Mechanical Ventilation Alarms and Alarm Fatigue

Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients

The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for significant strides in patient diagnosis, treatment, and prognostication in neurocritical care. These technologies offer the potential to unravel complex patterns within vast datasets ranging from vast clinical data and EEG (electroencephalogram) readings to advanced cerebral imaging facilitating a more nuanced understanding of patient conditions. Despite their promise, the implementation of AI and ML faces substantial hurdles. Historical biases within training data, the challenge of interpreting multifaceted data streams, and the "black box" nature of ML algorithms present barriers to widespread clinical adoption. Moreover, ethical considerations around data privacy and the need for transparent, explainable models remain paramount to ensure trust and efficacy in clinical decision-making.This article reflects on the emergence of AI and ML as integral tools in neurocritical care, discussing their roles from the perspective of both their scientific promise and the associated challenges. We underscore the importance of extensive validation in diverse clinical settings to ensure the generalizability of ML models, particularly considering their potential to inform critical medical decisions such as withdrawal of life-sustaining therapies. Advancement in computational capabilities is essential for implementing ML in clinical settings, allowing for real-time analysis and decision support at the point of care. As AI and ML are poised to become commonplace in clinical practice, it is incumbent upon health care professionals to understand and oversee these technologies, ensuring they adhere to the highest safety standards and contribute to the realization of personalized medicine. This engagement will be pivotal in integrating AI and ML into patient care, optimizing outcomes in neurocritical care through informed and data-driven decision-making.

Nurses' alarm fatigue, influencing factors, and its relationship with burnout in the critical care units: A cross-sectional study

BACKGROUND

Excessive number of alarms and false and nonactionable alarms may lead to alarm fatigue. Alarm fatigue could easily contribute to burnout. Burnout may reduce nurses' sensitivity to alarms, thus affecting patients' safety due to insufficient response to the alarms. However, no study has examined nurses' alarm fatigue in Ghana.

OBJECTIVES

The objective of this study was to investigate the level of alarm fatigue and its associated factors, as well as determine its relationship with burnout among nurses working in the critical care units of hospitals in Ghana.

METHODS

The cross-sectional study was conducted in critical care units of five hospitals in Ghana from November 2021 to January 2022. A total of 364 nurses were recruited and completed the questionnaire. Alarm fatigue was assessed by the alarm fatigue questionnaire, which was originally developed in Chinese and was translated into English using a standard protocol. Burnout was assessed using the Maslach Burnout Inventory.

RESULTS

The overall alarm fatigue score was 76.43 ± 27.80 out of 124. Longer years working at the critical care unit (B = -2.50, 95% confidence interval [CI]: -4.62, -0.37) and having policies related to alarm management (B = -10.77, 95% CI: -3.50, -18.04) were associated with a decreased risk of alarm fatigue, while working in neonatal intensive care unit (B = 16.35, 95% CI: 2.48, 30.21) and postanesthesia care unit (B = 15.16; 95% CI: 0.32, 30.01), and having anxiety and stress (B = 8.15, 95% CI: 1.30, 15.00) were associated with an increased risk of alarm fatigue. In addition, alarm fatigue was positively associated with emotional exhaustion (r = 0.52, P < 0.001) and depersonalisation (r = 0.43, P < 0.001) but not personal accomplishment (r = -0.09, P = 0.100).

CONCLUSION

Critical care nurses in Ghana experienced higher levels of alarm fatigue, which is affected by multiple factors. There is a significant link between nurses' alarm fatigue and burnout. Our findings provide important guidance for future intervention programs to improve critical care nurses' alarm fatigue by introducing policies on alarm management and improving nurses' psychological health, with a special focus on nurses with shorter working years and working in neonatal intensive care unit and postanesthesia care unit.

