Publication | Closed Access
Development and Validation of a Pediatric Comorbidity Index
81
Citations
46
References
2020
Year
Population Health SciencesLogistic AnalysisHospital MedicinePrimary CarePreventive PediatricsPediatric EpidemiologySocial HealthClinical EpidemiologyPublic HealthRetrospective Cohort StudyHealth Services ResearchPopulation ChildrenPsychiatryDisease Risk AssessmentRiskOutcomes ResearchEpidemiologyComorbidity ScoresHealth Care ReimbursementPatient SafetyPediatricsPediatric Comorbidity IndexPediatric PatientsTime-varying ConfoundingMedicineChild PsychiatryComorbidity
Comorbidity scores are widely used to help address confounding bias in nonrandomized studies conducted within health-care databases, but existing scores were developed to predict all-cause mortality in adults and might not be appropriate for use in pediatric studies. We developed and validated a pediatric comorbidity index, using health-care utilization data from the tenth revision of the International Classification of Diseases. Within the MarketScan database of US commercial claims data, pediatric patients (aged ≤18 years) continuously enrolled between October 1, 2015, and September 30, 2017, were identified. Logistic regression was used to predict the 1-year risk of hospitalization based on 27 predefined conditions and empirically identified conditions derived from the most prevalent diagnoses among patients with the outcome. A single numerical index was created by assigning weights to each condition based on its β coefficient. We conducted internal validation of the index and compared its performance with existing adult scores. The pediatric comorbidity index consisted of 24 conditions and achieved a C statistic of 0.718 (95% confidence interval (CI): 0.714, 0.723). The index outperformed existing adult scores in a pediatric population (C statistics ranging from 0.522 to 0.640). The pediatric comorbidity index provides a summary measure of disease burden and can be used for risk adjustment in epidemiologic studies of pediatric patients.
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