Evidence map›Paper›PMID 41260589›Full record

Trial reportJournal of public health management and practice : JPHMP

Lessons From the Community-Engaged, Data-Driven Selection of Evidence-Based Practice Strategies in the HEALing Communities Study.

Peter Balvanz, Daniel Harris, Ramona Olvera, Nasim Sabounchi, Carly Bridden, Jane Carpenter, Carolyn Damato-MacPherson, James David, Naleef Fareed, Erin Gibson and 11 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of public health management and practice : JPHMP. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Building Public Health Data Dashboards: Tutorial Playbook.JMIR public health and surveillance · 2026
    Article
  3. Article
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

21 authors.

Peter BalvanzAuthor Affiliations: General Internal Medicine, Boston Medical Center, Boston, MA (Mr Balvanz, Ms Bridden, Ms Damato-MacPherson, Ms Kosakowski, Dr Larochelle); Institute for Biomedical Informatics, University of Kentucky, Lexington, Kentucky (Dr Harris); Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research (CATALYST), College of Medicine, The Ohio State University, Columbus, Ohio (Dr Olvera); School of Social Work, Columbia University, New York, New York (Dr Sabounchi, Mr David, Dr Hunt, Dr Lounsbury, Dr Wu); Families First Parenting Programs, Watertown, Massachusetts (Ms Carpenter); Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio (Dr Fareed); College of Medicine, The Ohio State University, HEALing Communities Study, Columbus, Ohio (Dr Olvera, Dr Fareed, Dr Huerta, Ms Plagens, Dr Chase); Tufts Clinical and Translational Science Institute, Boston, Massachusetts (Ms Gibson); Boston University Chobanian & Avedisian School of Medicine (Dr Larochelle); Berkshire Regional Planning Commission, Pittsfield, Massachusetts (Ms Lewis); Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California (Ms Smeltzer) and Division of Program Coordination, Planning, and Strategic Initiatives, National Institute on Drug Abuse, Bethesda, Maryland (Dr Villani).ORCID 0000-0003-1273-8275
Carolyn Damato-MacPhersonORCID 0009-0002-7889-9717
Sarah Kosakowski
Nikki Lewis
Courtney Plagens

Funding

MassHEAL - Reducing overdose deaths by 40% (2019-2023)UM1DA049412 · NIDA · BOSTON MEDICAL CENTER · PI SAMET, JEFFREY H. · 2019 to 2023
$82.9M
NIDA NIH HHS UM1 DA049412
6 · The paper itself

Abstract

Public health data and tools have proliferated, yet practical guidance for community-engaged data-driven decision making is limited. The HEALing Communities Study (HCS) was a randomized, wait-list controlled trial to assess the impact of an intervention to reduce fatal opioid overdoses in 67 highly affected communities across 4 sites (Kentucky, Massachusetts, New York, and Ohio). HCS researchers implemented the Communities That HEAL intervention, a phased approach which included a coalition-engaged, data-driven approach to selection of evidence-based practice strategies to reduce fatal opioid overdoses. Core steps to the data-driven approach included data selection, access, display, and engagement. Staff selected metrics that aligned with study goals, accessed data from numerous sources, created visualizations, and engaged coalition members to assess resource gaps and intervention opportunities. At the intervention conclusion, all 4 sites' staff collectively workshopped best practices and barriers encountered to data-driven decision making. This article explains the data-driven decision-making approach implemented, assessment results, alterations for subsequent implementation, and guidance for future implementations.

Indexed as

Drug OverdoseEvidence-Based PracticeHumansNew Yorkclinical trialcommunity engagementdata-driven decision makingevidence-based practicesopioids

Identifiers

PMID41260589
PMCPMC13224081

What OpenQuestion holds

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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.