What's Happening?
Ksana Health, a software company based in Eugene, Oregon, has been awarded a $17.9 million contract by the U.S. Department of Health and Human Services (HHS) to develop a Large Health Behavior Model (LHBM). This initiative aims to advance mental health
and substance use disorder treatment through artificial intelligence. The project will utilize data from smartphones and wearables, such as sleep patterns, mobility, and language use, linked to electronic health records (EHRs). The effort is part of the HHS's Advanced Research Projects Agency for Health’s (ARPA-H) EVIDENT initiative, which includes other participants like Duke University and the Johns Hopkins University School of Medicine. The project will begin with a proof-of-concept study and pilot data collection, eventually scaling to tens of thousands of participants across multiple health systems, including Providence and MedStar Health.
Why It's Important?
This project represents a significant step forward in integrating technology with healthcare, particularly in the realm of behavioral health. By leveraging AI and data from everyday devices, the initiative aims to shift behavioral healthcare from episodic assessments to continuous, data-driven health promotion. This could lead to reduced healthcare costs, improved quality of life, and better access to effective behavioral health support for underserved populations. The use of AI in this context could revolutionize how mental health conditions are monitored and treated, potentially leading to more personalized and proactive care models.
What's Next?
The project will proceed in phases, starting with initial studies and data collection. Recruitment for participants will begin this summer, with Providence and MedStar Health leading the efforts. Participants will use Ksana's app and engage in activities for three months, consenting to include their EHRs in the study. The University of Washington will spearhead the computational modeling work. As the project progresses, it will expand to include a larger participant base, aiming to validate and refine the AI models for broader application in behavioral health care.
