PURPOSE: To assess the impact of geographic health services factors on the timely diagnosis of autism. METHODS: Children residing in central North Carolina were identified by records-based surveillance as meeting a standardized case definition for autism. Individual-level geographic access to health services was measured by the density of providers likely to diagnose autism, distance to early intervention service agencies and medical schools, and residence within a Health Professional Shortage Area. We compared the presence of an autism diagnosis by age 8 and timing of first diagnosis across level of accessibility, using Poisson regression and Cox proportional hazards regression and adjusting for family and neighborhood characteristics. RESULTS: Of 206 identified cases, 23% had no previous documented diagnosis of autism. Most adjusted estimates had confidence limits including the null. Point estimates across analyses suggested that younger age at diagnosis was found for areas with many neurologists and psychiatrists and proximal to a medical school but not areas with many primary care physicians or proximal to early intervention services agencies. CONCLUSIONS: Further study of the distribution of medical specialists diagnosing autism may suggest interventions to promote the early diagnosis, and initiation of targeted services, for children with autism spectrum disorders.
PURPOSE: To assess the impact of geographic health services factors on the timely diagnosis of autism. METHODS:Children residing in central North Carolina were identified by records-based surveillance as meeting a standardized case definition for autism. Individual-level geographic access to health services was measured by the density of providers likely to diagnose autism, distance to early intervention service agencies and medical schools, and residence within a Health Professional Shortage Area. We compared the presence of an autism diagnosis by age 8 and timing of first diagnosis across level of accessibility, using Poisson regression and Cox proportional hazards regression and adjusting for family and neighborhood characteristics. RESULTS: Of 206 identified cases, 23% had no previous documented diagnosis of autism. Most adjusted estimates had confidence limits including the null. Point estimates across analyses suggested that younger age at diagnosis was found for areas with many neurologists and psychiatrists and proximal to a medical school but not areas with many primary care physicians or proximal to early intervention services agencies. CONCLUSIONS: Further study of the distribution of medical specialists diagnosing autism may suggest interventions to promote the early diagnosis, and initiation of targeted services, for children with autism spectrum disorders.
Authors: P A Filipek; P J Accardo; S Ashwal; G T Baranek; E H Cook; G Dawson; B Gordon; J S Gravel; C P Johnson; R J Kallen; S E Levy; N J Minshew; S Ozonoff; B M Prizant; I Rapin; S J Rogers; W L Stone; S W Teplin; R F Tuchman; F R Volkmar Journal: Neurology Date: 2000-08-22 Impact factor: 9.910
Authors: Kevin Y Urayama; Julie Von Behren; Peggy Reynolds; Andrew Hertz; Monique Does; Patricia A Buffler Journal: Ann Epidemiol Date: 2009-04-11 Impact factor: 3.797
Authors: Ryan K McBain; Vishnupriya Kareddy; Jonathan H Cantor; Bradley D Stein; Hao Yu Journal: J Am Acad Child Adolesc Psychiatry Date: 2019-05-29 Impact factor: 8.829
Authors: Marlene B Lauritsen; Aske Astrup; Carsten Bøcker Pedersen; Carsten Obel; Diana E Schendel; Laura Schieve; Marshalyn Yeargin-Allsopp; Erik T Parner Journal: J Autism Dev Disord Date: 2014-02
Authors: Kate Hoffman; Marc G Weisskopf; Andrea L Roberts; Raanan Raz; Jaime E Hart; Kristen Lyall; Elin M Hoffman; Francine Laden; Verónica M Vieira Journal: Am J Epidemiol Date: 2017-10-01 Impact factor: 4.897
Authors: Maureen S Durkin; Matthew J Maenner; Jon Baio; Deborah Christensen; Julie Daniels; Robert Fitzgerald; Pamela Imm; Li-Ching Lee; Laura A Schieve; Kim Van Naarden Braun; Martha S Wingate; Marshalyn Yeargin-Allsopp Journal: Am J Public Health Date: 2017-09-21 Impact factor: 9.308