Validity and Reliability of a Short Form of the Questionnaire for the Reflective Practice of Nursing Involving Invasive Mechanical Ventilation: A Cross-Sectional Study

The number of patients on ventilators is rapidly increasing owing to the coronavirus pandemic. The previously developed Questionnaire for the Reflective Practice of Nursing Involving Invasive Mechanical Ventilation (Q-RPN-IMV) for the care of patients on ventilators includes nurses' thought processes as items. This study aims to develop a short form of the Q-RPN-IMV for immediate use in practice and to test its reliability and validity. A convenience sample of 629 participants was used to explore the factor structure using factor analysis. The test-retest reliability was assessed using the intraclass correlation coefficient (ICC). The study was a cross-sectional design instrument development study and was reported according to GRRAS guidelines. Q-RPN-IMV short form was divided into ventilator management and patient management. The ventilator management comprised 31 items organized into six factors. Cronbach's alpha ranged from 0.82 to 0.91, and the ICC ranged from 0.82 to 0.89. The patient management comprised 27 items organized into five factors. Cronbach's alpha ranged from 0.75 to 0.97, and ICC ranged from 0.75 to 0.97. The Q-RPN-IMV short form is a reliable and validated instrument for assessing care for patients on ventilators. This study was not registered.

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

INTRODUCTION

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.

METHODS

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.

RESULTS

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).

CONCLUSION

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.

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.

The basics of mechanical ventilation in adults

ABSTRACT

Mechanical ventilation (MV) is a complex, labor-intensive, often life-saving process that requires a knowledgeable team to manage. Nurses play a critical role in caring for adults receiving MV. Therefore, they need to know about all aspects of providing ventilatory support. This article reviews the basics of MV, describes how mechanical ventilators operate, and discusses mechanical ventilator management and the practical aspects of caring for adults requiring MV.

Alarm fatigue among nurses working in intensive care and other inpatient clinics

BACKGROUND

Alarm fatigue is an important technological hazard that adversely affects patient safety and the healthcare team. Nurses can be exposed to an excessive amount of alarms during their work which may lead to alarm fatigue.

OBJECTIVE

To determine the experiences of alarm fatigue among nurses working in intensive care units and other inpatient clinics.

METHODS

This descriptive study was conducted in university hospitals in five cities in Turkey between August and December 2019. A total of 592 nurses participated in this study. The data was collected using questionnaires and the Visual Analog Scale (0 to 10 points) was used to determine the level of alarm fatigue.

RESULTS

More than half of the nurses experienced problems, especially false alarms, caused by devices. Alarm fatigue decreased with increasing age and working years. Nurses reported appropriate actions in solving problems, but also had practices that may increase the risk of error, such as turning off or muting alarms or turning off equipment.

CONCLUSION

Alarm fatigue is mostly caused by false alarms. It can lead to physical fatigue, increased workload and decreased concentration, resulting in an increased possibility of error. Management of alarm fatigue is necessary in preventing a compromise in patients' safety and improving quality of care.

Determinants of Medical Equipment Alarm Fatigue in Practicing Nurses: A Systematic Review

Objective

This study aimed to systematically evaluate the level of medical equipment alarm fatigue and its influencing factors among clinical nurses.

Methods

PubMed, Embase, CNKI, and Wanfang databases were systematically searched to identify articles on alarm fatigue of clinical nurses published before September 25, 2022. According to the evaluation criteria of prevalence studies recommended by JBI Evidence-Based Health Care Center, the quality of the literature meeting the inclusion criteria was evaluated, and Stata MP17 software was used for meta-analysis.

Results

A total of 14 cross-sectional studies were included, with a total sample of 2,848 nurses. The results showed that the alarm fatigue score of clinical nurses was 21.76 (95% CI [20.27, 23.25]). Subgroup analysis showed that the nurses who worked night shift and had lower professional title had higher alarm fatigue.

Conclusion

The alarm fatigue of clinical nurses was at a moderate level. To reduce the alarm fatigue level of clinical nurses, nursing managers should strengthen the alarm safety awareness of nurses, rationally arrange nurse manpower, carry out training to actively improve the alarm management ability of nurses, and optimize the alarm level and frequency of alarm equipment.

