara, and Fabio Badilini. "Computer Assisted Patient Monitoring: Associated Patient, Clinical and ECG Characteristics and Strategy to Minimize False Alarms." Hearts 2, no. 4 (2021): 459–71. http://dx.doi.org/10.3390/hearts2040036.
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This chapter is a review of studies that have examined false arrhythmia alarms during in-hospital electrocardiographic (ECG) monitoring in the intensive care unit. In addition, we describe an annotation effort being conducted at the UCSF School of Nursing, Center for Physiologic Research designed to improve algorithms for lethal arrhythmias (i.e., asystole, ventricular fibrillation, and ventricular tachycardia). Background: Alarm fatigue is a serious patient safety hazard among hospitalized patients. Data from the past five years, showed that alarm fatigue was responsible for over 650 deaths, which is likely lower than the actual number due to under-reporting. Arrhythmia alarms are a common source of false alarms and 90% are false. While clinical scientists have implemented a number of interventions to reduce these types of alarms (e.g., customized alarm settings; daily skin electrode changes; disposable vs. non-disposable lead wires; and education), only minor improvements have been made. This is likely as these interventions do not address the primary problem of false arrhythmia alarms, namely deficient and outdated arrhythmia algorithms. In this chapter we will describe a number of ECG features associated with false arrhythmia alarms. In addition, we briefly discuss an annotation effort our group has undertaken to improve lethal arrhythmia algorithms.
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Torres, Adalberto, David E. Milov, Daniela Melendez, Joseph Negron, John J. Zhao, and Stephen T. Lawless. "A new approach to alarm management: mitigating failure-prone systems." Journal of Hospital Administration 3, no. 6 (2014): 79. http://dx.doi.org/10.5430/jha.v3n6p79.
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Alarm management that effectively reduces alarm fatigue and improves patient safety has yet to be convincingly demonstrated. The leaders of our newly constructed children’s hospital envisioned and created a hospital department dedicated to tackling this daunting task. The Clinical Logistics Center (CLC) is the hospital’s hub where all of its monitoring technology is integrated and tracked twenty-four hours a day, seven days a week by trained paramedics. Redundancy has been added to the alarm management process through automatic escalation of alarms from bedside staff to CLC staff in a timely manner. The paramedic alerting the bedside staff to true alarms based on good signal quality and confirmed by direct visual confirmation of the patient through bedside cameras distinguishes true alarms from nuisance/false alarms in real time. Communication between CLC and bedside staff occurs primarily via smartphone texts to avoid disruption of clinical activities. The paramedics also continuously monitor physiologic variables for early indicators of clinical deterioration, which leads to early interventions through mechanisms such as rapid response team activation. Hands-free voice communication via room intercoms facilitates CLC logistical support of the bedside staff during acute clinical crises/resuscitations. Standard work is maintained through protocol-driven process steps and serial training of both bedside and CLC staff. This innovative approach to prioritize alarms for the bedside staff is a promising solution to improving alarm management.
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Yu, Denny, Marian Obuseh, and Poching DeLaurentis. "Quantifying the Impact of Infusion Alerts and Alarms on Nursing Workflows: A Retrospective Analysis." Applied Clinical Informatics 12, no. 03 (2021): 528–38. http://dx.doi.org/10.1055/s-0041-1730031.
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Abstract Background Smart infusion pumps affect workflows as they add alerts and alarms in an information-rich clinical environment where alarm fatigue is already a major concern. An analytic approach is needed to quantify the impact of these alerts and alarms on nursing workflows and patient safety. Objectives To analyze a detailed infusion dataset from a smart infusion pump system and identify contributing factors for infusion programming alerts, operational alarms, and alarm resolution times. Methods We analyzed detailed infusion pump data across four hospitals in a health system for up to 1 year. The prevalence of alerts and alarms was grouped by infusion type and a selected list of 32 high-alert medications (HAMs). Logistic regression was used to explore the relationship between a set of risk factors and the occurrence of alerts and alarms. We used nonparametric tests to explore the relationship between alarm resolution times and a subset of predictor variables. Results The study dataset included 745,641 unique infusions with a total of 3,231,300 infusion events. Overall, 28.7% of all unique infusions had at least one operational alarm, and 2.1% of all unique infusions had at least one programming alert. Alarms averaged two per infusion, whereas at least one alert happened in every 48 unique infusions. Eight percent of alarms took over 4 minutes to resolve. Intravenous fluid infusions had the highest rate of error-state occurrence. HAMs had 1.64 more odds for alerts than the rest of the infusions. On average, HAMs had a higher alert rate than maintenance fluids. Conclusion Infusion pump alerts and alarms impact clinical care, as alerts and alarms by design interrupt clinical workflow. Our study showcases how hospital system leadership teams can leverage infusion pump informatics to prioritize quality improvement and patient safety initiatives pertaining to infusion practices.
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Talley, Linda B., Jeffrey Hooper, Brian Jacobs, et al. "Cardiopulmonary Monitors and Clinically Significant Events in Critically Ill Children." Biomedical Instrumentation & Technology 45, s1 (2011): 38–45. http://dx.doi.org/10.2345/0899-8205-45.s1.38.
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Abstract Cardiopulmonary monitors (CPMs) generate false alarm rates ranging from 85%–99% with few of these alarms actually representing serious clinical events. The overabundance of clinically insignificant alarms in hospitals desensitizes the clinician to true-positive alarms and poses significant safety issues. In this IRB-approved externally funded study, we sought to assess the clinical conditions associated with true and false-positive CPM alarms and attempted to define optimal alarm parameters that would reduce false-positive alarm rates (as they relate to clinically significant events) and thus improve overall CPM performance in critically ill children. Prior to the study, clinically significant events (CSEs) were defined and validated. Over a seven-month period in 2009, critically ill children underwent evaluation of CSEs while connected to a CPM. Comparative CPM and CSE data were analyzed with an aim to estimate sensitivity, specificity, and positive and negative predictive values for CSEs. CPM and CSE data were evaluated in 98 critically ill children. Overall, 2,245 high priority alarms were recorded with 68 CSEs noted in 45 observational days. During the course of the study, the team developed a firm understanding of CPM functionality, including the pitfalls associated with aggregation and analysis of CPM alarm data. The inability to capture all levels of CPM alarms represented a significant study challenge. Selective CPM data can be easily queried with standard reporting, however the default settings with this reporting exclude critical information necessary in compiling a coherent study denominator database. Although the association between CPM alarms and CSEs could not be comprehensively evaluated, preliminary analysis reflected poor CPM alarm specificity. This study provided the necessary considerations for the proper design of a future study that improves the positive predictive value of CPM alarms. In addition, this investigation has resulted in improved awareness of CPM alarm parameter settings and associated false-positive alarms. This information has been incorporated into nursing educational programs.
