Alarm Fatigue Research Articles

Degree of Alarm Fatigue and Mental Workload of Hospital Nurses in Intensive Care Units.

This study aimed to determine the degree of alarm fatigue and mental workload of ICU nurses, and to clarify the relationship between these two variables. A cross-sectional, descriptive research design was used. Data were collected from 90 nurses working in four ICUs in Seoul, Republic of Korea, using a questionnaire determining their degree of alarm fatigue and mental workload. Data were collected from 6 March to 26 April 2021 and were analyzed using a t-test, ANOVA, and Pearson's correlation coefficient. The average alarm-fatigue score was 28.59 out of 44. The item with the highest score was "I often hear a certain amount of noise in the ward", with a score of 3.59 out of 4. The average of the mental workload scores was 75.21 out of 100. The highest mental workload item was effort, which scored 78.72 out of 100. No significant correlation was found between alarm fatigue and mental workload. Although nurses were consistently exposed to alarm fatigue, this was not directly related to their mental workloads, perhaps owing to their professional consciousness as they strived to accomplish tasks despite alarm fatigue. However, since alarm fatigue can affect efficiency, investigations to reduce it and develop appropriate guidelines are necessary. This study was not registered.

Staff perspectives on the influence of patient characteristics on alarm management in the intensive care unit: a cross-sectional survey study

BackgroundHigh rates of clinical alarms in the intensive care unit can result in alarm fatigue among staff. Individualization of alarm thresholds is regarded as one measure to reduce non-actionable alarms. The aim of this study was to investigate staff’s perceptions of alarm threshold individualization according to patient characteristics and disease status.MethodsThis is a cross-sectional survey study (February-July 2020). Intensive care nurses and physicians were sampled by convenience. Data was collected using an online questionnaire.ResultsStaff view the individualization of alarm thresholds in the monitoring of vital signs as important. The extent to which alarm thresholds are adapted from the normal range varies depending on the vital sign monitored, the reason for clinical deterioration, and the professional group asked. Vital signs used for hemodynamic monitoring (heart rate and blood pressure) were most subject to alarm individualizations. Staff are ambivalent regarding the integration of novel technological features into alarm management.ConclusionsAll relevant stakeholders, including clinicians, hospital management, and industry, must collaborate to establish a “standard for individualization,” moving away from ad hoc alarm management to an intelligent, data-driven alarm management. Making alarms meaningful and trustworthy again has the potential to mitigate alarm fatigue – a major cause of stress in clinical staff and considerable hazard to patient safety.Trial registrationThe study was registered at ClinicalTrials.gov (NCT03514173) on 02/05/2018.

Alarm rationalization in engineering projects: analyzing cost-saving measures and efficiency gains

Alarm rationalization is a critical process in engineering projects, focusing on optimizing alarm management systems to enhance operational efficiency, reduce costs, and improve safety. This paper explores how alarm rationalization, when implemented effectively, mitigates alarm fatigue, reduces unnecessary alerts, and ensures that operators are only notified of critical issues. By analyzing cost-saving measures and efficiency gains, the study highlights how rationalization techniques can streamline decision-making and improve system reliability across various industries, such as oil and gas, manufacturing, and chemical processing. The rationalization process involves reviewing existing alarm systems, identifying redundant or non-critical alarms, and reclassifying alarms based on priority and operational impact. By refining alarm settings, engineers can decrease operator workload and minimize downtime, contributing to significant cost savings. For example, reducing nuisance alarms not only improves response times but also extends the lifespan of equipment by preventing unnecessary shutdowns. From a global perspective, the adoption of alarm rationalization varies by industry and region, with some sectors benefiting from advanced automation technologies and standardized regulatory guidelines. The implementation of intelligent alarm systems, combined with data analytics and machine learning, further enhances the ability to predict and prevent failures before they escalate into major operational disruptions. This paper also examines case studies of successful alarm rationalization projects, demonstrating tangible efficiency gains such as reduced maintenance costs, improved safety, and optimized production processes. Additionally, the discussion extends to the challenges and best practices in alarm rationalization, such as securing stakeholder buy-in, aligning rationalization efforts with organizational goals, and ensuring compliance with international safety standards. In conclusion, alarm rationalization offers engineering projects an effective pathway to achieve cost efficiency and operational excellence. However, the success of these initiatives depends on robust planning, continuous monitoring, and the integration of advanced technologies.

