Development and Validation of a Pediatric Comorbidity Index

Am J Epidemiol. 2021 May 4;190(5):918-927. doi: 10.1093/aje/kwaa244.


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.

Keywords: claims data; comorbidity; confounding; health services research; pediatrics; pharmacoepidemiology; risk adjustment.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adolescent
  • Child
  • Child, Hospitalized / statistics & numerical data
  • Child, Preschool
  • Comorbidity*
  • Confounding Factors, Epidemiologic
  • Databases, Factual
  • Epidemiologic Research Design
  • Female
  • Humans
  • Infant
  • Infant, Newborn
  • Male
  • Models, Statistical
  • Predictive Value of Tests
  • United States / epidemiology