SUDCare: A smart mobile tool to support substance use screening and follow-up care

SUDCare：支持物质使用筛查和后续护理的智能移动工具

• 批准号: 9897003
• 负责人: Y. Xian Ho
• 金额: $ 22.98万
• 依托单位: DIMAGI, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9897003
• 关键词: Address; Adult; Alcohol or Other Drugs use; Assessment tool; Blinded; Care given by nurses; Caring; Child; Clinic; Clinical; Consultations; Data; Data Analytics; Data Set; Development; Drug usage; Effectiveness; English Language; Enrollment; Ensure; Feedback; Goals; Guidelines; Health; Human; Insurance Carriers; Intelligence; Internet; Intervention Trial; Interview; Logistics; Machine Learning; Measures; Methods; Modeling; Natural Language Processing; Online Systems; Participant; Patient Care; Patient Monitoring; Patient risk; Patients; Perception; Performance; Phase; Pilot Projects; Population; Prevention; Primary Health Care; Protocols documentation; Provider; Public Health; Qualitative Methods; Research; Resources; Risk; Screening procedure; Self Administration; Series; Services; Small Business Innovation Research Grant; Specialist; Structure; Substance Use Disorder; System; Techniques; Technology; Testing; Text Messaging; Therapeutic; Training; Treatment Protocols; United States; United States Centers for Medicare and Medicaid Services; United States Dept. of Health and Human Services; Work; Workload; base; care providers; chatbot; commercialization; cost; design; disorder prevention; disorder risk; evidence base; experience; follow-up; handheld mobile device; high risk; innovation; mobile application; model design; multidisciplinary; novel; primary care setting; prototype; recruit; reduced substance use; referral services; satisfaction; screening; screening and brief intervention; screening, brief intervention, referral, and treatment; standard care; statistics; substance use prevention; tool; treatment program; trend; usability; user centered design; virtual

PROJECT SUMMARY Substance use disorder (SUD) is a significant public health challenge that costs the US over $740 billion annually and lacks the current workforce to address it. Our proposed innovation, SUDCare, is a novel and intelligent mobile application that will be designed to address the pressing needs of primary care patients who have inadequate resources and services for SUD screening and follow-up care. The core components of the proposed innovation will consist of a remote screening tool for the assessment of patients’ risk level of SUD and a chatbot to support logistical and routine queries. Our research team will utilize natural language processing (NLP) and machine learning techniques to create a scalable and sustainable solution to support an evidence-based SUD screening and treatment protocol. SUDCare has the potential to streamline follow-up clinic encounters and minimize the increasing workload burden placed on PCPs while filling a largely unfilled gap in care for hard-to- reach populations not directly served by any SUD therapeutic solutions available today. The goal of this SBIR Phase I project is to test technical merit, feasibility, and commercial potential of SUDCare. We will accomplish this goal using a user-centered design framework following three specific aims. In Aim 1, we will conduct semi- structured formative interviews with stakeholders (i.e., primary care providers, nurses, care coordinators, insurers, health IT specialists) and potential target end users (i.e., patients) (Substudy 1, N=20) recruited from our partnering primary care clinic. The data collected from this Substudy will be used to support the SUDCare development and requirements for integration with clinic workflow and systems. In Aim 2, we will build a working prototype of SUDCare. To create the chatbot prototype, we will train an English language model using a rich, existing de-identified dataset of text-message conversations from previous related work. Finally, in Aim 3, we will assess the acceptability of SUDCare through usability testing conducted with patients at risk of SUD (Substudy 2, N=8). Results from Phase I will inform a potential Phase II project to further develop SUDCare and conduct a larger-scaled pilot study to evaluate the efficiency and effectiveness of SUDCare.

项目总结 物质使用障碍(SUD)是一项重大的公共卫生挑战，每年给美国造成超过7400亿美元的损失 而且缺乏目前的劳动力来解决这个问题。我们提出的创新SUDCare是一种新颖而智能的 移动应用程序，旨在满足以下初级保健患者的迫切需求 没有足够的资源和服务用于严重急性呼吸综合征筛查和后续护理。建议的核心组成部分 创新将包括一个远程筛查工具，用于评估患者的SUD风险水平和一个聊天机器人 为后勤和例行查询提供支持。我们的研究团队将利用自然语言处理(NLP)和 机器学习技术可创建可扩展且可持续的解决方案，以支持基于证据的SUD 筛查和治疗方案。SUDCare有可能简化后续诊所会面，并 最大限度地减少儿科医生日益增加的工作负担，同时填补难以填补的护理缺口 覆盖目前没有得到任何SUD治疗解决方案直接服务的人群。这项SBIR的目标是 第一阶段的项目是测试SUDCare的技术优势、可行性和商业潜力。我们将完成 这一目标采用了以用户为中心的设计框架，遵循三个具体目标。在目标1中，我们将进行半 与利益相关者(即初级保健提供者、护士、护理协调员、 保险公司、医疗信息技术专家)和潜在目标最终用户(即患者)(子研究1，N=20) 我们的合作初级保健诊所。本子研究收集的数据将用于支持SUDCARE 与临床工作流程和系统集成的发展和要求。在目标2中，我们将构建一个有效的 SUDCARE的原型。为了创建聊天机器人原型，我们将使用丰富的、 来自以前相关工作的现有未识别的文本消息对话数据集。最后，在目标3中，我们 将通过对有SUD风险的患者进行可用性测试来评估SUDCare的可接受性 (分组研究2，N=8)。第一阶段的结果将为潜在的第二阶段项目提供信息，以进一步开发SUDCare和 开展一项更大规模的试点研究，以评估SUDCare的效率和效果。