Literature DB >> 24153215

Alarm fatigue: a patient safety concern.

Sue Sendelbach1, Marjorie Funk.   

Abstract

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.

Entities:  

Mesh:

Year:  2013        PMID: 24153215     DOI: 10.1097/NCI.0b013e3182a903f9

Source DB:  PubMed          Journal:  AACN Adv Crit Care        ISSN: 1559-7768


  61 in total

1.  Association between exposure to nonactionable physiologic monitor alarms and response time in a children's hospital.

Authors:  Christopher P Bonafide; Richard Lin; Miriam Zander; Christian Sarkis Graham; Christine W Paine; Whitney Rock; Andrew Rich; Kathryn E Roberts; Margaret Fortino; Vinay M Nadkarni; A Russell Localio; Ron Keren
Journal:  J Hosp Med       Date:  2015-04-15       Impact factor: 2.960

2.  Machine learning applied to multi-sensor information to reduce false alarm rate in the ICU.

Authors:  Gal Hever; Liel Cohen; Michael F O'Connor; Idit Matot; Boaz Lerner; Yuval Bitan
Journal:  J Clin Monit Comput       Date:  2019-04-06       Impact factor: 2.502

3.  2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry.

Authors:  Jonathan S Steinberg; Niraj Varma; Iwona Cygankiewicz; Peter Aziz; Paweł Balsam; Adrian Baranchuk; Daniel J Cantillon; Polychronis Dilaveris; Sergio J Dubner; Nabil El-Sherif; Jaroslaw Krol; Malgorzata Kurpesa; Maria Teresa La Rovere; Suave S Lobodzinski; Emanuela T Locati; Suneet Mittal; Brian Olshansky; Ewa Piotrowicz; Leslie Saxon; Peter H Stone; Larisa Tereshchenko; Mintu P Turakhia; Gioia Turitto; Neil J Wimmer; Richard L Verrier; Wojciech Zareba; Ryszard Piotrowicz
Journal:  Ann Noninvasive Electrocardiol       Date:  2017-05       Impact factor: 1.468

4.  Shaping critical care through sound-driven innovation: introduction, outline, and research agenda.

Authors:  Elif Özcan; Wim J R Rietdijk; Diederik Gommers
Journal:  Intensive Care Med       Date:  2019-12-03       Impact factor: 17.440

5.  Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.

Authors:  Christopher Barton; Uli Chettipally; Yifan Zhou; Zirui Jiang; Anna Lynn-Palevsky; Sidney Le; Jacob Calvert; Ritankar Das
Journal:  Comput Biol Med       Date:  2019-04-24       Impact factor: 4.589

6.  Contribution of Electrocardiographic Accelerated Ventricular Rhythm Alarms to Alarm Fatigue.

Authors:  Sukardi Suba; Cass Piper Sandoval; Jessica K Zègre-Hemsey; Xiao Hu; Michele M Pelter
Journal:  Am J Crit Care       Date:  2019-05       Impact factor: 2.228

7.  Generalizability of SuperAlarm via Cross-Institutional Performance Evaluation.

Authors:  Ran Xiao; Duc Do; Cheng Ding; Karl Meisel; Randall Lee; Xiao Hu
Journal:  IEEE Access       Date:  2020-07-16       Impact factor: 3.367

8.  Implementation of a novel postoperative monitoring system using automated Modified Early Warning Scores (MEWS) incorporating end-tidal capnography.

Authors:  Joseph M Blankush; Robbie Freeman; Joy McIlvaine; Trung Tran; Stephen Nassani; I Michael Leitman
Journal:  J Clin Monit Comput       Date:  2016-10-20       Impact factor: 2.502

9.  Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

Authors:  Lujie Chen; Artur Dubrawski; Donghan Wang; Madalina Fiterau; Mathieu Guillame-Bert; Eliezer Bose; Ata M Kaynar; David J Wallace; Jane Guttendorf; Gilles Clermont; Michael R Pinsky; Marilyn Hravnak
Journal:  Crit Care Med       Date:  2016-07       Impact factor: 7.598

Review 10.  Current monitoring and innovative predictive modeling to improve care in the pediatric cardiac intensive care unit.

Authors:  Mary K Olive; Gabe E Owens
Journal:  Transl Pediatr       Date:  2018-04
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.