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 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.
We propose to conduct a two-phase research project that leverages Center for Disease Control funding awarded to the Albuquerque Area Southwest Tribal Epidemiology Center for improving data quality in opioid overdose surveillance in New Mexico. In the first phase, the goal is to use geocoding and data linkages to address the need in New Mexico for tribe-specific data and analyses on opioid use disorder and opioid overdose. After disseminating analyses to tribal communities and Indian Health Service, Tribal and Urban Indian health facilities, our goal in the second phase is to collaborate with interested tribes and facilities in a community-based participatory intervention research project that develops and tests a culturally centered implementation program for providing medication for opioid use disorders to American Indian patients.
