Abstract
Objective
To characterize the rate of monitoring alarms by alarm priority, signal type, and developmental age in a Level-IIIB Neonatal Intensive Care Unit (NICU) population.
Study design
Retrospective analysis of 2,294,687 alarm messages from Philips monitors in a convenience sample of 917 NICU patients, covering 12,001 patient-days. We stratified alarm rates by alarm priority, signal type, postmenstrual age (PMA) and birth weight (BW), and reviewed and adjudicated over 21,000 critical alarms.
Results
Of all alarms, 3.6% were critical alarms, 55.0% were advisory alarms, and 41.4% were device alerts. Over 60% of alarms related to oxygenation monitoring. The average alarm rate (±SEM) was 177.1 ± 4.9 [median: 135.9; IQR: 89.2–213.3] alarms/patient-day; the medians varied significantly with PMA and BW (p < 0.001) in U-shaped patterns, with higher rates at lower and higher PMA and BW. Based on waveform reviews, over 99% of critical arrhythmia alarms were deemed technically false.
Conclusions
The alarm burden in this NICU population is very significant; the average alarm rate significantly underrepresents alarm rates at low and high PMA and BW. Virtually all critical arrhythmia alarms were artifactual.
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Change history
25 July 2018
The previously published version of this Article contained an error in Fig. 1 where the “HR low” and “HR high” labels were swapped.
Furthermore, in Table 1 of this Article, the fifth row in the centre column contained a typographical error where the study population birth weight incorrectly read “2050 (1 450–2 650)”, rather than “2050 (1450–2650)”.
These errors have now been corrected in both the PDF and HTML versions of the Article.
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Acknowledgements
The authors wish to thank Mr. Jeffrey Smith, Clinical Engineering, BIDMC, for his help and support over the course of this study. Additionally, the authors thank Mr. Nirmal Balachundhar, Mr. Rémi Dekimpe, Ms. Tiffany Ho, and Ms. Nalini Singh for their help with the adjudication of bedside monitoring alarms. The data collection and archiving was supported in part through grants R01 EB001659 and R01 GM104987 from the National Institute of Biomedical Imaging and Bioengineering and National Institute of General Medical Sciences, respectively, of the United States National Institutes of Health. The data analysis was supported in part by Nihon Kohden Corporation and Nihon Kohden Innovation Center, and in part by a Massachusetts Institute of Technology (MIT) Peter J. Eloranta Summer Undergraduate Research Fellowship and the MIT-Wertheimer Undergraduate Research and Innovation Scholar Fund. Preliminary analyses of this work were presented as a poster at the 2016 Pediatric Academic Societies Annual Meeting in Baltimore, MD.
Author contributions
TL led the data analysis, interpreted the results, helped draft the initial manuscript, critically reviewed and revised the manuscript, and approved the final manuscript as submitted. MM contributed to the data analysis, interpreted the results, helped draft and critically review and revise the initial manuscript, and approved the final manuscript as submitted. WT and SY provided clinical perspective on the study, interpreted the results, critically reviewed and revised the initial manuscript, and approved the final manuscript as submitted. DM supported the clinical data extraction and data collection, critically reviewed the initial manuscript, and approved the final manuscript as submitted. MG contributed to and supported the data collection, provided clinical perspective on the study, interpreted the results, critically reviewed and revised the initial manuscript, and approved the final manuscript as submitted. TH conceptualized, designed, and supervised all aspects of the study, including data collection, data analysis, overall study progress, and drafting and revising of the manuscript. He critically reviewed the manuscript and approved the final manuscript as submitted.
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Conflict of Interest
TH has received research funding from the National Institutes of Health, Nihon Kohden Corporation, Maxim Integrated, and Philips Healthcare. MM remained a salaried employee of Nihon Kohden Corporation while contributing to this study as a Visiting Scientist at MIT’s Institute for Medical Engineering & Science. TL received partial internship support from Nihon Kohden Innovation Center. SY, DM, WT, and MG declare no potential conflict of interest.
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Li, T., Matsushima, M., Timpson, W. et al. Epidemiology of patient monitoring alarms in the neonatal intensive care unit. J Perinatol 38, 1030–1038 (2018). https://doi.org/10.1038/s41372-018-0095-x
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DOI: https://doi.org/10.1038/s41372-018-0095-x
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