Search

Background: In response to the high patient admission rates during the COVID-19 pandemic, provisional intensive care units (ICUs) were set up, equipped with temporary monitoring and alarm systems. We sought to find out whether the provisional ICU setting led to a higher alarm burden and more staff with alarm fatigue., Objective: We aimed to compare alarm situations between provisional COVID-19 ICUs and non-COVID-19 ICUs during the second COVID-19 wave in Berlin, Germany. The study focused on measuring alarms per bed per day, identifying medical devices with higher alarm frequencies in COVID-19 settings, evaluating the median duration of alarms in both types of ICUs, and assessing the level of alarm fatigue experienced by health care staff., Methods: Our approach involved a comparative analysis of alarm data from 2 provisional COVID-19 ICUs and 2 standard non-COVID-19 ICUs. Through interviews with medical experts, we formulated hypotheses about potential differences in alarm load, alarm duration, alarm types, and staff alarm fatigue between the 2 ICU types. We analyzed alarm log data from the patient monitoring systems of all 4 ICUs to inferentially assess the differences. In addition, we assessed staff alarm fatigue with a questionnaire, aiming to comprehensively understand the impact of the alarm situation on health care personnel., Results: COVID-19 ICUs had significantly more alarms per bed per day than non-COVID-19 ICUs (P<.001), and the majority of the staff lacked experience with the alarm system. The overall median alarm duration was similar in both ICU types. We found no COVID-19-specific alarm patterns. The alarm fatigue questionnaire results suggest that staff in both types of ICUs experienced alarm fatigue. However, physicians and nurses who were working in COVID-19 ICUs reported a significantly higher level of alarm fatigue (P=.04)., Conclusions: Staff in COVID-19 ICUs were exposed to a higher alarm load, and the majority lacked experience with alarm management and the alarm system. We recommend training and educating ICU staff in alarm management, emphasizing the importance of alarm management training as part of the preparations for future pandemics. However, the limitations of our study design and the specific pandemic conditions warrant further studies to confirm these findings and to explore effective alarm management strategies in different ICU settings., (©Maximilian Markus Wunderlich, Nicolas Frey, Sandro Amende-Wolf, Carl Hinrichs, Felix Balzer, Akira-Sebastian Poncette. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 09.09.2024.)