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Kobayashi, Leo, John W. Gosbee, and Derek L. Merck. "Development and Application of a Clinical Microsystem Simulation Methodology for Human Factors-Based Research of Alarm Fatigue." HERD: Health Environments Research & Design Journal 10, no. 4 (2016): 91–104. http://dx.doi.org/10.1177/1937586716673829.
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Objectives: (1) To develop a clinical microsystem simulation methodology for alarm fatigue research with a human factors engineering (HFE) assessment framework and (2) to explore its application to the comparative examination of different approaches to patient monitoring and provider notification. Background: Problems with the design, implementation, and real-world use of patient monitoring systems result in alarm fatigue. A multidisciplinary team is developing an open-source tool kit to promote bedside informatics research and mitigate alarm fatigue. Method: Simulation, HFE, and computer science experts created a novel simulation methodology to study alarm fatigue. Featuring multiple interconnected simulated patient scenarios with scripted timeline, “distractor” patient care tasks, and triggered true and false alarms, the methodology incorporated objective metrics to assess provider and system performance. Developed materials were implemented during institutional review board–approved study sessions that assessed and compared an experimental multiparametric alerting system with a standard monitor telemetry system for subject response, use characteristics, and end-user feedback. Results: A four-patient simulation setup featuring objective metrics for participant task-related performance and response to alarms was developed along with accompanying structured HFE assessment (questionnaire and interview) for monitor systems use testing. Two pilot and four study sessions with individual nurse subjects elicited true alarm and false alarm responses (including diversion from assigned tasks) as well as nonresponses to true alarms. In-simulation observation and subject questionnaires were used to test the experimental system’s approach to suppressing false alarms and alerting providers. Conclusions: A novel investigative methodology applied simulation and HFE techniques to replicate and study alarm fatigue in controlled settings for systems assessment and experimental research purposes.
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Bawua, Linda K., Christine Miaskowski, Sukardi Suba, et al. "Thoracic Impedance Pneumography–Derived Respiratory Alarms and Associated Patient Characteristics." American Journal of Critical Care 31, no. 5 (2022): 355–65. http://dx.doi.org/10.4037/ajcc2022295.
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Background Respiratory rate (RR) alarms alert clinicians to a change in a patient’s condition. However, RR alarms are common occurrences. To date, no study has examined RR alarm types and associated patient characteristics, which could guide alarm management strategies. Objectives To characterize RR alarms by type, frequency, duration, and associated patient demographic and clinical characteristics. Methods A secondary data analysis of alarms generated with impedance pneumography in 461 adult patients admitted to either a cardiac, a medical/surgical, or a neurological intensive care unit (ICU). The RR alarms included high parameter limit (≥30 breaths/min), low parameter limit (≤5 breaths/min), and apnea (no breathing ≥20 s). The ICU type; total time monitored; and alarm type, frequency, and duration were evaluated. Results Of 159 771 RR alarms, parameter limit alarms (n = 140 975; 88.2%) were more frequent than apnea alarms (n = 18 796; 11.8%). High parameter limit alarms were most frequent (n = 131 827; 82.5%). After ICU monitoring time was controlled for, multivariate analysis showed that alarm rates were higher in patients in the cardiac and neurological ICUs (P = .001), patients undergoing mechanical ventilation (P = .005), and patients without a ventricular assist device or pacemaker (P = .02). Male sex was associated with low parameter limit (P = .01) and apnea (P = .005) alarms. Conclusion High parameter limit RR alarms were most frequent. Factors associated with RR alarms included monitoring time, ICU type, male sex, and mechanical ventilation. Although these factors are not modifiable, these data could be used to guide management strategies.
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Nakhal, Mohamad Al, Mirna Fawaz, Karim Khabaz, Ahmad Rayan, Salam Bani Hani, and Mohammed ALBashtawy. "Critical care nurses and their clinical reasoning for customizing monitor alarms: a mixed-method study." Frontiers of Nursing 11, no. 4 (2024): 457–67. https://doi.org/10.2478/fon-2024-0050.
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Abstract Objective To explore the clinical rationale of critical care nurses for personalizing monitor alarms. One of the most crucial jobs assigned to critical care nurses is monitoring patients’ physiological indicators and carrying out the necessary associated interventions. Successful use of equipment in the nursing practice environment will be improved by a thorough understanding of the nurse’s approach to alarm configuration. Methods A mixed-method design integrating quantitative and qualitative components was used. The sample of this study recruited a convenience sample of 60 nurses who have worked in critical care areas. This study took place at Lebanese American University Medical Center Rizk Hospital, utilizing a semi-structured interview with participants. Results The study demonstrated the high incidence of nuisance alarms and the desensitization of critical care nurses to vital ones. According to the nurses, frequent false alarms and a shortage of staff are the 2 main causes of alarm desensitization. Age was significantly associated with the perception of Smart alarms, according to the data (P = 0.03). Four interconnected themes and subcategories that reflect the clinical reasoning process for alarm customization were developed as a result of the study’s qualitative component: (1) unit alarm environment; (2) nursing style; (3) motivation to customize; and (4) clinical and technological customization. Conclusions According to this study, nurses believe that alarms are valuable. However, a qualitative analysis of the experiences revealed that customization has been severely limited since the healthcare team depends on nurses to complete these tasks independently. Additionally, a staffing shortage and lack of technical training at the start of placement have also hindered customization.
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van Rossum, Huub H., and Daan van den Broek. "Ten-Month Evaluation of the Routine Application of Patient Moving Average for Real-Time Quality Control in a Hospital Setting." Journal of Applied Laboratory Medicine 5, no. 6 (2020): 1184–93. http://dx.doi.org/10.1093/jalm/jfaa071.
