SBIR/STTR Research Award
Substance Use Disorder Artificially Intelligent chatbot for screening, assessment and referral: SUD Bot
Award amount
$300,526Program and phase
STTR · Phase IAward year
2023Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- Clinic Chat LLC
- Proposal award date
- 2023-08-15
- Contract end date
- 2024-08-14
- UEI
- YRSMD9OS6MK7
- Solicitation number
- PA22-178
- Topic code
- NIDA
Research abstract
ABSTRACT
The opioid epidemic is considered one of the most severe public health crises we are facing in
the U.S. and is worsened by use of stimulants such as methamphetamine. The US Preventive
Services Task Force (USPSTF) recommends screening for unhealthy drug use accompanied by
offers of and referrals to services that include accurate diagnosis, effective treatment and
appropriate care of a substance use disorder (SUD) for persons aged 18 and older. Automating
screening and assessment for SUD and removing stigmas and other barriers to treatment can
improve the scale, efficiency, and equitable access to SUD care. While artificial intelligence (AI)
chatbots using natural language processing (NLP) and Machine Learning (ML) are increasingly
common, they (a) fall short of systems that mimic social conversations with persuasive
responses to motivate action (b) are not interoperable with service delivery to link users
immediately with clinic appointments and (c) aren’t FDA approved under mandates to regulate
medical devices that complete assessments for medical outcomes. Specific to SUD, there is a
compelling need for AI chatbots that minimize stigma associated with SUD care and resources.
In this Phase I STTR, Clinic Chat, LLC, will build on prior research showing the success of their
chatbots to support improved access to chronic illness medication in partnership with Be Well
Texas, a provider of SUD services to develop and beta-test the feasibility, navigability, and
acceptability of using a next generation AI chatbot, called SUD Bot, to facilitate access to and
utilization of SUD services and resources. We aim to 1: Enhance existing Clinic Chat AI
Chatbots with (a) persuasive SUD screening and treatment messaging and (b) infrastructure
with capacity to simulate human conversation and be accessible in English and Spanish via
multiple platforms, i.e., text messaging, including voice and video; 2: Build fast healthcare
interoperative resource (FHIR) linkages that will allow users to self-schedule appointments
for treatment or to access peer support through the recovery network within Be Well Texas; and
3: Conduct a beta-test to determine the functionality and navigability of the FHIR-enabled
SUD Bot system. We will recruit 200 users to use the FHIR-enabled SUD Bot system in three
weeklong waves interspersed with iterative system refinement based on user feedback.
Completion of this Phase I study will generate an FHIR-enabled minimum viable product (MVP)
with initial functionality and navigability feedback ready for a Phase II STTR randomized clinical
trial testing system efficacy. Our goal is to have an effective and scalable tool that can be
adapted for use in any organization delivering SUD services and commercialized through fees
for service or Medicaid/Medicare reimbursement.
Technology keywords
Not reported
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Wearable Wireless Respiratory Monitoring System that Detects and Predicts Opioid Induced Respiratory Depression
- Building and testing the Life Enhancement and Advocacy Programming digital training tool (LEAPLink) to better serve people with lived experience of homelessness and substance use disorder
- A digital intervention to decrease self-stigma among pregnant and postpartum women with opioid use disorder
- Development of medication for the treatment of respiratory depression due to opioid (prescribed or illicit) overdose/multidrug (polysubstance) overdose in a hospital or community setting.
- Creation and Validation of the Dose-Opioid-Source Evaluation tool (DOSE) - a Robust Opioid Use Clinical Outcome Assessment for Qualification as an FDA Medical Device Development Tool (MDDT)