OBJECTIVE: To compare a diagnosis list to the Questionnaire for Identifying Children with Chronic Conditions (QuICCC) to assess their relative usefulness as measures for identifying children with chronic conditions. METHODS: Comparison of health encounter data and survey data for a cohort of 304 children aged 0-18 years at an urban health center affiliated with a teaching hospital. We used 2 strategies to identify children with a chronic condition: 1) identification by the existence of an encounter with an International Classification of Diseases, Ninth Revision code indicating a chronic condition and 2) identification by the QuICCC. We compared the characteristics of children identified by the diagnosis list with those of children identified by the QuICCC. RESULTS: This population had high rates of chronic conditions, with 44% identified by the diagnosis list and 36% identified by the QuICCC. These 2 methods jointly identified 66% of children, yet only half (53%) of the children who had a diagnosis of a chronic condition in the encounter data were identified by the QuICCC. Asthma, anorexia, developmental delay, and adjustment reaction were among the common chronic conditions for children identified by the diagnosis list approach only. CONCLUSIONS: We found only moderate concordance among the children identified as having chronic conditions by a diagnosis list and by the QuICCC in this high-risk urban population. These different results indicate that encounter data and survey approaches do not serve as simple substitutes for identifying children with chronic conditions for clinical or monitoring purposes.
OBJECTIVE: To compare a diagnosis list to the Questionnaire for Identifying Children with Chronic Conditions (QuICCC) to assess their relative usefulness as measures for identifying children with chronic conditions. METHODS: Comparison of health encounter data and survey data for a cohort of 304 children aged 0-18 years at an urban health center affiliated with a teaching hospital. We used 2 strategies to identify children with a chronic condition: 1) identification by the existence of an encounter with an International Classification of Diseases, Ninth Revision code indicating a chronic condition and 2) identification by the QuICCC. We compared the characteristics of children identified by the diagnosis list with those of children identified by the QuICCC. RESULTS: This population had high rates of chronic conditions, with 44% identified by the diagnosis list and 36% identified by the QuICCC. These 2 methods jointly identified 66% of children, yet only half (53%) of the children who had a diagnosis of a chronic condition in the encounter data were identified by the QuICCC. Asthma, anorexia, developmental delay, and adjustment reaction were among the common chronic conditions for children identified by the diagnosis list approach only. CONCLUSIONS: We found only moderate concordance among the children identified as having chronic conditions by a diagnosis list and by the QuICCC in this high-risk urban population. These different results indicate that encounter data and survey approaches do not serve as simple substitutes for identifying children with chronic conditions for clinical or monitoring purposes.
Authors: Tamara D Simon; Mary Lawrence Cawthon; Susan Stanford; Jean Popalisky; Dorothy Lyons; Peter Woodcox; Margaret Hood; Alex Y Chen; Rita Mangione-Smith Journal: Pediatrics Date: 2014-05-12 Impact factor: 7.124
Authors: Paul J Chung; Craig F Garfield; Marc N Elliott; Katherine D Vestal; David J Klein; Mark A Schuster Journal: Acad Pediatr Date: 2013-03-09 Impact factor: 3.107
Authors: Alyna T Chien; Zirui Song; Michael E Chernew; Bruce E Landon; Barbara J McNeil; Dana G Safran; Mark A Schuster Journal: Pediatrics Date: 2013-12-23 Impact factor: 7.124
Authors: Mark A Schuster; Paul J Chung; Marc N Elliott; Craig F Garfield; Katherine D Vestal; David J Klein Journal: JAMA Date: 2008-09-03 Impact factor: 56.272