Data2Action Oregon Project: Supporting Data-driven Decision-Making for Substance Use Services, Policy, and Overdose Prevention (D2A Oregon)

March 12, 2026 updated by: Gracelyn Cruden, Chestnut Health Systems

Supporting Data-driven Decision-Making to Support Substance Use Service Expansion Policies and to Prevent Overdoses

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

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

Enrollment (Estimated)

341

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • United States
    • Oregon
      • Eugene, Oregon, United States, 97401
        • Recruiting
        • Chestnut Health Systems
        • Contact:
        • Contact:
        • Principal Investigator:
          • Gracelyn Cruden, PhD, MA

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

Sample 1: Local or Regional Decision Makers

  • At least 18 years old
  • Has decision-making authority within their professional role related to substance use service delivery, including leadership responsible for developing policy (e.g. executive directors) OR middle-managers (e.g., case managers, supervisor) and front-line workers responsible for service delivery decisions OR Responsible for developing local or state policy related to substance use/behavioral health and/or the criminal justice system OR Advises these decision makers (e.g., legislative staff, data analysts)

These individuals will be drawn from organizations with the following perspectives: behavioral health, public health, health payer, first responders, health advocacy.

Sample 2: State or Local Decision Makers

  • At least 18 years old
  • Has decision-making authority within their professional role related to substance use service delivery, including leadership responsible for developing policy (e.g. executive directors) OR middle-managers (e.g., case managers, supervisor) and front-line workers responsible for service delivery decisions OR Responsible for developing local or state policy related to substance use/behavioral health and/or the criminal justice system OR Advises these decision makers (e.g., legislative staff, data analysts)

Exclusion Criteria:

  • None.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Sequential Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: CDS
This group will participate in 4 CDS to co-design and tailor data products with the study team. They will receive fully tailored Data Products at T3 or T4, depending on wedge assignment.
Other: Co-Design Sessions (CDS)
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.
Other: Data products
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.
Experimental: No CDS
This group will not participate in CDS. They will receive standardized data products at T3 or T4, depending on wedge assignment.
Other: Data products
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Community Engagement Survey
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
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.
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

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Data Product Usability
Time Frame: Annually for up to two years after each round of data product release in the given county (varies by condition)
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".
Annually for up to two years after each round of data product release in the given county (varies by condition)
Social Network of Collaboration
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
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).
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
Time Frame: Annually for up to two years after each round of data product release in the given county (varies by condition)
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.
Annually for up to two years after each round of data product release in the given county (varies by condition)

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Data Product: Missing Data
Time Frame: Annually for up to two years after each round of data product release in the given county (varies by condition)
The percentage of missing data (secondary data requested by the study team but not shared for any reason by local entities) will be compared across conditions.
Annually for up to two years after each round of data product release in the given county (varies by condition)
Focus Groups
Time Frame: Annually, post-baseline, for up to 3 years
Quantitative outcomes and the study's motivating theoretical frameworks -primarily the Exploration, Preparation, Implementation, Sustainment (EPIS) framework- will inform focus group discussion guides.
Annually, post-baseline, for up to 3 years
Evidence Use Behavior
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
Seven questions from Pew Health that were adopted for another NIDA-funded study are being used to assess decision makers' trust in evidence use and perceived skills to use evidence. 4 questions have a yes/no response, while 3 questions have a Likert-type response ranging from "Not at all" to "Extremely" or "Not Applicable to me in my role"
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Chestnut Health Systems

Collaborators

National Institute on Drug Abuse (NIDA)
University of California, San Diego

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 6, 2025

Primary Completion (Estimated)

June 1, 2028

Study Completion (Estimated)

August 31, 2028

Study Registration Dates

First Submitted

January 31, 2025

First Submitted That Met QC Criteria

February 26, 2025

First Posted (Actual)

February 28, 2025

Study Record Updates

Last Update Posted (Actual)

March 16, 2026

Last Update Submitted That Met QC Criteria

March 12, 2026

Last Verified

March 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • R33DA059163 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

De-identified IPD collected by the study will be shared per procedures outlined in a NIH-approved Data Sharing and Management Plan as part of the NIH and NIH HEAL-initiative data sharing requirements. Some qualitative data will lose meaning if de-identified and will thus not be shared.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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