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Abstract Background In recent years there has been renewed interest in patient-based real-time quality control (PBRTQC) techniques. This interest has been stimulated by the availability of new optimization and validation methods. Only a limited amount of research has focused on investigating the true operational value of PBRTQC. Therefore, we have evaluated the performance and value of recently implemented patient moving average quality control (MA QC) procedures. Methods The MA QC settings and protocols were as previously described (Clin Chem Lab Med 2019;57:1329–38) and included MA QCs for 10 chemistry and 6 hematological tests, all performed on duplicate analyzer systems. All MA QC alarms that occurred during the first 10 months of routine clinical application were investigated for assay-specific alarm rate and occurrence in time. Furthermore, the causes of these MA QC alarms were investigated, and alarm relevance was determined on the basis of total allowable bias (TBa) and error (TEa) derived from biological variations. Results During the 10-month period, 202 individual MA QC alarms occurred, resulting in an overall MA QC alarm rate of 0.030% and a frequency of 4.67 per week. Most alarms were triggered by sodium MA QC. Based on all available fully executed and documented MA QC alarm work-ups, MA QC detected errors that in 26.0% of the alarms exceeded the TBa and in 13.7% the TEa. In 9.2% of the alarms, MA QC alarming triggered instant (technical) corrections. Conclusions Routine clinical application of MA QC is feasible with maintaining a manageable number of alarms and enabling detection of relevant analytical errors.
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Ali Al-Quraan, Hamza, Amjad Eid, and Aladeen Alloubani. "Assessment of Alarm Fatigue Risk Among Oncology Nurses in Jordan." SAGE Open Nursing 9 (January 2023): 237796082311707. http://dx.doi.org/10.1177/23779608231170730.
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Introduction Using technology in the clinical setting where clinical alarms frequently occur, resulting in many false alarms, which is called alarm fatigue, alarm fatigue may increase nurses’ distraction, and that might negatively affect patient safety. Objective This study aimed to assess alarm fatigue among oncology nurses in Jordan. Methods A descriptive cross-sectional design was used in a non-profit specialized cancer center. A self-reported questionnaire was answered by nurses who participated in the study. Results A total of 222 questionnaires were analyzed with a more than 95% response rate. More than half of the sample (60.4%) were females. The participants were young nurses with a mean age of 25.18 ± 3.33 years. The total mean score of alarm fatigue was 31.62 ± 7.14 on a scale ranging from zero to 52. Post-hoc analysis showed that the palliative unit (25.73 ± 7.22) and emergency room (28.73 ± 6.62) had low scores of total mean alarm fatigue than remaining area of practice, such as the ICU (33.92 ± 6.99); p-value: .004. Conclusion Alarm fatigue is a global issue affecting many practice areas. An educational program is recommended for nurses to learn how to deal with alarm fatigue. In order to effectively manage alarms, nurses’ education and individual training are crucial.
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Fernandes, Chrystinne, Simon Miles, and Carlos José Pereira Lucena. "Detecting False Alarms by Analyzing Alarm-Context Information: Algorithm Development and Validation." JMIR Medical Informatics 8, no. 5 (2020): e15407. http://dx.doi.org/10.2196/15407.
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Background Although alarm safety is a critical issue that needs to be addressed to improve patient care, hospitals have not given serious consideration about how their staff should be using, setting, and responding to clinical alarms. Studies have indicated that 80%-99% of alarms in hospital units are false or clinically insignificant and do not represent real danger for patients, leading caregivers to miss relevant alarms that might indicate significant harmful events. The lack of use of any intelligent filter to detect recurrent, irrelevant, and/or false alarms before alerting health providers can culminate in a complex and overwhelming scenario of sensory overload for the medical team, known as alarm fatigue. Objective This paper’s main goal is to propose a solution to mitigate alarm fatigue by using an automatic reasoning mechanism to decide how to calculate false alarm probability (FAP) for alarms and whether to include an indication of the FAP (ie, FAP_LABEL) with a notification to be visualized by health care team members designed to help them prioritize which alerts they should respond to next. Methods We present a new approach to cope with the alarm fatigue problem that uses an automatic reasoner to decide how to notify caregivers with an indication of FAP. Our reasoning algorithm calculates FAP for alerts triggered by sensors and multiparametric monitors based on statistical analysis of false alarm indicators (FAIs) in a simulated environment of an intensive care unit (ICU), where a large number of warnings can lead to alarm fatigue. Results The main contributions described are as follows: (1) a list of FAIs we defined that can be utilized and possibly extended by other researchers, (2) a novel approach to assess the probability of a false alarm using statistical analysis of multiple inputs representing alarm-context information, and (3) a reasoning algorithm that uses alarm-context information to detect false alarms in order to decide whether to notify caregivers with an indication of FAP (ie, FAP_LABEL) to avoid alarm fatigue. Conclusions Experiments were conducted to demonstrate that by providing an intelligent notification system, we could decide how to identify false alarms by analyzing alarm-context information. The reasoner entity we described in this paper was able to attribute FAP values to alarms based on FAIs and to notify caregivers with a FAP_LABEL indication without compromising patient safety.
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Lewandowska, Katarzyna, Magdalena Weisbrot, Aleksandra Cieloszyk, Wioletta Mędrzycka-Dąbrowska, Sabina Krupa, and Dorota Ozga. "Impact of Alarm Fatigue on the Work of Nurses in an Intensive Care Environment—A Systematic Review." International Journal of Environmental Research and Public Health 17, no. 22 (2020): 8409. http://dx.doi.org/10.3390/ijerph17228409.
