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 at the University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.; §Department of Medicine, the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.; and ‖Department of Health Care Management, the Wharton School at the University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.
Abstract
PURPOSE: Electrographic status epilepticus (ESE) in critically ill children is associated with unfavorable functional outcomes, but identifying candidates for ESE management requires resource-intense EEG monitoring. A cost-effectiveness analysis was performed to estimate how much ESE identification and management would need to improve patient outcomes to make EEG monitoring strategies a good value. METHODS: A decision tree was created to examine the relationships among variables important to deciding whether to perform EEG monitoring. Variable costs were estimated from their component parts, outcomes were estimated in quality-adjusted life-years, and incremental cost-effectiveness ratios were calculated to compare the relative values using four alternative EEG monitoring strategies that varied by monitoring duration. RESULTS: Forty-eight hours of EEG monitoring would be worth its cost if ESE identification and management improved patient outcomes by ≥7%. If ESE identification and management improved patient outcomes by 3% to 6%, then 24 or 48 hours of EEG monitoring would be worth the cost depending on how much decision makers were willing to pay per quality-adjusted life-year gained. If ESE identification and management improved outcomes by as little as 3%, then 24 hours of EEG monitoring would be worth the cost. CONCLUSIONS: EEG monitoring has the potential to be cost-effective if ESE identification and management improves patient outcomes by as little as 3%.
PURPOSE: Electrographic status epilepticus (ESE) in critically ill children is associated with unfavorable functional outcomes, but identifying candidates for ESE management requires resource-intense EEG monitoring. A cost-effectiveness analysis was performed to estimate how much ESE identification and management would need to improve patient outcomes to make EEG monitoring strategies a good value. METHODS: A decision tree was created to examine the relationships among variables important to deciding whether to perform EEG monitoring. Variable costs were estimated from their component parts, outcomes were estimated in quality-adjusted life-years, and incremental cost-effectiveness ratios were calculated to compare the relative values using four alternative EEG monitoring strategies that varied by monitoring duration. RESULTS: Forty-eight hours of EEG monitoring would be worth its cost if ESE identification and management improved patient outcomes by ≥7%. If ESE identification and management improved patient outcomes by 3% to 6%, then 24 or 48 hours of EEG monitoring would be worth the cost depending on how much decision makers were willing to pay per quality-adjusted life-year gained. If ESE identification and management improved outcomes by as little as 3%, then 24 hours of EEG monitoring would be worth the cost. CONCLUSIONS: EEG monitoring has the potential to be cost-effective if ESE identification and management improves patient outcomes by as little as 3%.
Authors: Stacey K H Tay; Lawrence J Hirsch; Linda Leary; Nathalie Jette; John Wittman; Cigdem I Akman Journal: Epilepsia Date: 2006-09 Impact factor: 5.864
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: N S Abend; A M Gutierrez-Colina; A A Topjian; H Zhao; R Guo; M Donnelly; R R Clancy; D J Dlugos Journal: Neurology Date: 2011-02-09 Impact factor: 9.910
Authors: N S Abend; A Topjian; R Ichord; S T Herman; M Helfaer; M Donnelly; V Nadkarni; D J Dlugos; R R Clancy Journal: Neurology Date: 2009-06-02 Impact factor: 9.910
Authors: Daniel H Arndt; Jason T Lerner; Joyce H Matsumoto; Andranik Madikians; Sue Yudovin; Hannah Valino; David L McArthur; Joyce Y Wu; Michelle Leung; Farzad Buxey; Conrad Szeliga; Michele Van Hirtum-Das; Raman Sankar; Amy Brooks-Kayal; Christopher C Giza Journal: Epilepsia Date: 2013-09-13 Impact factor: 5.864