Predictors of emergency medical transport refusal following opioid overdose in Washington, DC

Refusal of emergency transport for opioid overdose cases in Washington, DC, USA, has expanded by 43.8% since 2017. Several social, environmental and systematic factors can predict this refusal. Logistic regression models can be used to quantify broad categories of behavior in surveillance medical research.

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Publication Details

Journal
Addiction
Published
2024-10-12
DOI
https://doi.org/10.1111/add.16686
Citations
3
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
2.07

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article

Predictors of emergency medical transport refusal following opioid overdose in Washington, DC

Ben Turley, Kenan Zamore, Robert P. Holman
3 citations
Addiction
Emergency and Acute Care Studies
2.07
article

Predictors of emergency medical transport refusal following opioid overdose in Washington, DC

Ben Turley, Kenan Zamore, Robert P. Holman
article en
3 citations

Abstract

Refusal of emergency transport for opioid overdose cases in Washington, DC, USA, has expanded by 43.8% since 2017. Several social, environmental and systematic factors can predict this refusal. Logistic regression models can be used to quantify broad categories of behavior in surveillance medical research.

AddictionVol. 120(2)
New York City Fire Department (US), Georgetown University (US), District of Columbia Department of Health (US), CDC Foundation (US), University of Maryland, College Park (US)
Centers for Disease Control and Prevention
No poverty
Openalex Percentile: Top 13%
Emergency and Acute Care Studies
2.07
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