Leveraging CDC Opioid Overdose Surveillance Funding from the Albuquerque Area Southwest Tribal Epidemiology Center to Create Tribal Data and Culturally Center Medications for Opioid Use Disorder

项目总结/摘要 美洲印第安人/阿拉斯加原住民的致命阿片类药物过量率高于西班牙裔， 非洲裔美国人和亚裔美国人，仅低于非西班牙裔白人。AI/AN阿片类药物过量率 州和县之间的差异很大;然而，部落层面的差异很难确定， 分散的数据系统，将州卫生数据和印度卫生服务数据分开。虽然县级 健康数据经常被用作部落数据的替代，州数据经常对AN/AN患者进行错误分类，而在县 由于县的数据包含多个部落的土地，可能会模糊部落间的重大差异。除了有限的 根据特定部落的数据，阿片类药物使用障碍的治疗也往往不能解释部落的多样性。 人口。平均而言，服用阿片类药物使用障碍（MOUD）的患者，特别是 美沙酮或丁丙诺啡，表现出改善的治疗保留和减少药物过量的风险相比， 不服用MOUD的患者。一些研究还显示，另一种MOUD-纳洛酮的保留率有所提高。 由于MOUD干预措施很少针对AI/AN患者的特定文化背景，因此社会和 治疗的文化障碍在人工授精/人工授精社区仍然存在。为了解决这些问题，我们建议利用 疾病控制中心资助阿尔伯克基地区西南部落流行病学中心 （AASTEC）在两阶段研究中提高新墨西哥州阿片类药物过量监测的数据质量 项目该项目将利用由临床医生和印度卫生设施组成的社区咨询委员会 工作人员，并利用来自AASTEC和新墨西哥州卫生部的流行病学家的合作， 犹他州大学、新墨西哥州大学和哥伦比亚大学的学术研究人员。上 阶段，我们将通过链接和地理编码来增强AI/AN阿片类药物使用障碍和过量数据的部落特异性 新墨西哥州的生命统计和综合征监测数据。然后，我们将在预测模型中使用这些数据， 确定特定部落社区可改变的风险和保护因素的作用。我们将传播 向部落社区提供分析报告，并寻求与部落和印第安卫生设施建立伙伴关系， 我们的研究阶段，这需要一个基于社区的参与性研究项目，将开发和测试 以文化为中心的MOUD实施计划，用于AI/AN社区。我们将使用一个步进 在四个印度卫生机构中进行楔形随机设计，以测试 随着时间的推移，患者和诊所工作人员之间的文化中心MOUD。该研究将加强 部落社区，AASTEC和学术研究人员之间的伙伴关系，并更好地调整阿片类药物研究 部落价值观和优先权。我们预计我们的研究不仅会在学术期刊上发表 而且还将产生用于为其他地区创建特定部落数据估计的工具包， 将MOUD集中在其他AI/AN社区和印度卫生设施的背景下。

Project Summary/Abstract Fatal opioid overdose rates are higher among American Indian/Alaska Native populations than among Hispanics, African Americans, and Asian Americans, and are just below non-Hispanic Whites. AI/AN opioid overdose rates vary significantly by state and county; however, tribe-level differences are difficult to ascertain due to decentralized data systems that divide state health data and Indian Health Service data. While county-level health data is often used as a proxy for tribal data, state data often misclassify AN/AN patients, and in counties containing the lands of multiple tribes, county data may blur significant inter-tribal variation. In addition to limited tribe-specific data, treatment for opioid use disorders also often fails to account for the diversity of tribal populations. On average, patients who take medication for opioid use disorder (MOUD), and specifically methadone or buprenorphine, exhibit improved treatment retention and reduced risk of drug overdose compared to patients not taking MOUD. Some research also shows improved retention for Naltrexone, another MOUD. Because MOUD interventions are rarely tailored to the specific cultural contexts of AI/AN patients, social and cultural barriers to treatment persist in AI/AN communities. To address these problems, we propose to leverage Center for Disease Control funding awarded to the Albuquerque Area Southwest Tribal Epidemiology Center (AASTEC) for improving data quality in opioid overdose surveillance in New Mexico in a two-phase research project. The project will draw upon a community advisory board composed of clinicians and Indian health facility staff, and use a collaboration of epidemiologists from AASTEC and the New Mexico Department of Health, and academic researchers at the University of Utah, University of New Mexico, and Columbia University. In the first phase, we will enhance tribal specificity of AI/AN opioid use disorder and overdose data by linking and geocoding New Mexico vital statistics and syndromic surveillance data. We will then use these data in predictive models to determine the role of modifiable risk and protective factors for specific tribal communities. We will disseminate analysis reports to tribal communities and seek partnerships with tribes and Indian health facilities for the second phase of our research, which entails a community-based participatory research project that will develop and test a culturally centered implementation program for MOUD for use in AI/AN communities. We will use a stepped wedge randomized design in four Indian health facilities to test initiation, retention, relapse, and acceptability of culturally centered MOUD among patients and clinic staff over time. The proposed research will strengthen partnerships between tribal communities, AASTEC, and academic researchers, and better align opioid research with tribal values and priorities. We anticipate our research will not only result in publications in academic journals but will also result in toolkits for creating tribe-specific data estimates for other regions, and protocols for culturally centering MOUD for the contexts of other AI/AN communities and Indian health facilities.