Objective: Children with autism spectrum disorders (ASDs) often have co-occurring conditions, but little is known on the effect of those conditions on their medical care cost. Medical expenditures attributable to ASDs among Medicaid-enrolled children were calculated, and the effects of 3 commonly co-occurring conditions--intellectual disability (ID), attention deficit/hyperactivity disorder (ADHD), and epilepsy-on those expenditures were analyzed.
Methods: Using MarketScan Medicaid Multi-State Databases (2003-2005) and the International Classification of Disease, Ninth Revision, children with ASD were identified. Children without ASD formed the comparison group. The 3 co-occurring conditions were identified among both the ASD and the comparison groups. Annual mean, median, and 95th percentile of total expenditures were calculated for children with ASD and the co-occurring conditions and compared with those of children without ASD. Multivariate analyses established the influence of each of those co-occurring conditions on the average expenditures for children with and without ASD.
Results: In 2005, 47% of children with ASD had at least 1 selected co-occurring condition; attention deficit/hyperactivity disorder was the most common, at 30%. The mean medical expenditures for children with ASD were 6 times higher than those of the comparison group. Children with ASD and ID incurred expenditures 2.7 times higher than did children with ASD and no co-occurring condition.
Conclusion: Medicaid-enrolled children with ASD incurred higher medical costs than did Medicaid-enrolled children without ASD. Among Medicaid-enrolled children with ASD, cost varied substantially based on the presence of another neurodevelopmental disorder. In particular, children with ID had much higher costs than did other children with ASD.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/DBP.0b013e31823969de | DOI Listing |
Res Child Adolesc Psychopathol
January 2025
Nutrition and Mental Health Research Group (NUTRISAM), Universitat Rovira I Virgili (URV), Carretera de Valls, S/N, 43007, Tarragona, Spain.
The aim of this study is to investigate the impact of using probiotics with strains related to dopamine and gamma-aminobutyric acid production on clinical features of autism spectrum disorder (ASD) and/or attention deficit/hyperactivity disorder (ADHD). This randomized, controlled trial involved 38 children with ADHD and 42 children with ASD, aged 5-16 years, who received probiotics (Lactiplantibacillus plantarum and Levilactobacillus brevis 109/cfu/daily) or placebo for 12 weeks. Parent-reported symptoms were assessed using Conners' 3rd-Ed and the Social Responsiveness Scale Test, 2nd-Ed (SRS-2), and children completed the Conners Continuous Performance Test, 3rd-Ed (CPT 3) or Conners Kiddie CPT, 2nd-Ed (K-CPT 2).
View Article and Find Full Text PDFBrain Struct Funct
January 2025
Applied Psychology, Faculty of Education, University of Western Ontario, 1137 Western Rd, London, ON, N6G 1G7, Canada.
Children and adolescents with neurodevelopmental disorders such as autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) may be more susceptible to early life stress compared to their neurotypical peers. This increased susceptibility may be linked to regionally-specific changes in the striatum and amygdala, brain regions sensitive to stress and critical for shaping maladaptive behavioural responses. This study examined early life stress and its impact on striatal and amygdala development in 62 children and adolescents (35 males, mean age = 10.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Computer Science Department, Yarmouk University, Irbid 21163, Jordan.
One of the key challenges in autism is early diagnosis. Early diagnosis leads to early interventions that improve the condition and not worsen autism in the future. Currently, autism diagnoses are based on monitoring by a doctor or specialist after the child reaches a certain age exceeding three years after the parents observe the child's abnormal behavior.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
Autism spectrum disorder (ASD) is a group of developmental disorders characterized by poor social skills, low motivation in activities, and a lack of interaction with others. Traditional intervention approaches typically require support under the direct supervision of well-trained professionals. However, teaching and training programs for children with ASD can also be enhanced by assistive technologies, artificial intelligence, and robotics.
View Article and Find Full Text PDFPsychiatry Res
January 2025
Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510630, China. Electronic address:
Background: Early screening for autism spectrum disorder (ASD) is crucial, yet current assessment tools in Chinese primary child care are limited in efficacy.
Objective: This study aims to employ machine learning algorithms to identify key indicators from the 20-item Modified Checklist for Autism in Toddlers, revised (M-CHAT-R) combining with ASD-related sociodemographic and environmental factors, to distinguish ASD from typically developing children.
Methods: Data from our prior validation study of the Chinese M-CHAT-R (August 2016-March 2017, n = 6,049 toddlers) were reviewed.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!