Implementation of a Comprehensive Testing Protocol for a Rapidly Manufactured Mechanical Ventilator

Introduction

The COVID-19 pandemic highlighted that surges in critical care demand can overwhelm existing healthcare infrastructures, most evident in the acute shortage of mechanical ventilators across the globe. Despite efforts to encourage urgent authorization of newly developed emergency ventilators, the currently available testing protocols are not internationally accepted, standardized and none address testing in clinical settings. The aim of this study was to compile and perform a comprehensive clinical testing protocol for a newly developed emergency ventilator.

Methods

Using previously available guidance, we compiled a sequential testing protocol with a: 1. preclinical, 2. safety testing, 3. clinician usability test and 4. clinical stage involving respiratory failure patients. The protocol was then tested on the Luca ventilator, a mechanical ventilator capable of sophisticated ventilator settings rapidly developed specifically in response to the COVID-19 pandemic.

Results

During the pre-clinical/safety stages, the ventilator produced pressure and volume changes deemed acceptable by the Rapidly Manufactured Ventilator System guideline. Furthermore, our protocol allowed the identification of a number of issues that were easily resolved with minor software adjustments. Usability was excellent (overall System Usability Scale score = 90.5). Clinical testing revealed that a sampling frame of 15 critically ill patients was sufficiently powered to detect any significant, clinically relevant differences between the Luca ventilator and a standard ICU ventilator.

Conclusions

The ventilator was accurate, reliable, safe, and user-friendly. The implementation of a comprehensive, standardized pre-clinical/clinical testing protocol is feasible, potentially enabling the safe and timely emergency authorization of rapidly developed mechanical ventilators crucial in pandemic situations.

Improving Home Ventilator Alarm Use Among Children Requiring Chronic Mechanical Ventilation

BACKGROUND AND OBJECTIVES

Children requiring long-term mechanical ventilation are at high risk of mortality. Setting ventilator alarms may improve safety, but best practices for setting ventilator alarms have not been established. Our objective was to increase the mean proportion of critical ventilator alarms set for those children requiring chronic mechanical ventilation followed in our pulmonary clinic from 63% to >90%.

METHODS

Using the Institute for Healthcare Improvement Model for Improvement, we developed, tested, and implemented a series of interventions using Plan-Do-Study-Act cycles. We followed our progress using statistical process control methods. Our primary interventions were: (1) standardization of the clinic workflow, (2) development of an algorithm to guide physicians in selecting and setting ventilator alarms, (3) updating that algorithm based on review of failures and inpatient testing, and (4) enhancing staff engagement to change the culture surrounding ventilator alarms.

RESULTS

We collected baseline data from May 1 to July 13, 2017 on 130 consecutive patients seen in the pulmonary medicine clinic. We found that 63% of critical ventilator alarms were set. Observation of the process, standardization of workflow, and adaptation of an alarm algorithm led to an increase to 85.7% of critical alarms set. Through revising our algorithm to include an apnea alarm, and maximizing provider engagement, more than 95% of critical ventilator alarms were set, exceeding our goal. We sustained this improvement through January 2021.

CONCLUSIONS

Our stepwise approach, including process standardization, staff engagement, and integration of an alarm algorithm, improved the use of ventilator alarms in chronically ventilated pediatric patients.

Effects of the Discharge Education Program on Family Caregivers Caring for Patients on Mechanical Home Ventilation in Korea: A Pilot Test

