James W Antoon1,2, James A Feinstein3,4, Carlos G Grijalva5, Yuwei Zhu6, Emily Dickinson3,4, Justine C Stassun1,2, Jakobi A Johnson1,2, Mert Sekmen1,2, Yasas C Tanguturi7, James C Gay8, Derek J Williams1,2. 1. aDivision of Hospital Medicine, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, Tennessee. 2. bDepartment of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee. 3. cAdult and Child Consortium for Health Outcomes Research and Delivery Science, Children's Hospital Colorado, Aurora, Colorado. 4. dUniversity of Colorado Anschutz Medical Campus, Aurora, Colorado. 5. eDivision of Pharmacoepidemiology, Department of Health Policy. 6. fDepartment of Biostatistics. 7. gDivision of Child & Adolescent Psychiatry, Department of Psychiatry. 8. hDivision of General Pediatrics, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee.
Abstract
OBJECTIVES: The objective of this study was to develop and validate an approach to accurately identify incident pediatric neuropsychiatric events (NPEs) requiring hospitalization by using administrative data. METHODS: We performed a cross-sectional, multicenter study of children 5 to 18 years of age hospitalized at two US children's hospitals with an NPE. We developed and evaluated 3 NPE identification algorithms: (1) primary or secondary NPE International Classification of Diseases, 10th Revision diagnosis alone, (2) NPE diagnosis, the NPE was present on admission, and the primary diagnosis was not malignancy- or surgery-related, and (3) identical to algorithm 2 but without requiring the NPE be present on admission. The positive predictive value (PPV) of each algorithm was calculated overall and by diagnosis field (primary or secondary), clinical significance, and NPE subtype. RESULTS: There were 1098 NPE hospitalizations included in the study. A total of 857 confirmed NPEs were identified for algorithm 1, yielding a PPV of 0.78 (95% confidence interval [CI] 0.76-0.80). Algorithm 2 (n = 846) had an overall PPV of 0.89 (95% CI 0.87-0.91). For algorithm 3 (n = 938), the overall PPV was 0.86 (95% CI 0.83-0.88). PPVs varied by diagnosis order, NPE clinical significance, and subtype. The PPV for critical clinical significance was 0.99 (0.97-0.99) for all 3 algorithms. CONCLUSIONS: We identified a highly accurate method to identify neuropsychiatric adverse events in children and adolescents. The use of these approaches will improve the rigor of future studies of NPE, including the necessary evaluations of medication adverse events, infections, and chronic conditions.
OBJECTIVES: The objective of this study was to develop and validate an approach to accurately identify incident pediatric neuropsychiatric events (NPEs) requiring hospitalization by using administrative data. METHODS: We performed a cross-sectional, multicenter study of children 5 to 18 years of age hospitalized at two US children's hospitals with an NPE. We developed and evaluated 3 NPE identification algorithms: (1) primary or secondary NPE International Classification of Diseases, 10th Revision diagnosis alone, (2) NPE diagnosis, the NPE was present on admission, and the primary diagnosis was not malignancy- or surgery-related, and (3) identical to algorithm 2 but without requiring the NPE be present on admission. The positive predictive value (PPV) of each algorithm was calculated overall and by diagnosis field (primary or secondary), clinical significance, and NPE subtype. RESULTS: There were 1098 NPE hospitalizations included in the study. A total of 857 confirmed NPEs were identified for algorithm 1, yielding a PPV of 0.78 (95% confidence interval [CI] 0.76-0.80). Algorithm 2 (n = 846) had an overall PPV of 0.89 (95% CI 0.87-0.91). For algorithm 3 (n = 938), the overall PPV was 0.86 (95% CI 0.83-0.88). PPVs varied by diagnosis order, NPE clinical significance, and subtype. The PPV for critical clinical significance was 0.99 (0.97-0.99) for all 3 algorithms. CONCLUSIONS: We identified a highly accurate method to identify neuropsychiatric adverse events in children and adolescents. The use of these approaches will improve the rigor of future studies of NPE, including the necessary evaluations of medication adverse events, infections, and chronic conditions.
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