Evidence map›Paper›PMID 42507832›Full record

Observational studyJMIR human factors2026

Barriers to Population Data Use in Overdose Fatality Reviews: Observational and Interview Study of Dashboard Deployment.

Amey Salvi, Cynthia Holladay, Allyson L Dir, Bradley Ray, Matthew C Aalsma, Khairi Reda

Abstract readObservational Study
In one paragraph

Observational study in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Amey SalviSchool of Informatics, Computing, and Engineering, Indiana University Indianapolis, Indianapolis, IN, United States.ORCID 0009-0006-7840-9924
Cynthia HolladayDepartment of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID 0009-0001-5332-6499
Allyson L DirDepartment of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID 0000-0002-6004-4692
Bradley RayRTI International, Research Triangle Park, NC, United States.ORCID 0000-0003-3643-775X
Matthew C AalsmaDepartment of Pediatrics, Children's Health Services Research, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID 0000-0001-5952-6785
Khairi RedaDepartment of Computer Science, University of Illinois Chicago, 850 W Taylor St, CDRLC 5409, Chicago, IL, 60607, United States, 1 3123550271.ORCID 0000-0002-8096-658X

Funding

Fatal Overdose Review Teams - Research to Enhance Surveillance Systems (FORTRESS)R33DA057660 · NIDA · INDIANA UNIVERSITY INDIANAPOLIS · PI AALSMA, MATTHEW, RAY, BRADLEY · 2024 to 2024
$3.3M
Fatal Overdose Review Teams - Research to Enhance Surveillance Systems (FORTRESS)R61DA057660 · NIDA · INDIANA UNIVERSITY INDIANAPOLIS · PI AALSMA, MATTHEW, RAY, BRADLEY · 2022 to 2022
$1.6M
NIDA NIH HHS R33 DA057660NIDA NIH HHS R61 DA057660
6 · The paper itself

Abstract

Background: Overdose fatality reviews (OFRs) are an important public health tool for developing local overdose prevention strategies by reviewing individual overdose cases. While this approach offers a rich, contextual understanding of drug overdose factors in communities, it examines a small number of cases, providing limited insight into broader population-level risk patterns. To complement OFRs, we developed a real-time dashboard that visualizes trends about 5 key "touchpoints" (ie, interactions with medical and justice services preceding overdose). We then trained local OFR teams to use this dashboard to identify prevention opportunities. Objective: This study examines the integration of population-level data into OFR practices, as well as the tensions that emerge between OFRs' traditional case-driven review processes and the statistical, population-level analysis typical in public health. We analyze how and when the dashboard was used in meetings, determine the extent to which the data informed recommendations, and identify barriers that prevented the broad uptake of this intervention. Methods: We observed 26 OFR meetings across 11 counties in Indiana over 10 months, from November 2024 to September 2025, during which teams conducted case reviews and developed recommendations. We documented instances of dashboard use as well as "missed opportunities," in which relevant population-level data were available but not incorporated into the discussion. We also conducted semistructured interviews with OFR team members (n=7) to understand their perceptions of the dashboard, including its usefulness, usability, and adoption barriers. Results: Despite its intended role, the dashboard was rarely integrated into OFR meetings; it was used only 10 times, compared to 114 missed opportunities in which relevant data could have informed discussions. Interviews revealed that this limited uptake was not solely due to usability barriers but reflected a deeper tension between 2 distinct analytic approaches. OFR teams prioritized narrative-driven case reviews that were grounded in empathy, local knowledge, and lived experience. This approach seemed at odds with the population-level visualizations shown in the dashboard, which required statistical abstraction and interpretation. Other barriers identified included limited time and resources, staff turnover, and varying levels of data fluency, which made it difficult for teams to confidently interpret the dashboard despite training. Conclusions: The results highlight a tension between case-based and data-driven approaches to overdose prevention. These approaches are grounded in different workflows, values, and motivations, making it challenging for OFR teams to maintain their traditional, empathetic review practices while incorporating population-level trends. Our findings indicate the need for data tools that bridge these approaches, such as visualizations that connect aggregate patterns to individual cases. The results also underscore the need for additional support and training for teams, such as dedicated data specialists who interpret population-level trends and provide insights to augment team discussions and inform prevention strategies.

Indexed as

Drug OverdoseDashboard SystemsHumansInterviews as Topicdashboardfatality reviewinterviewobservation studyoverdoseoverdose preventionpreventionpublic healthrecommendationssubstance abusetouchpointsvisualization

Identifiers

PMID42507832
PMCPMC13404934

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.