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Background: In conditions of intensive therapy, where the patients treated are in a critical condition, alarms are omnipresent. Nurses, as they spend most of their time with patients, monitoring their condition 24 h, are particularly exposed to so-called alarm fatigue. The purpose of this study is to review the literature available on the perception of clinical alarms by nursing personnel and its impact on work in the ICU environment. Methods: A systematic review of the literature was carried out according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol. The content of electronic databases was searched through, i.e., PubMed, OVID, EBSCO, ProQuest Nursery, and Cochrane Library. The keywords used in the search included: “intensive care unit,” “nurse,” “alarm fatigue,” “workload,” and “clinical alarm.” The review also covered studies carried out among nurses employed at an adult intensive care unit. Finally, seven publications were taken into consideration. Data were analyzed both descriptively and quantitatively, calculating a weighted average for specific synthetized data. Results: In the analyzed studies, 389 nurses were tested, working in different intensive care units. Two studies were based on a quality model, while the other five described the problem of alarms in terms of quantity, based on the HTF (Healthcare Technology Foundation) questionnaire. Intensive care nurses think that alarms are burdensome and too frequent, interfering with caring for patients and causing reduced trust in alarm systems. They feel overburdened with an excessive amount of duties and a continuous wave of alarms. Having to operate modern equipment, which is becoming more and more advanced, takes time that nurses would prefer to dedicate to their patients. There is no clear system for managing the alarms of monitoring devices. Conclusion: Alarm fatigue may have serious consequences, both for patients and for nursing personnel. It is necessary to introduce a strategy of alarm management and for measuring the alarm fatigue level.
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Zahradka, Nicole, Sophie Geoghan, Hope Watson, Eli Goldberg, Adam Wolfberg, and Matt Wilkes. "Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset." Bioengineering 10, no. 1 (2022): 37. http://dx.doi.org/10.3390/bioengineering10010037.
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The importance of vital sign monitoring to detect deterioration increases during healthcare at home. Continuous monitoring with wearables increases assessment frequency but may create information overload for clinicians. The goal of this work was to demonstrate the impact of vital sign observation frequency and alarm settings on alarms in a real-world dataset. Vital signs were collected from 76 patients admitted to healthcare at home programs using the Current Health (CH) platform; its wearable continuously measured respiratory rate (RR), pulse rate (PR), and oxygen saturation (SpO2). Total alarms, alarm rate, patient rate, and detection time were calculated for three alarm rulesets to detect changes in SpO2, PR, and RR under four vital sign observation frequencies and four window sizes for the alarm algorithms’ median filter. Total alarms ranged from 65 to 3113. The alarm rate and early detection increased with the observation frequency for all alarm rulesets. Median filter windows reduced alarms triggered by normal fluctuations in vital signs without compromising the granularity of time between assessments. Frequent assessments enabled with continuous monitoring support early intervention but need to pair with settings that balance sensitivity, specificity, clinical risk, and provider capacity to respond when a patient is home to minimize clinician burden.
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Burdick, Kendall, Madison Courtney, Mark Wallace, Sarah Baum Miller, and Joseph Schlesinger. "Living and Working in a Multisensory World: From Basic Neuroscience to the Hospital." Multimodal Technologies and Interaction 3, no. 1 (2019): 2. http://dx.doi.org/10.3390/mti3010002.
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The intensive care unit (ICU) of a hospital is an environment subjected to ceaseless noise. Patient alarms contribute to the saturated auditory environment and often overwhelm healthcare providers with constant and false alarms. This may lead to alarm fatigue and prevent optimum patient care. In response, a multisensory alarm system developed with consideration for human neuroscience and basic music theory is proposed as a potential solution. The integration of auditory, visual, and other sensory output within an alarm system can be used to convey more meaningful clinical information about patient vital signs in the ICU and operating room to ultimately improve patient outcomes.
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Petersen, Emalie M., and Cindy L. Costanzo. "Assessment of Clinical Alarms Influencing Nurses’ Perceptions of Alarm Fatigue." Dimensions of Critical Care Nursing 36, no. 1 (2017): 36–44. http://dx.doi.org/10.1097/dcc.0000000000000220.
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Suba, Sukardi, Cass Sandoval, Xiao Hu, and Michele Pelter. "ECG Monitoring during End of Life Care: Implications on Alarm Fatigue." Multimodal Technologies and Interaction 3, no. 1 (2019): 18. http://dx.doi.org/10.3390/mti3010018.
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Excessive numbers of clinical alarms in the intensive care unit (ICU) contribute to alarm fatigue. Efforts to eliminate unnecessary alarms, including during end of life (EOL) care, are pivotal. This study describes electrocardiographic (ECG) arrhythmia alarm usage following the decision for comfort care. We conducted a review of electronic health records (EHR) in patients who died and had comfort care orders that were in place during our study. The occurrences of ECG arrhythmia alarms among these patients were examined. We found 151 arrhythmia alarms that were generated in 11 patients after comfort care was initiated: 72% were audible, 21% were manually muted, and 7% had an unknown audio label. Level of alarm: 33% crisis, 58% warning, 1% message, and 8% were labeled unknown. Our report shows that ECG monitoring was commonly maintained during the EOL care. Since the goal of care during this phase is for both patient and family comfort, it is important for the clinicians to weigh the benefits versus harms of the continuous ECG monitoring.
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Deschamps, Marie-Lys F. A., and Penelope M. Sanderson. "Multiple Patient Monitoring in High Dependency Units: A Field Study." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 669. http://dx.doi.org/10.1177/1071181319631326.
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Much of the focus related to alarm fatigue has been directed towards reducing the number of alarms associated with vital sign monitoring. However, recent fieldwork conducted in four high dependency and critical care units of an Australian hospital suggests that the most problematic alarms were often unassociated with vital signs, such as IV pumps and mattress alarms. Many nurses indicated that they like alarms, even when false, because they support awareness of their patients’ well-being. Results of the fieldwork are guiding the design of a simulation study investigating clinical monitoring displays.
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Kusanto, B., M. Visser, N. Wandare, et al. "P0964 The effect of alarms on completion of electronic diaries in patients with inflammatory bowel disease." Journal of Crohn's and Colitis 19, Supplement_1 (2025): i1798. https://doi.org/10.1093/ecco-jcc/jjae190.1138.
