Data Science to Inform Coordinated Behavioral Health and HIV Care Re-Engagement

数据科学为协调行为健康和艾滋病毒护理重新参与提供信息

• 批准号: 10599453
• 负责人: Jane M. Simoni
• 金额: $ 28.62万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10599453
• 关键词: Age; Algorithms; Americas; Applications Grants; Area; Assertiveness; Behavior Therapy; Books; Caring; Characteristics; Collaborations; Communities; Complex; County; Data; Data Science; Emergency department visit; Ensure; Epidemic; Ethnic Origin; Evidence based intervention; Future; Gender; Goals; HIV; Health; Health Services; Homelessness; Housing; Human; Individual; Information Systems; Infrastructure; Intervention; Investigation; Jail; Logic; Mental Health; Modeling; Outcome; Personal Satisfaction; Persons; Population; Public Health; Quality of life; ROC Curve; Race; Reduce health disparities; Reporting; Research; Research Personnel; Research Project Grants; Research Proposals; Sensitivity and Specificity; Service delivery model; Services; Subgroup; Substance Use Disorder; System; Testing; United States; Universities; Viral Load result; Vision; Washington; Work; barrier to care; base; behavioral health; classification trees; community based treatment; community partnership; community setting; design; evidence base; experience; health data; housing instability; implementation design; implementation research; implementation science; implementation strategy; improved; injection drug use; machine learning method; marginalized population; member; multidisciplinary; outreach; prediction algorithm; predictive modeling; programs; prototype; public health intervention; public health relevance; regression trees; service engagement; severe mental illness; social health determinants; substance use; theories; therapy design

PROJECT SUMMARY / ABSTRACT Engaging the most marginalized people with HIV (PWH) in treatment is crucial to end the HIV epidemic in the U.S. The Ending the HIV Epidemic (EHE) strategy in King County, Washington is designed to improve HIV services for people with complex barriers to care, including homelessness or unstable housing, severe mental illness, and substance use disorders. The health department in King County has developed a robust information exchange system with data from HIV surveillance, jail booking, and emergency room visits to guide public health interventions to re-engage PWH in care (“Data to Care”). The overall goals of the proposed project are to use data science to improve public health Data to Care activities and to establish a community-engaged partnership team that will collaboratively develop a future data-guided mobile outreach & treatment team for high-need PWH. For Aim 1, we will develop and validate an algorithm to prioritize individual PWH for interventions to improve engagement in HIV care and behavioral health services. Using a machine learning method (classification and regression tree models), we will analyze data from >14 years of case investigations and the current health department information exchange system. During the project year, we will newly integrate behavioral health and housing data into the information exchange. Throughout this work, we will incorporate input from our community partners on our use of data for care re-engagement. For Aim 2, we will establish a community-engaged partnership team to develop a mobile outreach & treatment intervention for high-need PWH in King County. This team will include representatives of key service agencies and the health department, people with lived experience, and university researchers. We will use the Transcreation Framework for community-engaged implementation science research to develop a mobile outreach and engagement team based on the Assertive Community Treatment approach, an evidence-based service delivery model that uses a multidisciplinary team to deliver community-based mental health treatment to individuals with severe mental illness. The expected outcomes of this project include: 1) a validated case prioritization algorithm for HIV care re-engagement interventions that will immediately inform health department Data to Care efforts and guide a future mobile outreach & treatment team; 2) a solidified partnership of community agencies, community members with lived experience, the health department, and researchers, which will collaboratively implement and evaluate the future mobile outreach & treatment team; and 3) a refined intervention, implementation strategy, and implementation research logic model to be used in a grant proposal to study the data-guided mobile outreach & treatment team.

项目总结/摘要 让最边缘化的艾滋病毒感染者（PWH）参与治疗对于结束艾滋病毒在非洲的流行至关重要。 美国华盛顿金县的终止艾滋病毒流行战略旨在改善艾滋病毒 为在获得护理方面有复杂障碍的人提供的服务，包括无家可归或住房不稳定、严重精神病患者、 疾病和物质使用障碍。金郡的卫生部门已经发布了一份可靠的信息 与艾滋病毒监测、监狱预约和急诊室访问的数据交换系统，以指导公共卫生 干预措施，使威尔斯亲王医院重新参与护理工作（“Data to Care”）。拟议项目的总体目标是利用 数据科学，以改善公共卫生数据护理活动，并建立社区参与的伙伴关系 该小组将为高需求的威尔斯亲王医院合作发展一个未来的数据指导移动的外展和治疗小组。 对于目标1，我们将开发和验证一种算法，以优先考虑个别PWH的干预措施，以改善 参与艾滋病毒护理和行为健康服务。使用机器学习方法（分类和 回归树模型），我们将分析来自>14年的病例调查和当前健康状况的数据 部门信息交换系统。在项目年期间，我们将新整合行为健康和 住房数据纳入信息交流。在整个工作中，我们将纳入我们的社区的投入 我们使用数据进行护理再参与。在目标2方面，我们会建立一个社区参与的 我们与一个伙伴小组合作，为金郡高需求的威尔斯亲王医院发展一个移动的外展及治疗介入计划。这 该小组将包括主要服务机构和卫生部门的代表， 经验和大学研究人员。我们将使用创译框架进行社区参与 实施科学研究，以建立一个移动的外联和参与小组， 社区治疗方法，一种使用多学科团队的循证服务提供模式 为患有严重精神疾病的人提供社区精神健康治疗。预期 该项目的成果包括：1）一个经过验证的艾滋病毒护理重新参与的病例优先级算法 干预措施，将立即通知卫生部门的数据护理工作，并指导未来的移动的 外展和治疗团队; 2）社区机构，社区成员与生活 经验，卫生部门和研究人员，将合作实施和评估未来 移动的外展和治疗团队;以及3）完善的干预、实施策略和实施 研究逻辑模型将用于研究数据引导的移动的外展和治疗团队的赠款提案。