Heterogeneity in Autism Spectrum Disorder Case-Finding Algorithms in United States Health Administrative Database Analyses

Details

• Alternative Title:
  J Autism Dev Disord
• Personal Author:
  Grosse, Scott D. ; Nichols, Phyllis ; Nyarko, Kwame ; Maenner, Matthew ; Danielson, Melissa L. ; Shea, Lindsay
• Description:
  Strengthening systems of care to meet the needs of individuals with autism spectrum disorder (ASD) is of growing importance. Administrative data provide advantages for research and planning purposes, including large sample sizes and the ability to identify enrollment in insurance coverage and service utilization of individuals with ASD. Researchers have employed varying strategies to identify individuals with ASD in administrative data. Differences in these strategies can limit the comparability of results across studies. This review describes implications of the varying strategies that have been employed to identify individuals with ASD in US claims databases, with consideration of the strengths and limitations of each approach.
• Subjects:
  Algorithms Autism Spectrum Disorder Databases, Factual Humans Insurance Coverage United States
• Keywords:
  Autism Spectrum Disorder Case-finding Algorithms Claims Data Health Services Research
• Source:
  J Autism Dev Disord. 52(9):4150-4163
• Pubmed ID:
  34581918
• Pubmed Central ID:
  PMC9077262
• Document Type:
  Journal Article
• Funding:
  CC999999/ImCDC/Intramural CDC HHSUnited States/
• Volume:
  52
• Issue:
  9
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:71bb27fa298bd138bab10033989dadbf9338ee23920bb281c46c0dcc1bf456e5fe7a2deccdf866ebf8b847bb79afa2fb89a5eef233eb838f4bcba25e9129b016
• Download URL:
  https://stacks.cdc.gov/view/cdc/117076/cdc_117076_DS1.pdf
• File Type:
  [PDF - 368.87 KB ]