Nicholas S Abend1, Alexis A Topjian, Sankey Williams. 1. Departments of *Neurology, †Pediatrics, and ‡Anesthesia and Critical Care Medicine, The Children's Hospital of Philadelphia and the Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.; §Department of Medicine, the Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.; and ‖Department of Health Care Management, Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.
Abstract
OBJECTIVES: Electrographic seizures in critically ill children may be identified by continuous EEG monitoring. We evaluated the cost effectiveness of 4 electrographic seizure identification strategies (no EEG monitoring and EEG monitoring for 1 hour, 24 hours, or 48 hours). METHODS: We created a decision tree to model the relationships among variables from a societal perspective. To provide input for the model, we estimated variable costs directly related to EEG monitoring from their component parts, and we reviewed the literature to estimate the probabilities of outcomes. We calculated incremental cost-effectiveness ratios to identify the trade-off between cost and effectiveness at different willingness-to-pay values. RESULTS: Our analysis found that the preferred strategy was EEG monitoring for 1 hour, 24 hours, and 48 hours if the decision maker was willing to pay <$1,666, $1,666-$22,648, and >$22,648 per critically ill child identified with electrographic seizures, respectively. The 48-hour strategy only identified 4% more children with electrographic seizures at substantially higher cost. Sensitivity analyses found that all 3 strategies were acceptable at lower willingness-to-pay values when children with higher electrographic seizure risk were monitored. CONCLUSIONS: The results of this study support monitoring of critically ill children for 24 hours because the cost to identify a critically ill child with electrographic seizures is modest. Further study is needed to predict better which children may benefit from 48 hours of EEG monitoring because the costs are much higher.
OBJECTIVES: Electrographic seizures in critically ill children may be identified by continuous EEG monitoring. We evaluated the cost effectiveness of 4 electrographic seizure identification strategies (no EEG monitoring and EEG monitoring for 1 hour, 24 hours, or 48 hours). METHODS: We created a decision tree to model the relationships among variables from a societal perspective. To provide input for the model, we estimated variable costs directly related to EEG monitoring from their component parts, and we reviewed the literature to estimate the probabilities of outcomes. We calculated incremental cost-effectiveness ratios to identify the trade-off between cost and effectiveness at different willingness-to-pay values. RESULTS: Our analysis found that the preferred strategy was EEG monitoring for 1 hour, 24 hours, and 48 hours if the decision maker was willing to pay <$1,666, $1,666-$22,648, and >$22,648 per critically ill child identified with electrographic seizures, respectively. The 48-hour strategy only identified 4% more children with electrographic seizures at substantially higher cost. Sensitivity analyses found that all 3 strategies were acceptable at lower willingness-to-pay values when children with higher electrographic seizure risk were monitored. CONCLUSIONS: The results of this study support monitoring of critically ill children for 24 hours because the cost to identify a critically ill child with electrographic seizures is modest. Further study is needed to predict better which children may benefit from 48 hours of EEG monitoring because the costs are much higher.
Authors: Hansel M Greiner; Katherine Holland; James L Leach; Paul S Horn; Andrew D Hershey; Douglas F Rose Journal: Pediatrics Date: 2012-02-13 Impact factor: 7.124
Authors: Gretchen M Brophy; Rodney Bell; Jan Claassen; Brian Alldredge; Thomas P Bleck; Tracy Glauser; Suzette M Laroche; James J Riviello; Lori Shutter; Michael R Sperling; David M Treiman; Paul M Vespa Journal: Neurocrit Care Date: 2012-08 Impact factor: 3.210
Authors: Fenella J Kirkham; Angela M Wade; Fiona McElduff; Stewart G Boyd; Robert C Tasker; Melinda Edwards; Brian G R Neville; Norbert Peshu; Charles R J C Newton Journal: Intensive Care Med Date: 2012-04-11 Impact factor: 17.440
Authors: Nicholas S Abend; Katherine L Wagenman; Taylor P Blake; Maria T Schultheis; Jerilynn Radcliffe; Robert A Berg; Alexis A Topjian; Dennis J Dlugos Journal: Epilepsy Behav Date: 2015-04-20 Impact factor: 2.937
Authors: France W Fung; Marin Jacobwitz; Lisa Vala; Darshana Parikh; Maureen Donnelly; Rui Xiao; Alexis A Topjian; Nicholas S Abend Journal: Epilepsia Date: 2019-09-20 Impact factor: 5.864
Authors: Jainn-Jim Lin; Brenda L Banwell; Robert A Berg; Dennis J Dlugos; Rebecca N Ichord; Todd J Kilbaugh; Roxanne E Kirsch; Matthew P Kirschen; Daniel J Licht; Shavonne L Massey; Maryam Y Naim; Natalie E Rintoul; Alexis A Topjian; Nicholas S Abend Journal: Pediatr Crit Care Med Date: 2017-03 Impact factor: 3.624
Authors: Aaron F Struck; Mohammad Tabaeizadeh; Sarah E Schmitt; Andres Rodriguez Ruiz; Christa B Swisher; Thanujaa Subramaniam; Christian Hernandez; Safa Kaleem; Hiba A Haider; Abbas Fodé Cissé; Monica B Dhakar; Lawrence J Hirsch; Eric S Rosenthal; Sahar F Zafar; Nicholas Gaspard; M Brandon Westover Journal: JAMA Neurol Date: 2020-04-01 Impact factor: 18.302
Authors: Ryan P Williams; Brenda Banwell; Robert A Berg; Dennis J Dlugos; Maureen Donnelly; Rebecca Ichord; Sudha Kilaru Kessler; Jane Lavelle; Shavonne L Massey; Jennifer Hewlett; Allison Parker; Alexis A Topjian; Nicholas S Abend Journal: Epilepsia Date: 2016-03-07 Impact factor: 5.864