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Technological Distractions (Part 2): A Summary of Approaches to Manage Clinical Alarms With Intent to Reduce Alarm
Bradford D Winters1, Maria M Cvach, Christopher P Bonafide
11Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD.2Department of Integrated Healthcare Delivery, Johns Hopkins Health System, Baltimore, MD.3Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA.4Departments of Physiological Nursing and Neurological Surgery, UC Berkeley/UCSF Joint Bio-Engineering Graduate Programe, Berkeley, CA.5Department of Clinical Engineering, Clinical Engineering Professional Services, University of Virginia Health System, Charlottesville, VA.6Department of Anesthesia and Critical Care Section of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, IL.7Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.8Department of Nephrology, Centre for Kidney Research and Innovation, School of Medicine, University of Nottingham, Nottingham, United Kingdom.9Department of Physiological Nursing, University of California, San Francisco, San Francisco, CA.10Critical Care Division, Department of Critical Care, Grady Health Systems, Atlanta, GA.11Department of Pharmacy and Therapeutics, Critical Care Medicine, Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA.
Objective:
Alarm fatigue is a widely recognized safety and quality problem where exposure to high rates of clinical alarms results in desensitization leading to dismissal of or slowed response to alarms. Nonactionable alarms are thought to be especially problematic. Despite these concerns, the number of clinical alarm signals has been increasing as an everincreasing number of medical technologies are added to the clinical care environment.
Data Sources:
PubMed, SCOPUS, Embase, and CINAHL.
Study Selection:
We performed a systematic review of the literature focused on clinical alarms. We asked a primary key question; "what interventions have been attempted and resulted in the success of reducing alarm fatigue?" and 3-secondary key questions; "what are the negative effects on patients/families; what are the balancing outcomes (unintended consequences of interventions); and what human factor approaches apply to making an effective alarm?"
Data Extraction:
Articles relevant to the Key Questions were selected through an iterative review process and relevant data was extracted using a standardized tool.
Data Synthesis:
We found 62 articles that had relevant and usable data for at least one key question. We found that no study used/developed a clear definition of "alarm fatigue." For our primary key question 1, the relevant studies focused on three main areas: quality improvement/bundled activities; intervention comparisons; and analysis of algorithm-based false and total alarm suppression. All sought to reduce the number of total alarms and/or false alarms to improve the positive predictive value. Most studies were successful to varying degrees. None measured alarm fatigue directly.
Conclusions:
There is no agreed upon valid metric(s) for alarm fatigue, and the current methods are mostly indirect. Assuming that reducing the number of alarms and/or improving positive predictive value can reduce alarm fatigue, there are promising avenues to address patient safety and quality problem. Further investment is warranted not only in interventions that may reduce alarm fatigue but also in defining how to best measure it.
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