Substance Use Disorder Artificially Intelligent chatbot for screening, assessment & referral: SUD Bot
Substance Use Disorder Artificially Intelligent chatbot for screening, assessment & referral: SUD Bot
批准号:
10757191
负责人:
SHEANA S BULL
金额:
$30.05万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-08-15 至 2024-08-14
关键词:
AddressAlgorithmsAppointmentAppointments and SchedulesArtificial IntelligenceArtificial Intelligence platformBehaviorBehavior TherapyBehavioralBody Weight decreasedCaringCessation of lifeChronic DiseaseClinicColoradoCommunicationCommunitiesDataDecision MakingDiagnosisDrug usageEducationElectronic Health RecordEquityEvolutionExpert SystemsFDA approvedFee-for-Service PlansFeedbackFundingGoalsGroup InterviewsHealthHealth SciencesHealth Services AccessibilityHealth behaviorHealthcareHumanImprove AccessInformation SystemsInfrastructureIntentionInternetInterventionInterviewLinkMachine LearningMeasuresMedicalMedical DeviceMedicare/MedicaidMethamphetamineNational Heart, Lung, and Blood InstituteNatural Language ProcessingOpioidOutcomeOverdosePatientsPersonsPharmaceutical PreparationsPhasePrivatizationProfessional counselorProviderPublic HealthRecording of previous eventsRecoveryReminder SystemsResearchResourcesScheduleScienceSecureServicesSmall Business Technology Transfer ResearchStimulantSubstance Use DisorderSystemTestingTexasText MessagingUnited States National Institutes of HealthUnited States Preventative Services Task ForceUniversitiesVoiceWorkaccurate diagnosisagedbarrier to carechatbotcocaine usecommercializationdata miningdesigneffective therapyfallsfeasibility testingfirewallfollow-uphealth assessmenthealth care deliveryhealth communicationhealth equityillicit drug useimprovedinnovationmachine learning modelmedication compliancemembermethamphetamine usemultiple drug usenew technologynext generationnovel therapeuticsopioid epidemicpeerpeer supportphase 1 studyrandomized, clinical trialsrecovery servicesrecruitresponsesatisfactionscreeningscreening guidelinesservice deliverysmoking cessationsocialsocial stigmastimulant usesuccesssupportive environmenttoolusability
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英文摘要
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.
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负责人:SHEANA S BULL
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依托单位:
海外基金