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Abstract Background Clinical trials have contributed substantially to the development of novel therapies for inflammatory bowel disease, including Crohn’s disease (CD) and ulcerative colitis (UC). The Food and Drug Administration (FDA) recommends the use of the Crohn’s Disease and Activity Index (CDAI) and the modified Mayo Score (mMS) to measure primary endpoints in CD and UC trials, respectively. Both assessments use composite scores requiring the completion of a daily diary by subjects to report on symptoms, including stool frequency (SF), rectal bleeding, abdominal pain, and general well-being. In order to ensure the timely completion of diaries, and to limit missing days, it has been recommended to implement device alarms or reminders. The objective of this study was to investigate how device alarms and/or reminders can influence completion times of the daily electronic diaries (eDiaries) in CD and UC studies. Methods More than 3.7 million eDiary entries from 12 153 patients across 11 studies in CD and UC were evaluated. Only completed entries were included. Patients were required to complete eDiaries daily, either on their personal device or a provisioned device, throughout their participation in a specific study. Daily alarms were programmed to remind patients to complete their eDiary. For this analysis, the difference between the patient’s eDiary alarm time and the time the eDiary was first opened was determined. Results For CD trials, 65% (n=1 079 823) of eDiaries were opened after the programmed alarm time. Of these eDiary entries, 39% (n=652 138) were answered 30 minutes after the alarm time, and 8% (n=127 711) were answered between 30 minutes and an hour after the alarm time. In UC trials, 60% (n=1 277 090) of eDiaries were opened after the programmed alarm time. Similarly, 38% (n=822 552) of eDiaries were completed after 30 minutes of the alarm time, and 8% (n=170 433) were completed between 30 minutes and an hour after the alarm time. Conclusion The implementation of eDiary alarms is essential to support patient compliance in clinical trials and drive reliable inferences. The analysis performed here suggests that eDiary alarms are useful to encourage patients to answer their eDiary within an hour reporting window of their scheduled alarm time. Nevertheless, sites and study teams should continue to educate patients on the importance of eDiary completion.
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Korniewicz, Denise M., Tobey Clark, and Yadin David. "A National Online Survey on the Effectiveness of Clinical Alarms." American Journal of Critical Care 17, no. 1 (2008): 36–41. http://dx.doi.org/10.4037/ajcc2008.17.1.36.
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Purpose To develop a national online survey to be administered by the American College of Clinical Engineers Healthcare Technology Foundation to hospitals and healthcare workers to determine the problems associated with alarms in hospitals. Methods An online survey was developed by a 16-member task force representing professionals from clinical engineering, nursing, and technology to evaluate the reasons health-care workers do not respond to clinical alarms. Results A total of 1327 persons responded to the survey; most (94%) worked in acute care hospitals. About half of the respondents were registered nurses (51%), and one-third of respondents (31%) worked in a critical care unit. Most respondents (&gt;90%) agreed or strongly agreed with the statements covering the purpose of clinical alarms and the need for prioritized and easily differentiated audible and visual alarms. Likewise, many respondents identified nuisance alarms as problematic; most agreed or strongly agreed that the alarms occur frequently (81%), disrupt patient care (77%), and can reduce trust in alarms and cause caregivers to disable them (78%). Conclusions Effective clinical alarm management relies on (1) equipment designs that promote appropriate use, (2) clinicians who take an active role in learning how to use equipment safely over its full range of capabilities, and (3) hospitals that recognize the complexities of managing clinical alarms and devote the necessary resources to develop effective management schemes.
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Kovacs, Boldizsar, Haran Burri, Andres Buehler, et al. "High Incidence of Inappropriate Alarms in Patients with Wearable Cardioverter-Defibrillators: Findings from the Swiss WCD Registry." Journal of Clinical Medicine 10, no. 17 (2021): 3811. http://dx.doi.org/10.3390/jcm10173811.
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Background: The wearable cardioverter defibrillator (WCD) uses surface electrodes to detect arrhythmia before initiating a treatment sequence. However, it is also prone to inappropriate detection due to artefacts. Objective: The aim of this study is to assess the alarm burden in patients and its impact on clinical outcomes. Methods: Patients from the nationwide Swiss WCD Registry were included. Clinical characteristics and data were obtained from the WCDs. Arrhythmia recordings ≥30 s in length were analysed and categorized as VT/VF, atrial fibrillation (AF), supraventricular tachycardia (SVT) or artefact. Results: A total of 10653 device alarms were documented in 324 of 456 patients (71.1%) over a mean WCD wear-time of 2.0 ± 1.6 months. Episode duration was 30 s or more in 2996 alarms (28.2%). One hundred and eleven (3.7%) were VT/VF episodes. The remaining recordings were inappropriate detections (2736 (91%) due to artefacts; 117 (3.7%) AF; 48 (1.6%) SVT). Two-hundred and seven patients (45%) had three or more alarms per month. Obesity was significantly associated with three or more alarms per month (p = 0.01, 27.7% vs. 15.9%). High alarm burden was not associated with a lower average daily wear time (20.8 h vs. 20.7 h, p = 0.785) or a decreased implantable cardioverter defibrillator implantation rate after stopping WCD use (48% vs. 47.3%, p = 0.156). Conclusions: In patients using WCDs, alarms emitted by the device and impending inappropriate shocks were frequent and most commonly caused by artefacts. A high alarm burden was associated with obesity but did not lead to a decreased adherence.
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Jeong, Yu Jin, and Hyunjung Kim. "Evaluation of Clinical Alarms and Alarm Management in Intensive Care Units." Journal of Korean Biological Nursing Science 20, no. 4 (2017): 228–35. http://dx.doi.org/10.7586/jkbns.2018.20.4.228.
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Viet, Dao Duy, Nguyen Tra My, and Nguyen Thi Doai. "Anxiety level in patients with vital signs monitor at Cardiovascular Center, Hanoi Medical University." Tạp chí Nghiên cứu Y học 184, no. 11E15 (2024): 117–23. http://dx.doi.org/10.52852/tcncyh.v184i11e15.2719.
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The Cardiovascular Center at Hanoi Medical University Hospital (HMUH) routinely employs vital signs monitoring systems for patient in severe conditions, post-intervention, and post-cardiothoracic surgery. However, confining patients to their beds often causes significant inconvenience. Additionally, alarm signals from these systems, while crucial for safety, can often be clinically insignificant, leading to patient anxiety. This study aimed to assess the anxiety levels and experiences of patients connected to continuous monitoring systems. Conducted between February and May 2024 at the Cardiovascular Center (HMUH), the cross-sectional study involved 108 patients who had been continuously monitored for at least 24 hours. Data were collected on demographics, reasons for monitoring, alarm frequency, clinical significance of alarms, and anxiety levels using the Hospital Anxiety Depression Scale (HADS). Results indicated some notable results, continuous monitoring was primarily due to post-cardiovascular interventions (51.9%), a significant majority (96.8%) experienced more than 12 alarms per day, but only 38.7% of these alarms had clinical significance. Anxiety levels were notably high, with 33.4% having anxiety. Major factors contributing to patient discomfort included sound and limitations in personal care. Continuous monitoring significantly impacts patient anxiety and comfort, primarily due to excessive non-significant alarms and restricted mobility.
