Development of an Alarm Algorithm, With Nanotechnology Multimodal Sensor, to Predict Impending Infusion Failure and Improve Safety of Peripheral Intravenous Catheters in Neonates

Abstract

Peripheral intravenous catheters connected to an infusion pump are necessary for the delivery of fluids, nutrition, and medications to hospitalized neonates but are not without complications. These adverse events contribute to hospital-acquired patient harm. An artificial intelligence theory called fuzzy logic may allow the use of appropriate variables to predict infusion failure. This innovative study aimed to develop an intravenous infusion nanotechnology monitoring system that would alert the nurse to impending peripheral intravenous infusion failure. An intravenous infusion nanotechnology monitoring system, using predictor variables of pressure, pH, and oxygen saturation used in a fuzzy logic alarm algorithm was developed to alert the nurse to impending peripheral intravenous infusion failure. The developed intravenous infusion nanotechnology monitoring system is composed of a peripheral intravenous catheter with nanotechnology multimodal sensor, an intravenous pump, a fuzzy logic algorithm, and alarm. For example, using this system, an elevated in-line pressure, a low pH, and a low venous oxygen level would generate an alarm for possible impending infusion failure. With further development, this technology may help nurses predict and prevent adverse outcomes from intravenous infusions. This work shows how nurses can be content experts and innovators of technology that they use to make clinical decisions. After regulatory approval, a randomized controlled trial may be performed to investigate whether interventions at the time of an alarm would result in fewer adverse outcomes and improve safety.