ABSTRACT
Learning to use a new electronic anesthesia information management system can be challenging. Documenting anesthetic events, medication administration, and airway management in an unfamiliar system while simultaneously caring for a patient with the vigilance required for safe anesthesia can be distracting and risky. This technical report describes a vendor-agnostic approach to training using a high-technology manikin in a simulated clinical scenario. Training was feasible and valued by participants but required a combination of electronic and manual components. Further exploration may reveal simulated patient care training that provides the greatest benefit to participants as well as feedback to inform electronic health record improvements.
Subject(s)
Anesthesiologists/education , Computer-Assisted Instruction/methods , Education, Medical, Continuing/methods , Electronic Health Records , Health Information Management , High Fidelity Simulation Training/methods , Manikins , Anesthesiologists/psychology , Attitude of Health Personnel , Clinical Competence , Documentation , Feasibility Studies , Forms and Records Control , Health Knowledge, Attitudes, Practice , Humans , Task Performance and AnalysisABSTRACT
BACKGROUND: Alarm fatigue is reported to be a major threat to patient safety, yet little empirical data support its existence in the hospital. OBJECTIVE: To determine if nurses exposed to high rates of nonactionable physiologic monitor alarms respond more slowly to subsequent alarms that could represent life-threatening conditions. DESIGN: Observational study using video. SETTING: Freestanding children's hospital. PATIENTS: Pediatric intensive care unit (PICU) patients requiring inotropic support and/or mechanical ventilation, and medical ward patients. INTERVENTION: None. MEASUREMENTS: Actionable alarms were defined as correctly identifying physiologic status and warranting clinical intervention or consultation. We measured response time to alarms occurring while there were no clinicians in the patient's room. We evaluated the association between the number of nonactionable alarms the patient had in the preceding 120 minutes (categorized as 0-29, 30-79, or 80+ alarms) and response time to subsequent alarms in the same patient using a log-rank test that accounts for within-nurse clustering. RESULTS: We observed 36 nurses for 210 hours with 5070 alarms; 87.1% of PICU and 99.0% of ward clinical alarms were nonactionable. Kaplan-Meier plots showed incremental increases in response time as the number of nonactionable alarms in the preceding 120 minutes increased (log-rank test stratified by nurse P < 0.001 in PICU, P = 0.009 in the ward). CONCLUSIONS: Most alarms were nonactionable, and response time increased as nonactionable alarm exposure increased. Alarm fatigue could explain these findings. Future studies should evaluate the simultaneous influence of workload and other factors that can impact response time.
Subject(s)
Clinical Alarms/statistics & numerical data , Intensive Care Units, Pediatric/statistics & numerical data , Monitoring, Physiologic/nursing , Nursing Care/statistics & numerical data , Patient Safety , Reaction Time , Adolescent , Child , Child, Preschool , Clinical Alarms/classification , Clinical Alarms/standards , Critical Care Nursing/standards , Critical Care Nursing/statistics & numerical data , Heart Failure/nursing , Hospitals, Pediatric , Humans , Infant , Infant, Newborn , Intensive Care Units, Pediatric/standards , Kaplan-Meier Estimate , Monitoring, Physiologic/instrumentation , Multivariate Analysis , Nursing Care/psychology , Nursing Care/standards , Pediatric Nursing/standards , Pediatric Nursing/statistics & numerical data , Respiratory Insufficiency/nursing , WorkforceABSTRACT
False physiologic monitor alarms are extremely common in the hospital environment. High false alarm rates have the potential to lead to alarm fatigue, leading nurses to delay their responses to alarms, ignore alarms, or disable them entirely. Recent evidence from the U.S. Food and Drug Administration (FDA) and The Joint Commission has demonstrated a link between alarm fatigue and patient deaths. Yet, very little scientific effort has focused on the rigorous quantitative measurement of alarms and responses in the hospital setting. We developed a system using multiple temporarily mounted, minimally obtrusive video cameras in hospitalized patients' rooms to characterize physiologic monitor alarms and nurse responses as a proxy for alarm fatigue. This allowed us to efficiently categorize each alarm's cause, technical validity, actionable characteristics, and determine the nurse's response time. We describe and illustrate the methods we used to acquire the video, synchronize and process the video, manage the large digital files, integrate the video with data from the physiologic monitor alarm network, archive the video to secure servers, and perform expert review and annotation using alarm "bookmarks." We discuss the technical and logistical challenges we encountered, including the root causes of hardware failures as well as issues with consent, confidentiality, protection of the video from litigation, and Hawthorne-like effects. The description of this video method may be useful to multidisciplinary teams interested in evaluating physiologic monitor alarms and alarm responses to better characterize alarm fatigue and other patient safety issues in clinical settings.