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Fernandes, Chrystinne Oliveira, Simon Miles, Carlos José Pereira De Lucena, and Donald Cowan. "Artificial Intelligence Technologies for Coping with Alarm Fatigue in Hospital Environments Because of Sensory Overload: Algorithm Development and Validation." Journal of Medical Internet Research 21, no. 11 (2019): e15406. http://dx.doi.org/10.2196/15406.
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Background Informed estimates claim that 80% to 99% of alarms set off in hospital units are false or clinically insignificant, representing a cacophony of sounds that do not present a real danger to patients. These false alarms can lead to an alert overload that causes a health care provider to miss important events that could be harmful or even life-threatening. As health care units become more dependent on monitoring devices for patient care purposes, the alarm fatigue issue has to be addressed as a major concern for the health care team as well as to enhance patient safety. Objective The main goal of this paper was to propose a feasible solution for the alarm fatigue problem by using an automatic reasoning mechanism to decide how to notify members of the health care team. The aim was to reduce the number of notifications sent by determining whether or not to group a set of alarms that occur over a short period of time to deliver them together, without compromising patient safety. Methods This paper describes: (1) a model for supporting reasoning algorithms that decide how to notify caregivers to avoid alarm fatigue; (2) an architecture for health systems that support patient monitoring and notification capabilities; and (3) a reasoning algorithm that specifies how to notify caregivers by deciding whether to aggregate a group of alarms to avoid alarm fatigue. Results Experiments were used to demonstrate that providing a reasoning system can reduce the notifications received by the caregivers by up to 99.3% (582/586) of the total alarms generated. Our experiments were evaluated through the use of a dataset comprising patient monitoring data and vital signs recorded during 32 surgical cases where patients underwent anesthesia at the Royal Adelaide Hospital. We present the results of our algorithm by using graphs we generated using the R language, where we show whether the algorithm decided to deliver an alarm immediately or after a delay. Conclusions The experimental results strongly suggest that this reasoning algorithm is a useful strategy for avoiding alarm fatigue. Although we evaluated our algorithm in an experimental environment, we tried to reproduce the context of a clinical environment by using real-world patient data. Our future work is to reproduce the evaluation study based on more realistic clinical conditions by increasing the number of patients, monitoring parameters, and types of alarm.
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Satish, Kalyani, and Kirti Udayi. "Failure Mode Effect Analysis on Clinical Alarms." International Journal of Science and Research (IJSR) 10, no. 10 (2021): 1565–74. https://doi.org/10.21275/sr22628100839.
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Waterson, James, and Arkadiusz Bedner. "Types and Frequency of Infusion Pump Alarms and Infusion-Interruption to Infusion-Recovery Times for Critical Short Half-Life Infusions: Retrospective Data Analysis." JMIR Human Factors 6, no. 3 (2019): e14123. http://dx.doi.org/10.2196/14123.
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Background Alarm fatigue commonly leads to a reduced response to alarms. Appropriate and timely response to intravenous pump alarms is crucial to infusion continuity. The difficulty of filtering out critical short half-life infusion alarms from nonurgent alarms is a key challenge for risk management for clinicians. Critical care areas provide ample opportunities for intravenous medication error with the frequent administration of high-alert, critical short half-life infusions that require rigorous maintenance for continuity of delivery. Most serious medication errors in critical care occur during the execution of treatment, with performance-level failures outweighing rule-based or knowledge-based mistakes. Objective One objective of this study was to establish baseline data for the types and frequency of alarms that critical care clinicians are exposed to from a variety of infusion devices, including both large volume pumps and syringe drivers. Another objective was to identify the volume of these alarms that specifically relate to critical short half-life infusions and to evaluate user response times to alarms from infusion devices delivering these particular infusions. Methods The event logs of 1183 infusion pumps used in critical care environments and in general care areas within the European region were mined for a range of alarm states. The study then focused on a selection of infusion alarms from devices delivering critical short half-life infusions that would warrant rapid attention from clinicians in order to avoid potentially harmful prolonged infusion interruption. The reaction time of clinicians to infusion-interruption states and alarms for the selected critical short half-life infusions was then calculated. Results Initial analysis showed a mean average of 4.50 alarms per infusion in the general critical care pump population as opposed to the whole hospital rate of 1.39. In the pediatric intensive care unit (PICU) group, the alarms per infusion value was significantly above the mean average for all critical care areas, with 8.61 alarms per infusion. Infusion-interruption of critical short half-life infusions was found to be a significant problem in all areas of the general critical care pump population, with a significant number of downstream (ie, vein and access) occlusion events noted. While the mean and median response times to critical short half-life infusion interruptions were generally within the half-lives of the selected medications, there was a high prevalence of outliers in terms of reaction times for all the critical short half-life infusions studied. Conclusions This study gives an indication of what might be expected in critical care environments in terms of the volume of general infusion alarms and critical short half-life infusion alarms, as well as for clinician reaction times to critical short half-life infusion-interruption events. This study also identifies potentially problematic areas of the hospital for alarm fatigue and for particular issues of infusion and infusion-line management. Application of the proposed protocols can help create benchmarks for pump alarm management and clinician reaction times. These protocols can be applied to studies on the impact of alarm fatigue and for the evaluation of protocols, infusion-monitoring strategies, and infusion pump-based medication safety software aimed at reducing alarm fatigue and ensuring the maintenance of critical short half-life infusions. Given the frequency of infusion alarms seen in this study, the risk of alarm fatigue due to the white noise of pump alarms present in critical care, to which clinicians are constantly exposed, is very high. Furthermore, the added difficulties of maintaining critical short half-life infusions, and other infusions in specialist areas, are made clear by the high ratio of downstream occlusion to infusion starts in the neonatal intensive care unit (NICU). The ability to quantitatively track the volume of alarms and clinician reaction times contributes to a greater understanding of the issues of alarm fatigue in intensive care units. This can be applied to clinical audit, can allow for targeted training to reduce nuisance alarms, and can aid in planning for improvement in the key area of maintenance of steady-state plasma levels of critical short half-life infusions. One clear conclusion is that the medication administration rights should be extended to include right maintenance and ensured delivery continuity of critical short half-life infusions.
