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Multimodal Study Using Geospatial Mapping and Survey Analysis to Determine Disparities in Access to Care for Children with ASD

TitleMultimodal Study Using Geospatial Mapping and Survey Analysis to Determine Disparities in Access to Care for Children with ASD
Publication TypeConference Abstract
Year of Publication2017
AuthorsShoff, CR, Gehricke, J, Gott, RM, Dillon, M, Fox, C
Conference NameIMFAR
Abstract

Background
Among individuals with Autism Spectrum Disorders (ASD), disparities in access to healthcare have been linked to low socioeconomic status, racial and ethnic minorities, and residence in rural and under-resourced areas. However, little is known about the specific barriers individuals with ASD face in accessing care and the impact of specific geographic locations. The Autism Treatment Network (ATN) is a multisite network of 14 North American academic medical centers that specialize in the diagnosis and treatment of individuals with ASD. The purpose of this multimodal study was to examine how social determinants of health impact access to care across ATN sites.

Objectives
The main goals of the study were to (1) identify underserved individuals in ATN sites’ geographically defined catchment areas and determine whether or not they are receiving care at the site (2) identify how each ATN site is meeting the needs of underserved populations, and (3) highlight areas where sites need to increase outreach to individuals.

Methods
The multimodal study included a site-level survey with clinicians and a more detailed catchment area and service area analysis. The 34 items site level survey assessed the local, clinical, and patient characteristics of each of the 14 ATN sites to identify underserved populations and barriers to healthcare delivery. Building on part one, the second part of the study used geospatial mapping software (ArcGIS), to analyze whether sites are serving individuals at risk for not accessing healthcare services within their hospital’s defined catchment area. U.S. Census data and Area Deprivation Index (ADI) scores were used to identify zip codes with underserved individuals. After analyzing the data from 12 ATN sites we identified the percentage of high needs individuals within the catchment area and within the service area.

Results
Several barriers to reaching/serving the underserved in ATN communities were identified via the survey. The most frequently cited perceived barriers to reaching/serving the underserved included socio-economic status (42.9%), geographical distance (42%), caregivers’ education (35.7) and knowledge (28.5%), as well as transportation limitations (28.5%). Across all ATN sites, the percentage of individuals with an Area Deprivation Index greater than 100 (considered high-needs) in the hospital’s defined catchment areas (geographic area where patient population are drawn) was 55.6% and service areas (actual patients who access ATN centers) are 44.5%. The difference between the percentages of high needs individuals in the catchment area and those in the service area ranged from 3.4% to 118.9%. Some sites serve a greater percentage of high needs individuals than those in their catchment area, while other sites are not reaching a large proportion of high-needs individuals.

Conclusions
The survey revealed considerable variability among ATN sites in the demographic characteristics of patients and barriers to accessing care. Geospatial mapping using zip codes is an objective way for autism centers to identify geographical areas where they need to outreach to high needs patients. The catchment and service area analysis revealed areas where ATN sites could focus outreach efforts.