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Cases & Commentaries
- Web M&M
Lina Bergman, RN, MSc, and Wendy Chaboyer, RN, PhD; February 2019
Following surgery under general anesthesia, a boy was extubated and brought to postanesthesia care unit (PACU). Due to the patient's age and length of the surgery, the PACU anesthesiologist ordered continuous pulse-oximetry monitoring for 24 hours. Deemed stable to leave the PACU, the boy was transported to the regular floor. When the nurse went to place the patient on pulse oximetry, she realized he was markedly hypoxic. She administered oxygen by face mask, but he became bradycardic and hypotensive and a code blue was called.
Journal Article > Study
Beaulieu MJ. MCN Am J Matern Child Nurs. 2009;34:18-23.
This study discovers that using selected failure to rescue process measures may help identify areas for improvement in perinatal care.
Journal Article > Review
Ghaferi AA, Dimick JB. Br J Surg. 2016;103:e47-e51.
Failure-to-rescue is considered a potential contributing factor in the wide variations in surgical mortality rates. This review explored the evidence regarding the surgical mortality of older patients and found system factors that affected failure-to-rescue rates, including safety culture and access to technology. The authors suggest that teamwork and communication improvement can help reduce failure-to-rescue in this patient population.
Journal Article > Study
Effect of a pediatric early warning system on all-cause mortality in hospitalized pediatric patients.
Parshuram CS, Dryden-Palmer K, Farrell C, et al; Canadian Critical Care Trials Group and EPOCH Investigators. JAMA. 2018;319:1002-1012.
Identifying incipient clinical deterioration is a prerequisite for rapid response and prevention of harm for hospitalized patients. This study tested a bedside pediatric early warning system, which included an illness severity score, standardized documentation, and monitoring protocols. In a cluster-randomized trial in several high-income countries, implementation of the bundle did not result in decreased in-hospital mortality compared to usual care. The overall mortality rate in the study was less than 0.2%. The authors suggest that this unexpectedly low mortality rate may have made it difficult to detect differences in intervention versus control hospitals. A related editorial suggests that artificial intelligence should be used to identify clinical deterioration and that outcomes beyond mortality should be considered in their evaluation.
Ross C. STAT. May 13, 2019.
Nuisance alarms, interruptions, and insufficient staff availability can hinder effective monitoring and response to acute patient deterioration. This news article reports on how hospital logistics centers are working toward utilizing artificial intelligence to improve clinician response to alarms by proactively identifying hospitalized patients at the highest risk for heart failure to trigger emergency response teams when their condition rapidly declines.