Development and validation of a method to identify children with social complexity risk factors Journal Article uri icon
  • OBJECTIVES: We sought to develop and validate a method to identify social complexity risk factors (eg, limited English proficiency) using Minnesota state administrative data. A secondary objective was to examine the relationship between social complexity and caregiver-reported need for care coordination. METHODS: A total of 460 caregivers of children with noncomplex chronic conditions enrolled in a Minnesota public health care program were surveyed and administrative data on these caregivers and children were obtained. We validated the administrative measures by examining their concordance with caregiver-reported indicators of social complexity risk factors using tetrachoric correlations. Logistic regression analyses subsequently assessed the association between social complexity risk factors identified using Minnesota's state administrative data and caregiver-reported need for care coordination, adjusting for child demographics. RESULTS: Concordance between administrative and caregiver-reported data was moderate to high (correlation range 0.31-0.94, all P values <.01), with only current homelessness (r = -0.01, P = .95) failing to align significantly between the data sources. The presence of any social complexity risk factor was significantly associated with need for care coordination before (unadjusted odds ratio = 1.65; 95% confidence interval, 1.07-2.53) but not after adjusting for child demographic factors (adjusted odds ratio = 1.53; 95% confidence interval, 0.98-2.37). CONCLUSIONS: Social complexity risk factors may be accurately obtained from state administrative data. The presence of these risk factors may heighten a family's need for care coordination and/or other services for children with chronic illness, even those not considered medically complex.

  • Link to Article
    publication date
  • 2016
  • published in
  • Pediatrics  Journal
  • Research
  • Caregivers
  • Chronic Disease
  • Data Systems
  • Health Status
  • Pediatrics
  • Risk Factors
  • Additional Document Info
  • 138
  • issue
  • 3