914-P: Veteran Experiences with Hybrid Closed-Loop (HCL) Insulin Delivery Systems in Type 1 Diabetes (T1D)

While HCL systems are increasingly recommended, data regarding veteran experiences are limited. We performed semi-structured interviews to characterize veteran experiences with HCL systems at the VA Ann Arbor Healthcare System. We used qualitative description methodology to elicit participant experiences with HCL and identify factors that could improve practice. Semi-structured interviews were conducted with veterans with T1D using an HCL device for at least 6 months. The interview guide was developed based on a modified Theory of Planned Behavior, examining the domains of attitudes/knowledge, network support, and perceived behavioral control. Inductive thematic analysis of interview transcripts was performed to understand factors that contribute to the overall HCL experience. Nine HCL users (mean age 68 years, mean A1c 7.4%, mean diabetes duration 30 years, 78% Medtronic HCL users, 22% Tandem HCL users) were interviewed. Participants reported that HCL systems ease self-management burden, increase lifestyle flexibility, and enhance the perception of safety. However, challenges in alarm fatigue exist. Participants were satisfied with their outpatient multidisciplinary network support but noted significant gaps in inpatient support for HCL use. Lastly, participants reported an improved sense of confidence in diabetes management using HCL systems. Key facilitators for successful HCL use were a desire to stay healthy for their spouse and to avoid long-term diabetes complications. Our findings confirm that HCL systems improve self-management and enhance safety in veterans as well, similar with prior reports in non-veterans with T1D. Veterans felt supported in using these systems as outpatients though challenges remain for HCL systems in the inpatient setting. Future studies should focus on improving network support for inpatient use of these devices. Disclosure S.Azzawi: None. M.Dejonckheere: None. H.Thompson: None. K.Hurren: None. V.A.Leone: None. R.Busui: Board Member; American Diabetes Association, Consultant; Averitas Pharma, Inc., Lexicon Pharmaceuticals, Inc., Nevro Corp., Novo Nordisk, Roche Diagnostics, Procter & Gamble, Research Support; Novo Nordisk, Medtronic, National Institutes of Health. G.Piatt: None. J.M.Lee: Advisory Panel; GoodRx, Consultant; Tandem Diabetes Care, Inc. K.R.Mizokami-stout: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (P30DK020572-43S1)

Development and clinical impact assessment of a machine-learning model for early prediction of late-onset sepsis

Background and aimPreterm infants are prone to neonatal infections such as late-onset sepsis (LOS). The consequences of LOS can be severe and potentially life-threatening. Unfortunately, LOS often presents with unspecific symptoms, and early screening laboratory tests have limited diagnostic value and are often late. This study aimed to build a predictive algorithm to aid doctors in the early detection of LOS in very preterm infants. MethodsIn a retrospective cohort study, all consecutively admitted preterm infants (GA ≤ 32 weeks) from 2008 until 2019 were included. They were classified as LOS or control according to blood culture results, currently the gold standard. To generate features, routine and continuously measured oxygen saturation and heart rate data with a minute-by-minute sampling rate were extracted from electronic medical records. Care was taken not to include variables indicative of existing LOS suspicion. The timing of a positive blood culture served as a proxy for LOS-onset. An equivalent timestamp was generated in gestational-age-matched control patients without a positive blood culture. Three machine learning (ML) techniques (generalized additive models, logistic regression, and XGBoost) were used to build a classification algorithm. To simulate the performance of the algorithm in clinical practice, a simulation using multiple alarm thresholds was performed on hourly predictions for the total hospitalization period. Results292 infants with LOS were matched to 1497 controls. The median gestational age before matching was 28.1 and 30.3 weeks, respectively. Evaluation of the overall discriminative power of the LR algorithm yielded an AUC of 0.73 (p < 0.05) at the moment of clinical suspicion (t = 0). In the longitudinal simulation, our algorithm detects LOS in at least 47% of the patients before clinical suspicion without exceeding the alarm fatigue threshold of 3 alarms per day. Furthermore, medical experts evaluated the algorithm as clinically relevant regarding the feature contributions in the model explanations. ConclusionsAn ML algorithm was trained for the early detection of LOS. Performance was evaluated on both prediction horizons and in a clinical impact simulation. To the best of our knowledge, our assessment of clinical impact with a retrospective simulation on longitudinal data is the most extensive in the literature on LOS prediction to date. The clinically relevant algorithm, based on routinely collected data, can potentially accelerate clinical decisions in the early detection of LOS, even with limited inputs.

