Prevalence and patterns of medical co-morbidity and healthcare use before ASD diagnoses in children
Comprehensive electronic medical record data for a large, racially and ethnically diverse population of children born within the Kaiser Permanente (KP) Medical Care Program between 2000 and 2009 and who stayed members until at least age two will be collected from KP Northern California, Georgia, and the Northwest. Medical co-morbidities and health care utilization patterns experienced by children in these populations, who were diagnosed with an Autism Spectrum Disorder (ASD), will be compared with a non-ASD control population. The co-morbidities to be examined will include immune-related conditions (perinatal and pediatric infections, allergy, asthma, auto-immune conditions, and adverse reactions to vaccination), gastrointestinal symptoms, sleep problems, seizures, and other neurologic conditions, and metabolic disorders. Health care utilization patterns will include number of outpatient clinic visits (primary care, medical specialist, emergency care), vaccination history, and hospitalizations. The prevalence of co-morbidities and health care utilization in ASD cases and non-ASD controls will be described. In addition, longitudinal analyses to examine the period before ASD diagnosis will be conducted to determine if particular temporal patterns or health trajectories are associated with subsequent diagnosis with an ASD. Finally, the research team will examine if there is a temporal pattern in the occurrence or exacerbation of medical co-morbidities associated with regular childhood vaccinations, and whether this pattern is different for children with ASD compared to the non-ASD comparison group. Results from this study will help to fill important knowledge gaps in the understanding of the prevalence of medical co-morbidities and associated patterns of health care service utilization among this vulnerable population. This study may also identify certain health trajectories or co-morbidity patterns that are associated with later ASD diagnosis. That information could be used to improve the early identification of children at risk for ASD, thus maximizing the potential benefit of early intervention services on child development.