Online system for identifying and addressing teen depression in primary care
Online system for identifying and addressing teen depression in primary care
批准号:
10019727
负责人:
Barbara Jo Howard
金额:
$50.29万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-01 至 2023-06-30
关键词:
17 year oldAbnormal coordinationAddressAdolescentAffectAgreementAlgorithmsAppointmentAreaArtificial IntelligenceCaringChildChild PsychiatryChildhoodClinicalComputersConsensusDataData CollectionDepression and SuicideDepression screenDevelopmentEvidence based treatmentFamilyFeedbackFeelingFocus GroupsGoalsGuidelinesHealthHealth ProfessionalHealthcareIndividualInformation SystemsInterventionIntervention TrialInterviewKnowledgeMeasuresMental DepressionMental HealthModalityMoodsOffice VisitsOnline SystemsParentsPatientsPhasePrimary Health CareProcessPsychiatristPublic HealthQiQualitative ResearchQuestionnairesRandomizedRecommendationResourcesRiskSpecialistSpecialty BoardsStructureSupervisionSupport SystemSurveysSystemTeenagersTestingTexasTextTimeTrainingVisitYouthadolescent healthbarrier to carebasebehavioral healthcare coordinationcare providerschatbotcheckup examinationchild depressioncontrol trialdepressive symptomsfollow-upfunctional disabilityimplementation strategyinnovationmotivational enhancement therapyprogramsrecruitsatisfactionscreeningshared decision makingsingle episode major depressive disorderskillssuccesssuicidal risktoolvolunteer
中文摘要
这项建议提出了解决青少年在例行体检期间抑郁的创新之处
通过进一步开发名为CHADIS的在线临床流程支持系统。这个
初级保健提供者仍然处于这一过程的中心,他/她之前与
家庭和人类在相遇前通过计算机辅助以及
护理时刻提醒和电话提示特定提示,旨在增强患者的注意力
平衡讨论青少年目标的个人优势和障碍,称为
励志访谈。通过访问前的数据收集提供
要突出的相关细节以及支持省略一些传统制导领域的数据
对于个人青少年来说优先级较低。来自PCP的任何结论
建议和共享决策由以计算机为基础的、始终
由人工智能引导的可用聊天机器人,作为通向其他帮助的桥梁
专业人士、优势建设资源,以及基于已证实的智力的对话
基于早期试点数据的健康疗法,以减少抑郁症状。这些
创新将通过整群随机对照试验进行测试,展示使用
该系统导致更高的筛查率,抑郁症状的减少,以及
青少年抑郁症循证治疗的途径。系统的使用通过以下方式得到加强
初级医生和儿童精神病学家参与相关的质量改进
利用他们参与的数据制定计划,为重新认证提供必要的反馈
各自专业委员会的专业地位要求。系统的成功
将意味着一个新的初级保健工作流程友好的工具,可以帮助青少年避免
伴随青少年抑郁而来的严重功能障碍和风险增加。如果这个
青少年健康监督的新范式被证明对抑郁症有用,适应
青少年面临的其他挑战可能也很有希望。
英文摘要
This proposal presents innovations to addressing teen depression during routine check-up visits
through further development of an online clinical process support system called CHADIS. The
primary care provider remains in the center of the process with his/her prior relationship with
the family and humanity enabled with computer assistance prior to the encounter as well as
moment of care reminders and teleprompted specific hints aimed at enhancing a patient focused
balanced discussion of individual strengths and barriers to the teens goals known as a
motivational interview. This is made feasible through pre-visit data collection providing
relevant details to highlight as well as data to support omitting some traditional guidance areas
with lower priority for the individual teen. Any conclusions coming from PCP
recommendations and shared decision making is reinforced by a computer-based, always
available chatbot guided by artificial intelligence that serves as a bridge to other helping
professionals, strengths building resources, as well as conversations based on proven mental
health therapies based on earlier pilot data for reducing depressive symptoms. These
innovations will be tested via a cluster randomized control trial, demonstrating whether use of
the system results in higher rates of screening, reductions in depressive symptoms, and
accessing of evidence-based treatment for teen depression. Use of the system is reinforced by
engagement of primary doctors and child psychiatrists in a related quality improvement
program with data from their participation providing needed feedback for recertification of
professional status requirements of their respective specialty boards. Success of the system
would mean a new primary care workflow-friendly tool which could help adolescents avoid the
significant functional impairment and increased risks that accompany teen depression. If this
new paradigm for adolescent health supervision proves useful for depression, adaptations for
other teen challenges might also be promising.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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