Standardised electronic algorithms for monitoring prophylaxis of postoperative nausea and vomiting

用于监测术后恶心呕吐预防的标准化电子算法

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Abstract

INTRODUCTION: Despite comprehensive guidelines with high-grade evidence, postoperative nausea and vomiting (PONV) remains a frequent problem in anaesthesia care. Anaesthesia information management systems (AIMS) may aid clinicians in PONV prevention, but their benefit is critically dependent on the details of implementation into practice. This study aimed to examine strengths and weaknesses of the local AIMS-based algorithm in prevention of PONV. MATERIAL AND METHODS: This retrospective study was conducted in the post-anaesthesia care unit (PACU) of a university hospital and included 10 604 patients aged 18 or older who were followed up in the PACU (intracranial, obstetrical or cardiothoracic surgery excluded) from March 2013 until March 2014. The PONV incidence in PACU and AIMS data validity were analysed. RESULTS: Adherence to PONV guideline recommendations was considerably low, with only 5749 (54%) of the patients receiving correct PONV prophylaxis. Two thousand seven hundred sixty-six (26%) of the patients received an insufficient PONV prophylaxis, which was associated with an excess PONV incidence (11% vs. 4% with correct prophylaxis, p < 0.001) in the PACU. Two thousand four hundred forty-nine (23%) of all patients were discharged from the PACU with an insufficient PONV prophylaxis despite perioperative digital PONV prevention algorithms. CONCLUSIONS: Adherence to PONV prophylaxis guidelines in the era of AIMS software and decision support is still remarkably low. The AIMS data usefulness depends on the user, the type of data input and the configuration of the software. Adherence to correct PONV prophylaxis should be re-evaluated systematically before discharge from PACU.

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