Determining the Psychometric Properties of the Turkish Version of the Nurses’ Alarm Fatigue Questionnaire

Objective: This study was conducted to examine the psychometric properties of the Nurses’ Alarm Fatigue Questionnaire. Materials and Methods: In this methodological study, the sample consisted of 142 nurses working in neonatal and pediatric intensive care. In order to test the psychometric properties of the scale, language equivalence, content and construct validity were used for validity analysis. The data were evaluated using descriptive and confirmative factor analyses, Cronbach's alpha, split-half, and item-total score correlation. Results: The total explained variance of the Turkish version of the Nurses' Alarm Fatigue Questionnaire consisting of a single sub-dimension and nine items was determined as 41%. The total factor loading was &amp;gt;0.30. In the confirmatory factor analysis, all the goodness of fit indexes were &amp;gt;0.90, and the root mean square error of approximation (RMSEA) was &amp;lt;0.08. The correlation between the two halves was 0.71, and the Guttman split-half and Spearman-Brown coefficients were 0.83. The Cronbach's alpha coefficient for the scale was found to be 0.80. Conclusion: The study’s findings suggest that the scale is a valid and reliable tool in determining the alarm fatigue of nurses working in newborn and pediatric intensive care units in Türkiye.

Retracted: The Current Situation and Influencing Factors of the Alarm Fatigue of Nurses' Medical Equipment in the Intensive Care Unit Based on Intelligent Medical Care.

[This retracts the article DOI: 10.1155/2021/9994303.].

Multisensory alarm to benefit alarm identification and decrease workload: a feasibility study.

The poor design of conventional auditory medical alarms has contributed to alarm desensitization, and eventually, alarm fatigue in medical personnel. This study tested a novel multisensory alarm system which aims to help medical personnel better interpret and respond to alarm annunciation during periods of high cognitive load such as those found within intensive care units. We tested a multisensory alarm that combined auditory and vibrotactile cues to convey alarm type, alarm priority, and patient identity. Testing was done in three phases: control (conventional auditory), Half (limited multisensory alarm), and Full (complete multisensory alarm). Participants (N = 19, undergraduates) identified alarm type, priority, and patient identity (patient 1 or 2) using conventional and multisensory alarms, while simultaneously completing a cognitively demanding task. Performance was based on reaction time (RT) and identification accuracy of alarm type and priority. Participants also reported their perceived workload. RT was significantly faster for the Control phase (p < 0.05). Participant performance in identifying alarm type, priority, and patient did not differ significantly between the three phase conditions (p = 0.87, 0.37, and 0.14 respectively). The Half multisensory phase produced the lowest mental demand, temporal demand, and overall perceived workload score. These data suggest that implementation of a multisensory alarm with alarm and patient information may decrease perceived workload without significant changes in alarm identification performance. Additionally, a ceiling effect may exist for multisensory stimuli, with only part of an alarm benefitting from multisensory integration.

Refining Clinical Phenotypes to Improve Clinical Decision Support and Reduce Alert Fatigue: A Feasibility Study.