Objectives: We present the 'COVID-19 evidence ecosystem' (CEOsys) as a German network to inform pandemic management and to support clinical and public health decision-making. We discuss challenges faced when organizing the ecosystem and derive lessons learned for similar networks acting during pandemics or health-related crises., Study Design and Setting: Bringing together 18 university hospitals and additional institutions, CEOsys key activities included research prioritization, conducting living systematic reviews (LSRs), supporting evidence-based (living) guidelines, knowledge translation (KT), detecting research gaps, and deriving recommendations, backed by technical infrastructure and capacity building., Results: CEOsys rapidly produced 31 high-quality evidence syntheses and supported three living guidelines on COVID-19-related topics, while also developing methodological procedures. Challenges included CEOsys' late initiation in relation to the pandemic outbreak, the delayed prioritization of research questions, the continuously evolving COVID-19-related evidence, and establishing a technical infrastructure. Methodological-clinical tandems, the cooperation with national guideline groups and international collaborations were key for efficiency., Conclusion: CEOsys provided a proof-of-concept for a functioning evidence ecosystem at the national level. Lessons learned include that similar networks should, among others, involve methodological and clinical key stakeholders early on, aim for (inter)national collaborations, and systematically evaluate their value. We particularly call for a sustainable network., Competing Interests: Declaration of competing interest F.B. reports a relationship with Pfizer that includes: speaking and lecture fees; reports a relationship with Hans-Bockler-Foundation that includes: funding grants; reports a relationship with German Research Foundation that includes: funding grants; reports a relationship with German Federal Ministry of Health that includes: funding grants; reports a relationship with Federal German Ministry of Education and Research that includes: funding grants; reports a relationship with Charité Foundation that includes: funding grants; reports a relationship with Joint Federal Committee that includes: funding grants; reports a relationship with General Electric that includes: speaking and lecture fees; reports a relationship with Medtronic that includes: board membership. I.K. reports the following grants or contracts from any entity in the past 36 months (type of grant: third party fund; recipient: institutional): German Cancer Aid Foundation, German Ministry of Health (BMG), German Federal Joint Committee independent Funding Programme for Clinical Practice Guidelines developed under the auspices of AWMF member societies (2020-2023), German Ministry for Education and Research (BMBF; 2020-2022); reports consulting fees (recipient: personal) were provided by: European Federation of Periodontology (honoraria, travel costs; 2020-2023), British Society for Periodontology (honoraria, travel costs; 2020-2023), European Society of Endotontology (ESE; honoraria; 2021 – 2023), European Society for Contact Dermatitis (ESCD; honoraria; 2021-2021); reports payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events (recipient: personal) by EBM Frankfurt, Working Group at the Institute for Family Medicine, Goethe-University Frankfurt (honoraria, travel costs; 2020-2022), German Society for Pediatric Infectiology (honoraria; 2021-2022), European Business School (EBS) Wiesbaden (honoraria; 2021-2022), European Association of Dental Implantologists (BDIZ; honoraria, travel costs; 2022-2022); reports payment for expert testimony was provided by German Accreditation Body (DAkkS; honoraria, travel costs); reports participation on a Data Safety Monitoring Board or Advisory Board (Agency for Quality in Medicine (ÄZQ) (a nonprofit organization)—advisory board; type of grant: honoraria, 2020-2023); reports leadership or a fiduciary role in other board, society, committee, or advocacy group (unpaid, nonfinancial): AWMF-Representative in the Board of Trustees- IQTIG (German Institute for Quality and Transparency in Health Care) a nonprofit, governmental institution), Honorary Member—German Society for Breast Health, Member—German Network for Evidence based Medicine (DNEbM), German Society of Surgery (DGCH), Member—Steering Committee for the Guideline Program in Oncology of the German Cancer Society, German Cancer Aid and AWMF, Member—Advisory Board for the Program National Disease Management Guidelines under the auspices of AWMF, German Cancer Society and AWMF, Deputy Chair- Standing Commission on Guidelines of the German Medical Association, the National Association of Statutory Health Insurance Physicians, and the AWMF, Primary Contact on behalf of the AWMF in the Guidelines International Network, Trustee, Guidelines International Network, AWMF Curriculum for guideline developers and guideline advisors; Reviewer, GIN-Mcmaster INGUIDE Program. Other financial or nonfinancial interests: Research interests (Guidelines, Health Services Research, Digitalization); and explicitly declares that she has no ties to pharmaceutical or medical product industry. M.S. reports financial support and administrative support were provided by Charité Universitätsmedizin Berlin Infectious Diseases; reports a relationship with Charité University Hospital Berlin that includes: employment. F.v.D. reports a relationship with Charité University Hospital Berlin that includes: funding grants; reports a relationship with University Medicine Greifswald that includes: funding grants. There are no competing interests for any other author., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: The Charité Alarm Fatigue Questionnaire (CAFQa) is a 9-item questionnaire that aims to standardize how alarm fatigue in nurses and physicians is measured. We previously hypothesized that it has 2 correlated scales, one on the psychosomatic effects of alarm fatigue and the other on staff's coping strategies in working with alarms., Objective: We aimed to validate the hypothesized structure of the CAFQa and thus underpin the instrument's construct validity., Methods: We conducted 2 independent studies with nurses and physicians from intensive care units in Germany (study 1: n=265; study 2: n=1212). Responses to the questionnaire were analyzed using confirmatory factor analysis with the unweighted least-squares algorithm based on polychoric covariances. Convergent validity was assessed by participants' estimation of their own alarm fatigue and exposure to false alarms as a percentage., Results: In both studies, the χ2 test reached statistical significance (study 1: χ226=44.9; P=.01; study 2: χ226=92.4; P<.001). Other fit indices suggested a good model fit (in both studies: root mean square error of approximation <0.05, standardized root mean squared residual <0.08, relative noncentrality index >0.95, Tucker-Lewis index >0.95, and comparative fit index >0.995). Participants' mean scores correlated moderately with self-reported alarm fatigue (study 1: r=0.45; study 2: r=0.53) and weakly with self-perceived exposure to false alarms (study 1: r=0.3; study 2: r=0.33)., Conclusions: The questionnaire measures the construct of alarm fatigue as proposed in our previous study. Researchers and clinicians can rely on the CAFQa to measure the alarm fatigue of nurses and physicians., (© Maximilian Markus Wunderlich, Henning Krampe, Kristina Fuest, Dominik Leicht, Moriz Benedikt Probst, Julian Runge, Sebastian Schmid, Claudia Spies, Björn Weiß, Felix Balzer, Akira-Sebastian Poncette, CAFQa Study Group Germany. Originally published in JMIR Human Factors (https://humanfactors.jmir.org).)

When exposed to hundreds of medical device alarms per day, intensive care unit (ICU) staff can develop "alarm fatigue" (i.e., desensitisation to alarms). However, no standardised way of quantifying alarm fatigue exists. We aimed to develop a brief questionnaire for measuring alarm fatigue in nurses and physicians. After developing a list of initial items based on a literature review, we conducted 15 cognitive interviews with the target group (13 nurses and two physicians) to ensure that the items are face valid and comprehensible. We then asked 32 experts on alarm fatigue to judge whether the items are suited for measuring alarm fatigue. The resulting 27 items were sent to nurses and physicians from 15 ICUs of a large German hospital. We used exploratory factor analysis to further reduce the number of items and to identify scales. A total of 585 submissions from 707 participants could be analysed (of which 14% were physicians and 64% were nurses). The simple structure of a two-factor model was achieved within three rounds. The final questionnaire (called Charité Alarm Fatigue Questionnaire; CAFQa) consists of nine items along two scales (i.e., the "alarm stress scale" and the "alarm coping scale"). The CAFQa is a brief questionnaire that allows clinical alarm researchers to quantify the alarm fatigue of nurses and physicians. It should not take more than five minutes to administer., (© 2023. Springer Nature Limited.)