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Gajowniczek, Krzysztof, Iga Grzegorczyk, and Tomasz Ząbkowski. "Reducing False Arrhythmia Alarms Using Different Methods of Probability and Class Assignment in Random Forest Learning Methods." Sensors 19, no. 7 (2019): 1588. http://dx.doi.org/10.3390/s19071588.
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The literature indicates that 90% of clinical alarms in intensive care units might be false. This high percentage negatively impacts both patients and clinical staff. In patients, false alarms significantly increase stress levels, which is especially dangerous for cardiac patients. In clinical staff, alarm overload might lead to desensitization and could result in true alarms being ignored. In this work, we applied the random forest method to reduce false arrhythmia alarms and specifically explored different methods of probability and class assignment, as these affect the classification accuracy of the ensemble classifiers. Due to the complex nature of the problem, i.e., five types of arrhythmia and several methods to determine probability and the alarm class, a synthetic measure based on the ranks was proposed. The novelty of this contribution is the design of a synthetic measure that helps to leverage classification results in an ensemble model that indicates a decision path leading to the best result in terms of the area under the curve (AUC) measure or the global accuracy (score). The results of the research are promising. The best performance in terms of the AUC was 100% accuracy for extreme tachycardia, whereas the poorest results were for ventricular tachycardia at 87%. Similarly, in terms of the accuracy, the best results were observed for extreme tachycardia (91%), whereas ventricular tachycardia alarms were the most difficult to detect, with an accuracy of only 51%.
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Cho, Ok Min, Hwasoon Kim, Young Whee Lee, and Insook Cho. "Clinical Alarms in Intensive Care Units: Perceived Obstacles of Alarm Management and Alarm Fatigue in Nurses." Healthcare Informatics Research 22, no. 1 (2016): 46. http://dx.doi.org/10.4258/hir.2016.22.1.46.
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Albanowski, Kimberly, Kendall J. Burdick, Christopher P. Bonafide, Ruth Kleinpell, and Joseph J. Schlesinger. "Ten Years Later, Alarm Fatigue Is Still a Safety Concern." AACN Advanced Critical Care 34, no. 3 (2023): 189–97. http://dx.doi.org/10.4037/aacnacc2023662.
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Ten years after the publication of a landmark article in AACN Advanced Critical Care, alarm fatigue continues to be an issue that researchers, clinicians, and organizations aim to remediate. Alarm fatigue contributes to missed alarms and medical errors that result in patient death, increased clinical workload and burnout, and interference with patient recovery. Led by the American Association of Critical-Care Nurses, national patient safety organizations continue to prioritize efforts to battle alarm fatigue and have proposed alarm management strategies to mitigate the effects of alarm fatigue. Similarly, clinical efforts now use simulation studies, individualized alarm thresholds, and interdisciplinary teams to optimize alarm use. Finally, engineering research efforts have innovated the standard alarm to convey information more effectively for medical users. By focusing on patient and provider safety, clinical workflow, and alarm technology, efforts to reduce alarm fatigue over the past 10 years have been grounded in an evidence-based and personnel-focused approach.
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Edworthy, Judy, Scott Reid, Siné McDougall, Jonathan Edworthy, and Stephanie Hall. "The Design and Testing of Novel IEC 60601-1-8 Audible Alarms." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (2016): 641–42. http://dx.doi.org/10.1177/1541931213601147.
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IEC 60601-1-8 is a medical alarms standard concerned with equipment safety. Part of its content specifies a set of audible alarms for eight clinical functions: cardiovascular, drug administration, oxygen, artificial perfusion, power down, temperature, ventilation and a general sound, along with a medium- and a low-priority alarm. It has long been acknowledged that the alarms specified are difficult to learn and retain , (Atyeo and Sanderson 2015; Edworthy, Page, et al, 2014; Lacherez, Seah & Sanderson, 2007; Sanderson, Wee & Lacherez 2006; Wee and Sanderson 2008). The alarm sounds require updating. The project reported here is concerned with developing candidate sets of alarms aimed at replacing those currently specified in IEC 60601-1-8. Four prototype sets of alarms were designed for the eight functions specified in the standard. These were as follows: Word rhythms: Each alarm contains a large number of harmonics and the eight alarms vary in pitch pattern, number of pulses and rhythm where those patterns mimic the words of the functions (so for example the ‘Cardiovascular’ alarm possesses 6 pulses and contains stresses on the first and fourth pulses). Auditory icons: These are real-world sounds that are used as metaphors for the functions. So for example the cardiovascular alarm is a heartbeat-like sound, the “Oxygenation” sound is an aerosol sound and so on. Auditory icons with beacon: Same as the Auditory icons but possesses a short beacon at the start of the sound in order to signify that it is an alarm sound. Resilient: These sounds are simple metaphors (such as a rising pitch for temperature) created at a sampling rate of 8kHz, intended for use in equipment with poor acoustic reproduction. A fifth set, IEC, is the set currently specified in the standard and was also tested for comparison. Participants were tested on a single set of alarms. Once they had been told the meanings of the eight alarms, they were presented with each of them ten times in a block-randomised fashion, and were required to name the alarm. Analysis of variance on the correct/incorrect scores considered the effect of sound type (IEC, word rhythm, auditory icons, auditory icons plus beacon, resilient), block (blocks 1 to 10) and sound (the individual alarm sounds) on the number of correct responses. Each of these factors showed significant effects, as well as some interactions. The largest effect by a considerable margin was attributable to sound type. Performance was significantly lower for the IEC condition than any of the other conditions; performance for the word rhythm condition was significantly higher than for the IEC condition but significantly lower than the other three conditions; performance in the resilient condition was significantly higher than for both the IEC and the word rhythm conditions but significantly lower than in the auditory icons conditions; and performance in the auditory icons and the auditory icons plus beacon conditions was significantly higher than in all other conditions, and similar to one another.
