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Children diagnosed with autism spectrum disorder (ASD) are as varied as those who are diagnosed with it. As Dr. Stephen Shore, a prominent advocate for autism research puts it, “If you’ve met one person with autism, you’ve met one person with autism.” Therefore, intervention programs must be highly individualized to be effective, and that can be very expensive. It is estimated that the costs associated with ASD will be in excess of $2 million over a individual’s life. However, studies have shown that the costs of lifetime care for a child diagnosed with ASD can be reduced by 2/3 with early intervention.
Designing an appropriate program, and then monitoring its efficacy, requires the collection of a range of data. Treatment providers often collect detailed data while working with an individual diagnosed with ASD, but they count on parents and caregivers to provide them with data regarding the individual’s progress outside the clinical setting. The data submitted is usually incomplete and inadequate (if it’s submitted at all). This is understandable: the arduous work of caring for a child diagnosed with ASD fully taxes the resources of most parents, leaving little time or energy for logging data about their child. The result is that the data ASD providers are able to analyze contains a large blind spot. Many ASD treatment providers refer to this as the “Achilles’ heel” problem they face when trying to develop and deliver an optimal program for an individual with ASD.
The SpinRise Autism Journal application allows parents to easily submit data about their children using methods they’re already familiar with: text messages and voice. For example, if their child is having a meltdown, the parent can send a text message to the SpinRise service. They can add tags, photos, or videos if applicable. The combined data is stored, encrypted, in a secure database. Proprietary machine learning algorithms first preprocess each individual data stream, and then analyze the merged streams as a whole. ASD treatment providers and parents can access the analysis, as well as the raw data, via a web-based, HIPAA- compliant portal, where it can be further analyzed, compiled into reports, and exported in standardized formats.