Patients on home ventilators rely on mechanical ventilation until their death; hence, family caregivers should perform additional caregiving, including tracheostomy, equipment management, and positive pressure ventilation by ambu-bag in emergencies. Therefore, a systematic discharge education program and evaluation of actual caregiver performance are necessary for safe home management. The program consists of suction and tracheostomy management, home ventilator management, emergency management, fundamental caregiving, and video material. To test clinical validity, family caregivers of patients about to be discharged to their homes from S hospital in Seoul, Korea, were selected by convenience sampling with a non-equivalent control group design. Of 18 participants, one refused, one died, and two became unstable after their agreement; therefore, 14 participants were finally included. To compare caregiving performance scores between the groups, we ran repeated measures ANOVA. Intergroup and period interaction of suction ( F = 6.08, p = .001) and tracheostomy management ( F = 3.00, p = .038) crucial for airway management, showed significant statistical differences. In short, the intervention group showed a faster increase in suction and tracheostomy management than the control group. Home ventilator management ( F = 22.53, p < .001), emergency management ( F = 12.01, p < .001), and fundamental caregiving ( F = 7.88, p < .001) showed significant differences within the group regarding the period. According to the results of the clinical validity test, the discharge education program increased the family caregiver’s suction and tracheostomy management performance scores. Further research is needed to demonstrate long-term effects of the program with a larger sample.

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

After rapid development and reform, the health level and medical diagnosis and treatment capabilities of Chinese residents have been significantly improved, and high-quality medical resources have significantly improved the life safety and health of the masses. As the most concentrated area of medical equipment in the hospital, the intensive care unit produces the most alarms during the operation of the equipment. The intensive care unit nurses are responsible for heavier nursing work, and the problem of alarming in other departments is more prominent. Therefore, this paper presents an analysis and research on the current situation and influencing factors of the alarm fatigue of nurse medical equipment in the intensive care unit based on intelligent medicine. This article uses a variety of related methods such as literature data method and questionnaire survey method to deeply study the theoretical knowledge of intelligent medical treatment, medical equipment alarm fatigue device, and so on. The logistic regression analysis method is introduced to classify its influencing factors, and the analysis experiment on the influencing factors of the medical equipment alarm fatigue of nurses in the intensive care unit is designed. The nurses' cognition of clinical alarms and the analysis of clinical alarm fatigue questionnaire data are studied. The alarm fatigue of nurses in the intensive care unit is at a severe level, which needs to be taken seriously in the intensive care unit. Unmarried, high-level positions, long working years, high professional titles, and high education are negatively correlated with alarm fatigue (P < 0.05), and those without an alarm habit are positively correlated with alarm fatigue (P < 0.05), and the number of night shifts per month is related to alarm fatigue. There is no correlation between them (P > 0.05).

An evaluation of manual tidal volume and respiratory rate delivery during simulated resuscitation

INTRODUCTION

Excessive minute ventilation during cardiac arrest may cause lung injury and decrease the effectiveness of cardiopulmonary resuscitation (CPR). However, little is known about how clinicians deliver tidal volumes and respiratory rates during CPR.

METHODS

In this cross-sectional study, licensed practitioners attending an American Heart Association (AHA) Advanced Cardiac Life Support (ACLS) course performed CPR and manual ventilation on a high-fidelity simulator during the megacode portion of the course. Delivered tidal volumes and respiratory rates were measured on a monitor. During the first scenario, results were not displayed to participants, but were displayed during the second scenario.

RESULTS

Fifty-two clinicians participated in this study. Average height was 169 (157,178) cm. Pre-monitor display tidal volumes delivered were larger in male participants compared to female participants (684.6 ± 134.4 vs 586.7 ± 167.6 ml, P = 0.05). Those using medium-sized gloves delivered smaller tidal volumes than those using small or large gloves. Twenty-two (42.3%) delivered tidal volume in the range of 5-8 ml/kg of predicted body weight for the simulation manikin, and 35 (67.3%) delivered tidal volumes with >20% variability among breaths. All participants met the target respiratory rate around 10 breaths/min.

CONCLUSION

Tidal volume delivery varied greatly during manual ventilation and fewer than half participants delivered tidal volume at 5-8 ml/kg to the manikin. Sex and glove size appeared to impact tidal volume delivery when the participants were unaware of what they were delivering. Participants were able to meet the target respiratory rate around 10 without audio or visual feedback.