Ling Shao’s 3-year-old autistic son has trouble communicating. “My youngest son, he almost has a calcified part of his forehead because he bangs it so hard on the floor because he’s frustrated and he can’t communicate what he wants,” she says. “It’s heartbreaking.”
Shao, a mother of four with an autism spectrum disorder, is a health industry veteran. She has held leadership positions at insurer UnitedHealth, healthcare giant Optum and digital healthcare startup Buoy Health. But she became increasingly frustrated with what she sees as some of the biggest barriers to more widely accessible autism care: a lack of data transparency that makes defining and thus seeking proven quality care difficult for parents.
Shao was launched last year SpectrumAi to address some of these fundamental flaws in autism care, using a software platform and artificial intelligence to capture data on autism treatments for a future where caregivers are paid for the value they bring rather than the greatest part of the services they provide, and encourage best practices.
Company announced a $9 million funding round in early June led by F-Prime Capital and Frist Cressey Ventures, alongside investments from the Autism Impact Fund. Its mission, in short, is to bring transparency to the notoriously opaque and poorly measured practice of applied behavioral analysis (ABA), a form of autism therapy.
About 1 in 44 American children have autism spectrum disorder, according to the Centers for Disease Control and Prevention, and ABA is by far the longest-standing and most commonly used form of autism therapy, with multiple studies showing its promise in children. Types of ABA can include positive reinforcement, in which a patient earns rewards for achieving certain communication goals or correctly answering questions from their therapist. Therapies can include things like communication between pictures, where a patient can start asking for an object by exchanging a picture of it for the real thing, and eventually work their way up to verbally asking for the object.
These are extremely valuable resources for people with autism spectrum disorder, especially children who are lagging behind in their communication skills. But therapy providers who misapply ABA can actively harm and reinforce negative behaviors, Shao says. And a fundamental flaw in the U.S. health system, where behavioral and mental health often make short work, is that there are “no universally accepted objective data standards to evaluate outcomes and improve the quality of care,” she says.
Some parents may struggle to find an effective ABA care provider because the data simply does not exist in a convenient form. SpectrumAi wants to bring more clarity about what works and deliver better treatment results by measuring this empirically via a digital platform. Rather than scribbling largely unquantifiable and subjective notes on paper that interrupt the flow of ABA therapy, requiring deep therapist involvement, SpectrumAi’s software helps automate the data collection process and provides a publicly accessible information hub that Therapists also can help focus on the most effective ABA techniques for different patient groups. Shao did not disclose SpectrumAi’s specific customers, but said they are major players in the US health insurance and ABA provider sectors.
The purpose of the SpectrumAi software is twofold: to give insurers an easier way to find out exactly what kind of treatment goals and ABA techniques are used in sessions (the behavioral health equivalent of seeing if an MRI and blood test were taken during a hospital visit), and give ABA therapists an interface that makes it much easier to record the types of techniques they’ve used during a session.
“We’ve given these great providers a unicycle, and in the meantime they should get a self-driving car that really helps them rather than prevents them from doing their job better,” Shao says.
As SpectrumAi analyzes the treatments and outcomes, Shao hopes to share best practices with ABA therapists to help identify proven approaches to each child’s individual needs. “One of the other ways we think you can improve quality is actually shared learning, by taking that data and giving it back to the providers by saying, ‘Hey, this is what works better than other methods’ “says Shao. “Maybe this one works on this kid, and this other one works on this other kid, given their kind of assessments and their backgrounds and the challenges they might face.”
Sy Mukherjee has been reporting on healthcare for ten years. He is a consultant and communication architect at IDEA Pharma.