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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Dec 12, 2018
Open Peer Review Period: Dec 17, 2018 - Feb 11, 2019
Date Accepted: May 16, 2019
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Identification and Quantification of Gaps in Access to Autism Resources in the United States: An Infodemiological Study

Ning M, Daniels J, Schwartz J, Dunlap K, Washington P, Kalantarian H, Du M, Wall DP

Identification and Quantification of Gaps in Access to Autism Resources in the United States: An Infodemiological Study

J Med Internet Res 2019;21(7):e13094

DOI: 10.2196/13094

PMID: 31293243

PMCID: 6652124

Identification and Quantification of Gaps in Access to Autism Resources in the U.S.

  • Michael Ning; 
  • Jena Daniels; 
  • Jessey Schwartz; 
  • Kaitlyn Dunlap; 
  • Peter Washington; 
  • Haik Kalantarian; 
  • Michael Du; 
  • Dennis P Wall

ABSTRACT

Background:

1 in 59 children have autism. While similar rates of autism are reported in rural and urban areas, rural families report greater difficulty in accessing resources. An overwhelming number of families experience waitlists for diagnostic and therapeutic services.

Objective:

To accurately identify gaps in access to autism care using GapMap: a mobile platform that connects families with local resources while continuously collecting up-to-date autism resource epidemiology information.

Methods:

Resources were extracted from various resource databases. Resources were deduplicated, validated, and allocated into seven categories based on keywords identified on the resource website. The average distance between individuals from a simulated autism population and the nearest autism resource in our database was calculated for each U.S. county. Resource load, an approximation of demand over supply for diagnostic resources, was calculated for each U.S. county.

Results:

There are approximately 28,000 U.S. resources validated on the GapMap database, each allocated into one or more of seven categories. States with the greatest distances to autism resources include Alaska, Nevada, Wyoming, Montana, and Arizona. Of the seven resource categories, diagnostic resources are the most underrepresented, comprising only 8.83% of all resources. Alarmingly, 83.86% of all U.S. counties lack any diagnostic resource. States with the highest diagnostic resource load include West Virginia, Kentucky, Maine, Mississippi, and New Mexico.

Conclusions:

Results from this study demonstrate the sparsity and uneven distribution of diagnostic resources in the U.S., which may contribute to the lengthy waitlists and travel distances often necessary to receive diagnosis in specific regions. More data is needed on autism diagnosis demand to better quantify resource needs across the U.S.


 Citation

Please cite as:

Ning M, Daniels J, Schwartz J, Dunlap K, Washington P, Kalantarian H, Du M, Wall DP

Identification and Quantification of Gaps in Access to Autism Resources in the United States: An Infodemiological Study

J Med Internet Res 2019;21(7):e13094

DOI: 10.2196/13094

PMID: 31293243

PMCID: 6652124

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.