Evidence map›Paper›PMID 41604150›Full record

ArticleJAMA network open2026

Health, Costs, and Injection-Related Infections at a Hypothetical Overdose Prevention Center.

Pranav Padmanabhan, Yjuliana Tin, Samantha K Nall, Alia Al-Tayyib, Theodore Yoder, Kristina Yamkovoy, Kevin Fotso, Paul J Christine, Cole Jurecka, Lisa Raville and 2 more

Abstract read
In one paragraph

Article in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Pranav PadmanabhanDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.
Yjuliana TinDepartment of Health Systems, Management & Policy, Colorado School of Public Health, Aurora.
Samantha K NallDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.
Alia Al-TayyibDepartment of Epidemiology, Colorado School of Public Health, Aurora.
Theodore YoderDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.
Kristina YamkovoyDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.
Kevin FotsoOffice of Information Technology, University of Colorado School of Medicine, Aurora.
Paul J ChristineDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.
Cole JureckaDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.
Lisa RavilleHarm Reduction Action Center, Denver, Colorado.
Danielle M KlineDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.
Joshua A BarocasDepartment of Medicine, Division of General Internal Medicine, University of Colorado School of Medicine, Aurora.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: While the impact of overdose prevention centers (OPCs) on fatal overdose, HIV, and hepatitis C is well-characterized, the long-term clinical and cost impact on injection-related infections is unknown, and empirical data from the US are limited. Objective: To estimate the 10-year impact of a hypothetical OPC in Denver, Colorado, on injection-related infections, hospitalizations, mortality, and associated costs from a payer perspective. Design, Setting, and Participants: This decision analytical modeling study used a calibrated and validated Monte Carlo microsimulation model of the natural history of injection drug use. Data included people who inject drugs (PWID) in Denver, Colorado, simulated over 10 years, from 2023 to 2032. Input data were largely collected from the 2022 National HIV Behavioral Surveillance survey and published research on currently operating OPCs. Exposure: Treatment service model for PWID; the status quo, in which 3 syringe service programs are operating, was compared with counterfactual scenarios in which a single OPC also operated and served between 10% and 70% of Denver's population of PWID. Main Outcomes and Measures: Incidence of serious injection-related infections (SIRIs; infective endocarditis [IE] and skin and soft tissue infections [SSTIs]), hospitalizations, mortality, and associated costs from a health care payer perspective. Results: The modeled population of 9697 PWID had an input mean (SD) age of 41.3 (1.9) years and included 74.1% male participants. Over a 10-year period, the status quo resulted in approximately 15 400 SIRIs, 15 000 hospitalizations for SIRIs and overdose, and 2400 deaths among Denver's population of PWID. Compared with the status quo scenario, a hypothetical OPC decreased SSTI incidence by up to 11.5% (95% credible interval [CrI], -16.8% to -6.4%), IE incidence by up to 22.0% (95% CrI, -27.6% to -6.1%), hospitalizations by up to 8.5% (95% CrI, -14.0% to -2.6%), and all-cause mortality by up to 5.8% (95% CrI, -12.4% to 4.9%), and saved between $7 million and $46 million from a payer perspective over 10 years, depending on the program reach. Findings were robust in sensitivity analyses. Conclusions and Relevance: In this simulation modeling study of the effect of a hypothetical OPC, implementing a single OPC in Denver was an effective intervention to decrease SIRIs, drug use-related hospitalizations, costs, and deaths among PWID.

Indexed as

Drug OverdoseHealth Care CostsNeedle-Exchange ProgramsSubstance Abuse, IntravenousColoradoHepatitis CHIV InfectionsHospitalizationHumansMaleMonte Carlo Method

Identifiers

PMID41604150
PMCPMC12853211

What OpenQuestion holds

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Registered trials

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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.