Oregon's decision makers (e.g., community service providers, public health, justice, advocacy groups, payers) are calling for comprehensive, current, and trusted data to inform how they allocate resources to improve substance use services and mitigate the growing opioid and methamphetamine epidemics in their state. Consistent with the HEAL Data2Action call for Innovation projects that drive action with data in real-world settings, this study will refine and test the impact of a novel implementation strategy to engage cross- sector decision makers and make data that they identify as relevant to their decisions available to them in easy- to-use products. The proposed study aims to not only address critical knowledge gaps regarding how and when data can inform impactful, transparent decision-making, but to provide decision makers with the data that they need to achieve community-wide substance use prevention and treatment goals, including the increased delivery of high-quality, evidence-informed, services and the prevention of overdoses.
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. In 2022 national survey data, Oregon ranked 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. This 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 Oregonian's health. Major, innovative policy decisions about substance use are being in made in Oregon right now. This policy context is accounted for in study design, activities, and analyses. One is 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. More recently, HB 4002 re-criminalized simple possession and set aside funding for counties to establish criminal legal system deflection programs. Both critics and advocates of M110 and HB 4002 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, the investigators will develop, refine, and test a policy implementation strategy-Co-Design Sessions (CDS)-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 current project phase, which includes the clinical trial, counties will be cluster randomized to participate in CDS and receive fully tailored data products (N = 18) or to later receive products only (N = 18) in a stepped-wedge design. The investigators will: (Aim 1) identify whether CDS is an efficient, generalizable strategy to optimize policy implementation based on the comparative usability of CDS-generated data products between counties; (Aim 2) test the impact of CDS on substance use service gaps and service-recipient outcomes, as well as cross-sector collaboration and trust in data as potential mechanisms of CDS; and (Aim 3) examine whether CDS-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, the investigators 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 study holds strong potential for immediate, real-world impact.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
341
CDS uses principles and activities from Liberating Structures (LS) and Group Model Building (GMB). Each method uses semi-structured processes for engaging partners to collaborate with one another and address complex problems. Example activities and discussions include: identifying a shared vision for how data can inform decisions related to substance use service delivery and overdose prevention; identifying relevant data that should be disseminated; identifying decisions to be supported with data. Methods from human-centered design - an approach for developing products that are useful and easy to use - will be used to refine data products developed by the study team so that the data products are acceptable and useful to end users. Together, these three methods (Liberating Structures, group model building, human-centered design) will be used to engage partners to iteratively co-design products for disseminating data back to partners to inform their daily substance use service delivery.
Data products disseminate localized data from local, state, or regional-level data sources to local (i.e., county) decision makers to inform their daily decision-making. Data products in counties assigned to CDS will receive fully tailored data products, while no-CDS counties will receive standardized data products. A suite of data products will be made available to inform diverse decisions by a variety of end users. Data products will be identified and prioritized during CDS, but may include reports, policy briefs, journey maps, and technical assistance for data interpretation.
Chestnut Health Systems
Eugene, Oregon, United States
RECRUITINGCommunity Engagement Survey
A measure of community engagement (Oetzel et al, 2018) which includes 2 subscales; collaboration, which includes 4 items answered on a Likert Scale ranging from Strongly Disagree to Strongly Agree, and synergy, which includes 7 items answered on a Likert Scale ranging from Not at All to To a Great Extent.
Time frame: Measurement will occur at five timepoints: baseline, around 15 months post-baseline, around 18 months post-baseline, around 30 months post-baseline, around 42 months post-baseline
Data Product Usability
Acceptability and Usability of the Data Products will be assessed through the System Usability Scale, a 10-item measure that will be tailored for the current study. Scoring is from 1 - 5, with 1 indicating "Strongly disagree" and 5 indicating "Strongly agree".
Time frame: Annually for up to two years after each round of data product release in the given county (varies by condition)
Social Network of Collaboration
A study-specific measure will probe about connections that facilitate collaboration, defined as clinical referrals and client care coordination. Questions probe presence and strength of ties (e.g., whether referrals sent and/or received from other organizations). Open-ended questions probe timing, nature, and origin of collaborations (e.g., nodes).
Time frame: Measurement will occur at five timepoints: baseline, around 15 months post-baseline, around 18 months post-baseline, around 30 months post-baseline, around 42 months post-baseline
Trust in data
A measure of trust in data (Yoon \& Lee, 2019) was tailored for the current study. Tailoring including removing items and slight rewording of item stems (e.g., "data system" to "data"). The study measure includes 5 items answered on a Likert Scale ranging from 1= Strongly Disagree to 5 = Strongly Agree and including 0 = don't know.
Time frame: Annually for up to two years after each round of data product release in the given county (varies by condition)
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