Understanding opioid use within a Southwestern American Indian Reservation Community: A qualitative study.

PURPOSE: Morbidity and mortality due to nonprescription use of opioids has been well documented following the significant increase in the availability of prescription opioids in the early 2000s. The aim of this paper is to explore community beliefs about correlates of opioid risk, protective factors, and behavioral functions of opioid misuse among American Indian youth and young adults living on or near a reservation. METHODS: Qualitative in-depth interviews were conducted with N = 18 youth and young adults who were enrolled in a parent research trial focused on American Indian youth suicide prevention. Participants were eligible if they endorsed the use of opioids themselves or by close friends or family members at any point during their trial participation. FINDINGS: Major themes discussed include: (1) description of opioid use and those who use opioids; (2) acquisition; (3) initiation; (4) motivation to continue using; (5) consequences; and (6) possibilities for intervention. Family played an important role in the initiation of use, but was also highlighted as an important factor in treatment and recovery. A need for upstream prevention methods, including increased employment and after-school activities, was described. CONCLUSIONS: The insights gained through this work could help to inform treatment and prevention programs in the community. This work is timely due to the pressing urgency of the opioid epidemic nationally, and community capacity to address opioid use locally.

Designing a Clinical Decision Support Tool That Leverages Machine Learning for Suicide Risk Prediction: Development Study in Partnership With Native American Care Providers.

BACKGROUND: Machine learning algorithms for suicide risk prediction have been developed with notable improvements in accuracy. Implementing these algorithms to enhance clinical care and reduce suicide has not been well studied. OBJECTIVE: This study aims to design a clinical decision support tool and appropriate care pathways for community-based suicide surveillance and case management systems operating on Native American reservations. METHODS: Participants included Native American case managers and supervisors (N=9) who worked on suicide surveillance and case management programs on 2 Native American reservations. We used in-depth interviews to understand how case managers think about and respond to suicide risk. The results from interviews informed a draft clinical decision support tool, which was then reviewed with supervisors and combined with appropriate care pathways. RESULTS: Case managers reported acceptance of risk flags based on a predictive algorithm in their surveillance system tools, particularly if the information was available in a timely manner and used in conjunction with their clinical judgment. Implementation of risk flags needed to be programmed on a dichotomous basis, so the algorithm could produce output indicating high versus low risk. To dichotomize the continuous predicted probabilities, we developed a cutoff point that favored specificity, with the understanding that case managers' clinical judgment would help increase sensitivity. CONCLUSIONS: Suicide risk prediction algorithms show promise, but implementation to guide clinical care remains relatively elusive. Our study demonstrates the utility of working with partners to develop and guide the operationalization of risk prediction algorithms to enhance clinical care in a community setting.