Maternal and child health journal · 2013
Do unmet needs differ geographically for children with special health care needs?
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Fulda Kimberly G, Johnson Katandria L, Hahn Kristen, Lykens Kristine
Аннотация
The purpose of this study was to identify geographic differences in health indicators for children with special health care needs (CSHCN). It was hypothesized that geographic differences in unmet health care needs exist among CSHCN by region in the United States. Data were obtained from the National Survey of Children with Special Health Care Needs, 2005-2006. Nine variables representing unmet needs were analyzed by geographic region. The region with the highest percent of unmet needs was identified for each service. Logistic regression was utilized to determine differences by region after controlling for age, gender, ethnicity, race, federal poverty level, relationship of responder to child, insurance status, severity of condition, and size of household. A total of 40,723 CSHCN were represented. Crude analysis demonstrated that the greatest unmet need for routine preventive care, specialist care, prescription medications, physical/occupational/speech therapy, mental health care, and genetic counseling occurred in the West. The greatest unmet need for preventive dental care, respite care, and vision care occurred in the South. Significant differences between regions remained for six of the nine services after controlling for potential confounders. Geographic differences in unmet health care needs exist for CSHCN. Further delving into these differences provides valuable information for program and policy planning and development. Meeting the needs of CSHCN is important to reduce cost burden and improve quality of life for the affected child and care providers.
Предметные рубрики MeSH
AdolescentChildChild Health ServicesChild, PreschoolDelivery of Health CareChildren with DisabilitiesFemaleHealth Care SurveysHealth Services AccessibilityHealth Services Needs and DemandHealth Status IndicatorsHealthcare DisparitiesHumansInsurance, HealthMaleRegression AnalysisSocioeconomic FactorsUnited StatesVulnerable Populations