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Challenge
Seeing an increased demand for and rapid expansion of ABA therapy, SpectrumAi realized the old EHR tools weren’t keeping up.
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Solution
Improve the quality and transparency of ABA Therapy with modern clinical tools powered by objective, quantifiable data.
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Results
A new ABA clinical session management tool, Twyll, that simplifies data capture, automates documentation, and records sessions.
Modernizing ABA Therapy. SpectrumAi's goal is to change the field of Applied Behavioral Analysis (ABA). With the expansion of insurance coverage for ABA therapy and a resulting rise in demand, SpectrumAi saw a pressing need to develop a better, more modern ABA electronic health record (EHR). Together, we developed Twyll, a tool that increases transparency for families and improves quality of care by capturing objective, quantifiable data.
Areas of Expertise
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A Best-In-Class Experience
ABA clinicians have two goals during sessions: to provide high quality therapy and to collect real-time data to track progress over time. Balancing these goals can be a challenge, so our teams thoughtfully designed Twyll to make data capture and note taking incredibly simple. By optimizing the user interface for tablets, creating custom buttons to efficiently document the intensity and type of client behavior, and providing the option to flag a moment for later review; Twyll incentivizes real-time capture of clinical data without sacrificing focus on the client.
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One Supervisor, Many Clinicians
ABA therapy clinician feedback and training has historically been limited to sessions a supervisor can attend in-person. To address this problem, Viget and SpectrumAi developed novel oversight tools that provide live video and data, allowing supervisors to attend sessions remotely. Twyll records video of these sessions, tags and notates behaviors, and then syncs that data to the video timeline, making the process of identifying and reviewing key interactions simple and efficient. This capability not only increases a supervisor's ability to provide valuable feedback and training to clinicians asynchronously, but also brings increased transparency to sessions for families and payors.
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All The Data, Half The Time
Clinicians and supervisors spend a lot of time creating post-session documentation for insurance providers. Existing tools are often too cumbersome to use in-session, leading to hours of uncompensated time spent capturing notes that are based on a clinician’s best recollection of what happened. Twyll was developed to pull together in-session data, comments, and insights to automatically generate a SOAP note (a widely used method of healthcare documentation). This process not only saves clinicians time, but also provides payors and families with documentation backed by objective, timely data.
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Automating Improvement
With all the work that goes into implementing and documenting ABA therapy, there’s not much time left over to focus on improving care. Twyll provides data-driven analysis, real-time metrics, and interactive charts to help supervisors flag anomalies, provide timely support to clinicians, and efficiently monitor curriculum implementation. Twyll even allows supervisors to create rules-based curriculum automations and alerts, update goals, track outcomes, and phase out old programs, all based on recent in-session progress data.
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$20m
SpectrumAi has gone on to raise $20 million during their Series A funding.
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Disrupting an Industry
After partnering with Viget to develop this powerful, easy to use tool, SpectrumAi has gone on to raise $20 million during their Series A funding. By creating a tool that allows for objective and timely data collection, SpectrumAi is positioned to help the industry move towards the kind of data-backed, value-based care that supports clients in reaching their optimal outcomes.
Summary
With a rise in demand for ABA therapy, SpectrumAi saw a pressing need to develop a modern ABA Clinical Session Management tool. Together we developed Twyll, a tool that increases transparency for families and payors, while improving quality by capturing objective, quantifiable data.