Chronic kidney disease (CKD) is common and associated with adverse clinical outcomes. Most care for early CKD is provided in primary care, including hypertension (HTN) management. Computerized clinical decision support (CDS) can improve the quality of care for CKD but can also cause alert fatigue for primary care physicians (PCPs). Computable phenotypes (CPs) are algorithms to identify disease populations using, for example, specific laboratory data criteria. Our objective was to determine the feasibility of implementation of CDS alerts by developing CPs and estimating potential alert burden. We utilized clinical guidelines to develop a set of five CPs for patients with stage 3 to 4 CKD, uncontrolled HTN, and indications for initiation or titration of guideline-recommended antihypertensive agents. We then conducted an iterative data analytic process consisting of database queries, data validation, and subject matter expert discussion, to make iterative changes to the CPs. We estimated the potential alert burden to make final decisions about the scope of the CDS alerts. Specifically, the number of times that each alert could fire was limited to once per patient. In our primary care network, there were 239,339 encounters for 105,992 primary care patients between April 1, 2018 and April 1, 2019. Of these patients, 9,081 (8.6%) had stage 3 and 4 CKD. Almost half of the CKD patients, 4,191 patients, also had uncontrolled HTN. The majority of CKD patients were female, elderly, white, and English-speaking. We estimated that 5,369 alerts would fire if alerts were triggered multiple times per patient, with a mean number of alerts shown to each PCP ranging from 0.07-to 0.17 alerts per week. Development of CPs and estimation of alert burden allows researchers to iteratively fine-tune CDS prior to implementation. This method of assessment can help organizations balance the tradeoff between standardization of care and alert fatigue.

Alert Fatigue and Alert Override Significance in Relation to CDSS Success

Alert Fatigue and Alert Override Significance in Relation to CDSS Success

Determining Factors of Alarm Fatigue among Nurses in Intensive Care Units-A Polish Pilot Study.

With the development of medical technology, clinical alarms from various medical devices, which are rapidly increasing, are becoming a new problem in intensive care units. The aim of this study was to evaluate alarm fatigue in Polish nurses employed in Intensive Care Units and identify the factors associated with alarm fatigue. A cross-sectional study. The study used the nurses' alarm fatigue questionnaire by Torabizadeh. The study covered 400 Intensive Care Unit nurses. The data were collected from February to June 2021. The overall mean score of alarm fatigue was 25.8 ± 5.8. Participation in training programs related to the use of monitoring devices available in the ward, both regularly (ß = -0.21) and once (ß = -0.17), negatively correlated with nurses' alarm fatigue. On the other hand, alarm fatigue was positively associated with 12 h shifts [vs. 8 h shifts and 24 h shifts] (ß = 0.11) and employment in Intensive Cardiac Surveillance Units-including Cardiac Surgery [vs. other Intensive Care Units] (ß = 0.10). Monitoring device alarms constitute a significant burden on Polish Intensive Care Unit nurses, in particular those who do not take part in training on the operation of monitoring devices available in their ward. It is necessary to improve Intensive Care Unit personnel's awareness of the consequences of overburdening and alarm fatigue, as well as to identify fatigue-related factors.

The relationship between alarm fatigue and burnout among critical care nurses: A cross-sectional study.

Alarm fatigue has significant negative impacts on nurses and patient safety. However, the relationship between alarm fatigue and burnout is still unclear. This study aimed to explore the relationship between alarm fatigue and burnout among critical care nurses. A descriptive-analytical cross-sectional study design was used. Data were collected from five hospitals in mainland China between January 2022 and March 2022. A general information questionnaire, the Chinese version of the Intensive Care Unit Nurse Alarm Fatigue Questionnaire, and the Chinese version of the Maslach Burnout Inventory were used. A total of 236 critical care nurses were enrolled in this study. The mean score of alarm fatigue among critical care nurses was 21.11 ± 6.83. The results showed that critical care nurses experienced moderate alarm fatigue levels, and most nurses had moderate to high levels of burnout. The multiple linear regression analyses showed that alarm fatigue was independently associated with emotional exhaustion, depersonalization dimensions, and reduced personal accomplishment dimension. Alarm fatigue was associated with burnout among critical care nurses. Reducing critical care nurses' alarm fatigue may help to alleviate burnout. Managers should provide comprehensive training for nurses and promote the application of artificial intelligence technology in alarm management to reduce alarm fatigue and improve burnout among critical care nurses.

