Supporting data-driven decision-making to support substance use service expansion policies and to prevent overdoses

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PROJECT SUMMARY Cross-sector decision makers—such as community service providers, public health, justice, advocates, and payers—are calling for actionable data to be collected and shared in sustainable, useful ways. Oregon ranks last in the U.S. for access to substance use services and first in opioid and methamphetamine use. A recent state- wide analysis estimated that service gaps may even be larger than previously estimated. The proposed study aims to make data that are relevant to decision makers available to them in easy-to-use formats so that they can make timely, evidence-informed decisions to reduce substance use service gaps and overdoses, and ultimately improve health. We will leverage the roll-out of a first-of-its-kind policy in the United States—Ballot Measure 110 (M110). M110 is bringing unprecedented levels of funding to expand services aligned with the pillars of overdose prevention statewide, and it decriminalized the possession of personal amounts of substances. Both critics and advocates of M110 have called for better data to provide a holistic picture of substance use service and service- recipient impacts, and to inform looming decisions such as how to allocate opioid settlement funds. To meet this need, consistent with goals of the NIH Helping to End Addiction Long-term Data2Action Program call for Innovation Projects with cross-sector partnerships, we propose to develop, refine, and test a policy implementation strategy—Discovery and Design Sessions (DDS)—to engage cross-sector decision makers in conversations about what data are of priority to them and to develop feasible protocols for linking and disseminating data through products that they co-design (e.g., reports, simulations, dashboards). In the R61 phase, we will strengthen and expand existing partnerships with five types of decision makers, including state agencies responsible for monitoring and/or implementing M110 and for maintaining a statewide data repository. DDS, DDS-generated data products, and co-developed protocols for data sharing and for study-generated data collection will be refined for feasibility and testing. In the R33 phase, counties will be cluster randomized to participate in DDS and receive fully tailored data products (N = 18) or to later receive products only (N = 18) in a stepped-wedge design. We will: (Aim 1) identify whether DDS is an efficient, generalizable strategy to optimize policy implementation based on the comparative usability of DDS-generated data products between counties; (Aim 2) test the impact of DDS on substance use service gaps and service-recipient outcomes, as well as cross- sector collaboration; and (Aim 3) examine whether DDS-generated data products are associated with concrete actions (e.g., funding) to strengthen the availability and quality of evidence-based, culturally-responsive substance use services. Based on study results and partners’ input, we will provide state decision makers with recommendations and protocols for supporting sustainment of study infrastructure and output, including: feasible methods for prioritized data collection and data product dissemination, and the transfer of study-generated data to state-wide data infrastructures. The proposed study holds strong potential for immediate, real-world impact.