An Observational Study of Pulse Oximeter Alarms in a Newborn Unit at a Tertiary Facility in Kenya
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Background
Continuous pulse oximetry monitoring of neonates in the intensive care unit improves clinical outcomes. However, monitoring will only be effective if actions are taken based on the results of appropriate monitoring. While threshold alarms are used to alert providers about clinical deterioration, alarm fatigue significantly degrades the effectiveness of alarms if the thresholds are not adapted based on the clinical status of each neonate, including changes seen in neonatal physiology.
Methods
As part of a quality improvement project aimed at reducing the risk of apnea of prematurity, which included caffeine citrate administration, we conducted an observational study of alarms during the implementation of continuous pulse oximetry in a newborn unit (NBU) of a tertiary teaching and referral healthcare facility in Kenya. Default alarm thresholds were set at 85 to 96% for oxygen saturation (SpO 2 ) and 90 to 200 beats per minute (bpm) for pulse rate (PR).
Results
Among 49 neonates with a median birth weight of 1.3 kilograms (IQR,329 grams) at admission, 16,212 hours of data were recorded. Respiratory support was provided on 28% of patient days. The median number of alarms per hour per neonate was 12 (IQR,40) visual and 9 (IQR,21) audible alarms. Half of the SpO 2 values lay outside the thresholds, with 44% exceeding the upper threshold of 96%, with a median duration of 20 (IQR,72) seconds. The mean for HR was 1 (SD,1.17) alarm per hour per neonate, with 2% of the data lying outside the thresholds.
Conclusions
The thresholds for SpO 2 resulted in a high alarm burden. A short alarm delay could have significantly reduced this burden. Setting an upper threshold of 96% in clinically stable babies resulted in a large volume of unnecessary alarms. Adjusting thresholds based on individual neonatal characteristics, including consideration of the need for respiratory support, is recommended. Effective monitoring of neonates requires individualized alarm thresholds and additional smart algorithms specifically designed to detect clinical deterioration.