Alarm Fatigue in Nursing Students Undertaking Clinical Training in Intensive Care Units: A Multicenter Study.

The frequency of alarms from monitors and other electro-medical devices is of great utility but can increase the professional's workload and expose nurses in the intensive care unit to Alarm Fatigue. A recent study suggested that students in training can also experience the problem during their first clinical experiences in intensive care. Unfortunately, no data are available about the Italian panorama. To explore Alarm Fatigue among Bachelor of Science in Nursing students at the end of their internship experience in intensive care settings. Multicenter cross-sectional design. A convenience sample of nurses from 3 Italian university hospitals was recruited. The students completed the revised version of the "Alarm Fatigue questionnaire-ita" at the end of the clinical internship in intensive care settings. 130 nursing students were enrolled (response rate 59.36%). The overall level of Alarm Fatigue was Me= 24.5 IQR [17.5, 30.5]. In addition, 9.23% of the sample reported errors or near misses related to Alarm Fatigue during the internship experience. The alarm fatigue level was higher in students who committed "errors/almost errors" (p=0.038) and in "student workers" (p=0.005). The extent of alarm fatigue experienced by nursing students requires developing a preventive strategy.

Implementing a Unit-Based Alarm Management Bundle for Critical Care Nurses

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. 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. 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. 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. 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.

Prevalence of alarm fatigue and its relevant factors in critical care nurses: A cross-sectional study

Prevalence of alarm fatigue and its relevant factors in critical care nurses: A cross-sectional study

Informing Healthcare Alarm Design and Use: A Human Factors Cross-Industry Perspective

Background: Alarms are signals intended to capture and direct human attention to a potential issue that may require monitoring, assessment, or intervention and play a critical safety role in high-risk industries. Healthcare relies heavily on auditory and visual alarms. While there are some guidelines to inform alarm design and use, alarm fatigue and other alarm issues are challenges in the healthcare setting. Automotive, aviation, and nuclear industries have used the science of human factors to develop alarm design and use guidelines. These guidelines may provide important insights for advancing patient safety in healthcare. Methods: We identified documents containing alarm design and use guidelines from the automotive, aviation, and nuclear industries that have been endorsed by oversight agencies. These guidelines were reviewed by human factors and clinical experts to identify those most relevant to healthcare, qualitatively analyze the relevant guidelines to identify meaningful topics, synthesize the guidelines under each topic to identify key commonalities and differences, and describe how the guidelines might be considered by healthcare stakeholders to improve alarm design and use. Results: A total of 356 guidelines were extracted from industry documents (2012–present) and 327 (91.9%) were deemed relevant to healthcare. A qualitative analysis of relevant guidelines resulted in nine distinct topics: Alarm Reduction, Appropriateness, Context-Dependence, Design Characteristics, Mental Model, Prioritization, Specificity, Urgency, and User Control. There were several commonalities, as well as some differences, across industry guidelines. The guidelines under each topic were found to inform the auditory or visual modality, or both. Certain guidelines have clear considerations for healthcare stakeholders, especially technology developers and healthcare facilities. Conclusion: Numerous guidelines from other high-risk industries can inform alarm design and use in healthcare. Healthcare facilities can use the information presented as a framework for working with their technology developers to appropriately design and modify alarming technologies and can evaluate their clinical environments to see how alarming technologies might be improved.

Evaluation of alarm fatigue in nurses working in intensive care units and alarm fatigue

Aims: This study aimed to investigate alarm fatigue, which has a negative impact on nurses working in intensive care units. Methods: A questionnaire of 20 questions consisting of the alarm fatigue scale in nursing and sociodemographic questions prepared on Google Forms was sent to the nurses working in intensive care units as a social messaging platform and e-mail between 1 January-1 February 2022. Results: 219 nurses provided feedback. Nurses working in adult intensive care units participated with 70.6%. It was observed that alarm fatigue scores decreased as the duration of working in the intensive care unit and the working time in the nurse increased. Conclusion: As the age and professional experience of the nurses increase, the fatigue caused by the alarms decreases. Since this situation may pose a danger to the safety of patients who young nurses follow in the first years of the profession, it would be appropriate to develop nurses' methods of coping with alarms.

