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NCT06084221: FORTRESS

Fatal Overdose Review Teams - Research to Enhance Surveillance Systems

ENROLLING BY INVITATION NA Last updated 6 February 2026
What this trial tests

NA trial testing Data-Driven Decision Making (DDDM) in Substance-Related Disorders in 400 participants. Enrolling by invitation.

Timeline
21 September 2023
Primary endpoint
30 September 2027
30 September 2027

Quick facts

Lead sponsorIndiana University
PhaseNA
StatusENROLLING BY INVITATION
Study typeINTERVENTIONAL
Allocationrandomized
Designparallel
Maskingnone
Primary purposeprevention
Enrollment400
Start date21 September 2023
Primary completion30 September 2027
Estimated completion30 September 2027
Sites1 location across United States

Drugs / interventions tested

Conditions studied

Sponsor

Indiana University

Who can join

Eligibility, any sex, with Substance-Related Disorders or Opioid-Related Disorders. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This project seeks to address the overdose epidemic by working with overdose fatality review (OFR) teams. Current OFR practices rely on a case review model where OFR teams assess one or two overdose cases to make policy and program recommendations. However, the continued rise in overdose rates and number of preventable overdose deaths suggest a need to shift OFR teams away from case review and toward using timely population-level data to better inform their recommendations and actions. The goal of this project, Fatal Overdose Review Teams - Research to Enhance Surveillance Systems (FORTRESS), is to improve standard OFR practices by equipping OFRs with a data dashboard built on near real-time aggregate data, linked across multiple sources and presented in a way that helps identify common "overdose touchpoints," or opportunities to connect individuals at risk for overdose with evidence-based treatment. During the first project phase, the FORTRESS team will design the "Overdose Touchpoints Dashboard'' (Aim 1). The FORTRESS team will also train OFR team members in "Data-Driven Decision Making" (DDDM) to effectively use the dashboard. The FORTRESS team also includes individuals involved in developing the CDC's OFR best practice guidelines and a pilot study of OFR adherence to these guidelines, which will inform the FORTRESS team's development of an "OFR Fidelity Tool'' (Aim 2). This tool will be the first of its kind. For the second project phase, the FORTRESS team will conduct a cluster-randomized stepped-wedge trial comparing the impact of the intervention (dashboard + DDDM training) versus standard OFR practices on both implementation (Aim 3) and effectiveness outcomes (Aim 4). Implementation outcomes include implementation process fidelity (Stages of Implementation Completion), staff acceptance of harm reduction philosophies (qualitative interviews), OFR fidelity to CDC best practices (FORTRESS OFR Fidelity Tool), and usability of the Overdose Touchpoint Dashboard, (Systems Usability Scale). A statewide OFR data repository serves as a rich source of data on effectiveness outcomes, including OFR team recommendation quality and local actions to implement recommended overdose prevention strategies. The FORTRESS team will also survey OFR team members to assess changes in their attitudes toward evidence-based overdose prevention strategies. In sum, the FORTRESS team is uniquely qualified to help OFRs use more comprehensive available data to inform quality, action-oriented recommendations to reduce overdose. Funding for this project comes from the HEAL Initiative (https://heal.nih.gov/).

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Substance-Related Disorders

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Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06084221.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing