Using Voice AI to Improve Behavioral Health Care for Disadvantaged Youth
Only 20% of behavioral health providers use measurement-based care [MBC].1 Two reasons for MBC’s low uptake outcomes are a need for stronger consensus regarding optimal use (in both frequency and consistency) and the absence of a widely utilized data analytics infrastructure. TQIntelligence has built and implemented a measurement-based system for community behavioral health providers, which includes the use of a novel AI-enabled voice algorithm designed to provide psychiatric decision and triaging support to pediatric populations. The success of the implementation and related outcomes varied depending on the organization and the therapist's involvement in the pilot.2 This paper will contribute to the literature on measurement care and its effectiveness. It also challenges the dominant narrative that such systems are too complicated and ineffective in community behavioral health that serve children and adolescents from low-income communities.