Clinical Alarms in a Gynaecological Surgical Unit: A Retrospective Data Analysis

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.

The impact of an intervention to improve intrapartum maternal vital sign monitoring and reduce alarm fatigue

The infrastructure of many labor and delivery units in the United States may dispose clinicians to overuse continuous and automated maternal physiological monitors. Overmonitoring low-risk patients can negatively affect patient care, primarily through generating alarm fatigue. Given the national attention to reducing alarm fatigue across healthcare settings and the concern for vital sign monitoring overuse on our labor and delivery unit, this quality improvement study aimed to evaluate vital sign monitoring patterns and alarm rates, and nursing experiences of alarm fatigue, before and after implementing a vital sign monitoring guideline for low-risk obstetrical patients. This was a quality improvement study conducted on the labor and delivery unit of an urban, academic, tertiary hospital. The lack of guidance for maternal vital sign assessment in low-risk patients was identified as a potential safety challenge. A vital sign guideline was developed with multidisciplinary input, followed by a pre-post-implementation study evaluating vital sign volume and alarm rates. Total vital signs and alarm rates for all patients delivered during designated calendar days were assessed as a rate of vital signs per patient and compared across baseline, peri-intervention, and follow-up periods. Data were examined in p-type statistical process control charts and with time-series analysis. Patient characteristics and severe maternal morbidity, as a balancing metric, were compared across periods. Nursing perceptions of vital sign monitoring and experience of alarm fatigue were assessed via survey before and after implementation of the guideline. A total of 35 individual 24-hour periods were evaluated with regard to vital sign and alarm volume. There was a decrease in vital signs per patient from a mean of 208.34 to 135.46 (incidence rate ratio, 0.65) and in alarms per patient from a mean of 14.31 to 10.51 (incidence rate ratio, 0.73) after implementation, with no difference in severe maternal morbidity. There were 85 total respondents to the nursing surveys, and comparison of modified task-load index scores before and after implementation demonstrated overall lower scores in the postperiod, although these were not statistically significant. Introducing a maternal vital sign guideline for low-risk patients on the labor and delivery unit decreased vital signs measured as well as alarms, which may ultimately reduce alarm fatigue. This strategy should be considered on labor and delivery units widely to improve patient safety and optimize outcomes.

A grounded theory study of alarm fatigue among nurses in intensive care units

ObjectivesThe aim of this study was to explore the process of how nurses experienced and dealt with alarm fatigue in intensive care units based on Iranian nurses' perceptions and experiences. BackgroundAlarm fatigue is the overstimulation of senses due to the constant ringing of alarms in intensive care units. It is associated with nurses’ desensitization to critical alarms that can directly influence patient safety and quality of care. MethodsA qualitative exploratory study using the grounded theory approach by Strauss and Corbin was carried out. Participants were 20 nurses working in intensive care units. The sampling process was started purposively and continued theoretically. Data were collected using semi-structured, in-depth, and individual interviews and continued to data saturation. The constant comparative analysis approach was used consisting of the following steps: open coding, developing concepts, analysing the context, entering the process into data analysis, integrating categories. FindingsThe participants' main concern in the exposure to alarm fatigue was ‘threat to personal balance’. The core category in this research was ‘trying to create a holistic balance’, which reflected a set of strategies that the nurses consistently and continuously used to deal with alarm fatigue and consisted of four main categories as follows: ‘smart care’, ‘deliberate balancing’, ‘conditional prioritisation’, and ‘negligent performance’. Threat to personal balance was strengthened by ‘inappropriate circuit of individual roles’, ‘distortion of the organisational structure’, and ‘insecurity of the infrastructure’. The consequences of this process was harm to the patient, burnout among nurse, and damage to the healthcare organisation. ConclusionsThe research findings have practical implications for healthcare management, policymaking, nursing education, research, and clinical practice. Mitigating staff shortages, improving staff competencies, enhancing nurses’ authority for responding to alarms, modifying care routines, improving the physical environment, and removing problems related to alarm equipment can prevent alarm fatigue and its unappropriated consequences.