Heterogeneity in Autism Spectrum Disorder Case-Finding Algorithms in United States Health Administrative Database Analyses
- Resource Type
- Journal Articles
Reports - Descriptive
- Authors
- Grosse, Scott D. (ORCID 0000-0003-1078-6855); Nichols, Phyllis; Nyarko, Kwame; Maenner, Matthew; Danielson, Melissa L.; Shea, Lindsay
- Source
- Journal of Autism and Developmental Disorders. Sep 2022 52(9):4150-4163.
- Subject
- Autism
Pervasive Developmental Disorders
Data Use
Databases
Health Services
Identification
- Language
- English
- ISSN
- 0162-3257
1573-3432
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.