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Suso-Ribera, Carlos, Diana Castilla, Irene Zaragozá, et al. "Telemonitoring in Chronic Pain Management Using Smartphone Apps: A Randomized Controlled Trial Comparing Usual Assessment against App-Based Monitoring with and without Clinical Alarms." International Journal of Environmental Research and Public Health 17, no. 18 (2020): 6568. http://dx.doi.org/10.3390/ijerph17186568.
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Background. The usefulness of mHealth in helping to target face-to-face interventions for chronic pain more effectively remains unclear. In the present study, we aim to test whether the Pain Monitor mobile phone application (app) is well accepted by clinicians, and can help improve existent medical treatments for patients with chronic musculoskeletal pain. Regarding this last goal, we compared three treatment conditions, namely usual treatment, usual treatment with an app without alarms and usual treatment with an app with alarms. All treatments lasted one month. The three treatments were compared for all outcomes, i.e., pain severity and interference, fatigue, depressed mood, anxiety and anger. Methods. In this randomized controlled trial, the usual monitoring method (i.e., onsite; n = 44) was compared with daily ecological momentary assessment using the Pain Monitor app—both with (n = 43) and without alarms (n = 45). Alarms were sent to the clinicians in the presence of pre-established undesired clinical events and could be used to make treatment adjustments throughout the one-month study. Results. With the exception of anger, clinically significant changes (CSC; 30% improvement) were greater in the app + alarm condition across outcomes (e.g., 43.6% of patients experienced a CSC in depressed mood in the app + alarm condition, which occurred in less than 29% of patients in the other groups). The clinicians were willing to use the app, especially the version with alarms. Conclusions. The use of apps may have some benefits in individual health care, especially when using alarms to tailor treatments.
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Borowski, M., S. Siebig, C. Wrede, and M. Imhoff. "Reducing False Alarms of Intensive Care Online-Monitoring Systems: An Evaluation of Two Signal Extraction Algorithms." Computational and Mathematical Methods in Medicine 2011 (2011): 1–11. http://dx.doi.org/10.1155/2011/143480.
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Online-monitoring systems in intensive care are affected by a high rate of false threshold alarms. These are caused by irrelevant noise and outliers in the measured time series data. The high false alarm rates can be lowered by separating relevant signals from noise and outliers online, in such a way that signal estimations, instead of raw measurements, are compared to the alarm limits. This paper presents a clinical validation study for two recently developed online signal filters. The filters are based on robust repeated median regression in moving windows of varying width. Validation is done offline using a large annotated reference database. The performance criteria are sensitivity and the proportion of false alarms suppressed by the signal filters.
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Bridi, Adriana Carla, Thiago Quinellato Louro, and Roberto Carlos Lyra da Silva. "Clinical Alarms in intensive care: implications of alarm fatigue for the safety of patients." Revista Latino-Americana de Enfermagem 22, no. 6 (2014): 1034–40. http://dx.doi.org/10.1590/0104-1169.3488.2513.
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OBJECTIVES: to identify the number of electro-medical pieces of equipment in a coronary care unit, characterize their types, and analyze implications for the safety of patients from the perspective of alarm fatigue.METHOD: this quantitative, observational, descriptive, non-participatory study was conducted in a coronary care unit of a cardiology hospital with 170 beds.RESULTS: a total of 426 alarms were recorded in 40 hours of observation: 227 were triggered by multi-parametric monitors and 199 were triggered by other equipment (infusion pumps, dialysis pumps, mechanical ventilators, and intra-aortic balloons); that is an average of 10.6 alarms per hour.CONCLUSION: the results reinforce the importance of properly configuring physiological variables, the volume and parameters of alarms of multi-parametric monitors within the routine of intensive care units. The alarms of equipment intended to protect patients have increased noise within the unit, the level of distraction and interruptions in the workflow, leading to a false sense of security.
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De Rosa, Immacolata, Alessandro Pepino, Gianluca Giaconia, and Mario Guarino. "Bedside communication and management of vital parameters and alarms in care-intensive environments: Simulation model development for the clinical effectiveness analysis of an innovative technology." Global Clinical Engineering Journal 2, no. 3 (2020): 45–56. http://dx.doi.org/10.31354/globalce.v2i3.86.
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Background and Objective. The deliberation n.7301 of 31/12/2001 provides for the inclusion of a call system with acoustic and luminous signalling within the minimum equipment of the recovery ward. However, traditional call systems are inefficient since they are based on the following incorrect assumptions: patients and staff are unmoving, information sources are static and assistance is unidirectional. Taking care of a patient involves different figures who should be dynamic and should be able to exchange information.
 Furthermore, the high number of clinical calls and alarms might be an issue, because on one hand they are essential to fulfil patients’ needs, but on the other hand they could cause stress and additional workload on medical staff. Indeed, they sometimes ignore some calls or waste a lot of time on non-urgent requests. In addition, the identification of an alarm and the prompt intervention seems to be more difficult during travelling.
 An ideal alarm system should have 100% sensitivity and specificity. Nevertheless, the alarms are designed to be extremely sensitive, at the expense of specificity.
 The alarm fatigue, that is the work overload due to an excessive alarms number exposition, is a critical problem in terms of safety in the current clinical practice because it involves desensitization and alarm loss, causing sometimes even the patient's death.
 Material and Methods. Therefore, appropriate approaches to notifications should be evaluated, including the effectiveness of mobile wireless technologies: linking patients, staff, data, services and medical devices simplifies communications and workflows.
 Several issues related to the communication among staff members, between patient and caregiver and to the alarms and vital parameters distribution in care-intensive environments have been analysed, focusing on the clinical effectiveness analysis of an innovative technology to support the Emergency Department of the Azienda Ospedaliera dei Colli activities.
 Afterwards, we have created a simulation model with Simul8, so that a digital twin reproduces direct and indirect activities in two cases: with and without (What If and As Is model) the aid of the technology.
 Results and conclusions. The model provides a set of Key Performance Indicators (number of performing activities, average alarm resolution time, waiting time) on which the compensatory aggregation method is applied to elaborate a single final score in both cases. This score is 52,5 in the As Is Model and 80 in the What If model. So, the clinical effectiveness has been demonstrated.