Background: High 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., Methods: This 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., Results: Staff 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., Conclusions: All 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 Registration: The study was registered at ClinicalTrials.gov (NCT03514173) on 02/05/2018., (© 2023. The Author(s).)

Routine medical care is to be transformed by the introduction of artificial intelligence (AI), requiring medical professionals to acquire a novel set of skills. We assessed the density of AI learning objectives and the availability of courses containing AI content in postgraduate medical education in Germany. The results reveal general paucity in AI learning objectives and content across (sub-)specialty training and continuing medical education (CME) in Germany. Innovative and regulatory solutions are needed to herald an era of physicians competent in navigating medical AI applications.

The aim of this study was to synthesize quantitative research that identified ranking lists of the most severe stressors of patients in the intensive care unit, as perceived by patients, relatives, and health care professionals (HCP). We conducted a systematic literature search in PubMed, MEDLINE, EMBASE, PsycInfo, CINAHL, and Cochrane Library from 1989 to 15 May 2020. Data were analyzed with descriptive and semi-quantitative methods to yield summarizing ranking lists of the most severe stressors. We synthesized the results of 42 prospective cross-sectional observational studies from different international regions. All investigations had assessed patient ratings. Thirteen studies also measured HCP ratings, and four studies included ratings of relatives. Data indicated that patients rate the severity of stressors lower than HCPs and relatives do. Out of all ranking lists, we extracted 137 stressor items that were most frequently ranked among the most severe stressors. After allocation to four domains, a group of clinical ICU experts sorted these stressors with good to excellent agreement according to their stress levels. Our results may contribute to improve HCPs' and relatives' understanding of patients' perceptions of stressors in the ICU. The synthesized stressor rankings can be used for the development of new assessment instruments of stressors.

Background: As one of the most essential technical components of the intensive care unit (ICU), continuous monitoring of patients' vital parameters has significantly improved patient safety by alerting staff through an alarm when a parameter deviates from the normal range. However, the vast number of alarms regularly overwhelms staff and may induce alarm fatigue, a condition recently exacerbated by COVID-19 and potentially endangering patients., Objective: This study focused on providing a complete and repeatable analysis of the alarm data of an ICU's patient monitoring system. We aimed to develop do-it-yourself (DIY) instructions for technically versed ICU staff to analyze their monitoring data themselves, which is an essential element for developing efficient and effective alarm optimization strategies., Methods: This observational study was conducted using alarm log data extracted from the patient monitoring system of a 21-bed surgical ICU in 2019. DIY instructions were iteratively developed in informal interdisciplinary team meetings. The data analysis was grounded in a framework consisting of 5 dimensions, each with specific metrics: alarm load (eg, alarms per bed per day, alarm flood conditions, alarm per device and per criticality), avoidable alarms, (eg, the number of technical alarms), responsiveness and alarm handling (eg alarm duration), sensing (eg, usage of the alarm pause function), and exposure (eg, alarms per room type). Results were visualized using the R package ggplot2 to provide detailed insights into the ICU's alarm situation., Results: We developed 6 DIY instructions that should be followed iteratively step by step. Alarm load metrics should be (re)defined before alarm log data are collected and analyzed. Intuitive visualizations of the alarm metrics should be created next and presented to staff in order to help identify patterns in the alarm data for designing and implementing effective alarm management interventions. We provide the script we used for the data preparation and an R-Markdown file to create comprehensive alarm reports. The alarm load in the respective ICU was quantified by 152.5 (SD 42.2) alarms per bed per day on average and alarm flood conditions with, on average, 69.55 (SD 31.12) per day that both occurred mostly in the morning shifts. Most alarms were issued by the ventilator, invasive blood pressure device, and electrocardiogram (ie, high and low blood pressure, high respiratory rate, low heart rate). The exposure to alarms per bed per day was higher in single rooms (26%, mean 172.9/137.2 alarms per day per bed)., Conclusions: Analyzing ICU alarm log data provides valuable insights into the current alarm situation. Our results call for alarm management interventions that effectively reduce the number of alarms in order to ensure patient safety and ICU staff's work satisfaction. We hope our DIY instructions encourage others to follow suit in analyzing and publishing their ICU alarm data., (©Akira-Sebastian Poncette, Maximilian Markus Wunderlich, Claudia Spies, Patrick Heeren, Gerald Vorderwülbecke, Eduardo Salgado, Marc Kastrup, Markus A Feufel, Felix Balzer. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.05.2021.)