Statistical process monitoring creates a hemodynamic trajectory map after pediatric cardiac surgery: A case study of the arterial switch operation

Abstract

Abstract Postoperative critical care management of congenital heart disease patients requires prompt intervention when the patient deviates significantly from clinician‐determined vital sign and hemodynamic goals. Current monitoring systems only allow for static thresholds to be set on individual variables, despite the expectations that these signals change as the patient recovers and that variables interact. To address this incongruency, we have employed statistical process monitoring (SPM) techniques originally developed to monitor batch industrial processes to monitor high‐frequency vital sign and hemodynamic data to establish multivariate trajectory maps for patients with d‐transposition of the great arteries following the arterial switch operation. In addition to providing multivariate trajectory maps, the multivariate control charts produced by the SPM framework allow for assessment of adherence to the desired trajectory at each time point as the data is collected. Control charts based on slow feature analysis were compared with those based on principal component analysis. Alarms generated by the multivariate control charts are discussed in the context of the available clinical documentation.

Keywords

• computational modeling
• congenital heart disease
• medical devices
• postoperative monitoring
• statistical process monitoring