Neurologic Monitoring of Neonates in the Neonatal Intensive Care Unit

The American Clinical Neurophysiology Society has identified neonates at high risk for neurologic sequelae. These clinical conditions include: hypoxic ischemic encephalopathy, neonatal seizures, significant intraventricular hemorrhage, neonates placed on extracorporeal membrane oxygenation, central nervous system abnormalities, neuromuscular abnormalities, metabolic or neuromuscular disorders, and any change in dose or type of seizure medication. Neonates with these conditions often develop seizures and benefit from neurologic monitoring through electroencephalography (EEG) technology. Appropriate monitoring can lead to identification of prognostic EEG patterns and accurate diagnosis of seizures and non-seizure events. Neonatal seizures are typically subclinical thus making accurate diagnosis a significant challenge. Timely and accurate diagnosis of seizures leads to improved neurologic and developmental outcomes. This project was to develop an algorithm to guide clinician ordering of neurologic monitoring at sites where a lack of consistency was problematic. The objectives for this doctoral project included: 1) Development of a Neurologic Monitoring Algorithm; 2) Introduction of the Algorithm to clinicians at the implementation sites; 3) Assessment of EEG testing and neurology consult ordered at admission after implementation; and 4) Dissemination of results to the Neuro Newborn Intensive Care Unit steering committee and submission of an abstract for poster presentation at the 2017 Academy of Neonatal Nursing Las Vegas Conference, National Neonatal Conference. A literature review was conducted to determine the prevalence of abnormal brain activity in infants, conditions that increase the risk of seizures, the consequences of untreated seizures and the value of neurologic monitoring. The search confirmed that specific guidelines for neurologic monitoring could be used to guide diagnosis of seizures, response to treatment, and correlation with infant exam. Prospective studies concluded that monitoring led to earlier identification of seizures and acute neurologic deterioration plus the ability to guide treatment. A Neurologic Monitoring Algorithm for infants with high-risk clinical conditions was developed and implemented. A chart audit of neurologic testing ordered and neurology consult at admission were analyzed. The results of this audit found improved testing based on the algorithm with appropriate timeframes, improved neurology consultation in a timely manner, and monitoring was used to diagnose sub-clinical seizures in 30% of infants and assisted in prognostic data and treatment decision making for 30% of infants. The algorithms guided clinicians in appropriate neurologic monitoring. The evidence-based algorithms improved seizure identification and decreased time to treatment leading to better long-term and developmental outcomes. Recommendations include continued used of algorithms with yearly training to clinicians and regular chart audits.