Introduction: Linking emergency medical services (EMS) data to emergency department (ED) data enables assessing the continuum of care and evaluating patient outcomes. We developed novel methods to enhance linkage performance and analysis of EMS and ED data for opioid overdose surveillance in North Carolina.
Methods: We identified data on all EMS encounters in North Carolina during January 1-November 30, 2017, with documented naloxone administration and transportation to the ED. We linked these data with ED visit data in the North Carolina Disease Event Tracking and Epidemiologic Collection Tool. We manually reviewed a subset of data from 12 counties to create a gold standard that informed developing iterative linkage methods using demographic, time, and destination variables. We calculated the proportion of suspected opioid overdose EMS cases that received diagnosis codes for opioid overdose in the ED.
Results: We identified 12 088 EMS encounters of patients treated with naloxone and transported to the ED. The 12-county subset included 1781 linkage-eligible EMS encounters, with historical linkage of 65.4% (1165 of 1781) and 1.6% false linkages. Through iterative linkage methods, performance improved to 91.0% (1620 of 1781) with 0.1% false linkages. Among statewide EMS encounters with naloxone administration, the linkage improved from 47.1% to 91.1%. We found diagnosis codes for opioid overdose in the ED among 27.2% of statewide linked records.
Practice Implications: Through an iterative linkage approach, EMS-ED data linkage performance improved greatly while reducing the number of false linkages. Improved EMS-ED data linkage quality can enhance surveillance activities, inform emergency response practices, and improve quality of care through evaluating initial patient presentations, field interventions, and ultimate diagnoses.
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http://dx.doi.org/10.1177/00333549211012400 | DOI Listing |
BMJ Open
December 2024
Disease Elimination, Burnet Institute, Melbourne, Victoria, Australia
Introduction: Opioid overdose and blood-borne virus transmission are key health risks for people who inject drugs. Existing study methods that record data on injecting drug risks mostly rely on retrospective self-reporting that, while valid, are limited to being broad and subject to recall bias. The In-The-Moment-Expanded (ITM-Ex) study will evaluate the feasibility and acceptability of multiple novel data collection methods to capture in situ drug injecting data.
View Article and Find Full Text PDFPharmacoepidemiol Drug Saf
January 2025
Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, USA.
Purpose: Long-term opioid therapy (LTOT) has been shown to be associated with opioid overdose, but the definition of LTOT varies widely across studies. We use a rigorous LTOT definition to examine risk of opioid overdose by duration of treatment.
Methods: Data were from a large private health insurance provider in North Carolina linked to mortality records from 2006-2018.
Subst Use Addctn J
January 2025
Behavioral Health Network - St. Louis, St. Louis, MO, USA.
Background: In 2020, loosened federal regulations allowed for buprenorphine for opioid use disorder to be initiated via telemedicine. In response to these regulatory changes and growing racial inequities in overdose in St. Louis, MO, a local, peer-led outreach program incorporated a new rapid access (RA) to buprenorphine program.
View Article and Find Full Text PDFDrug Alcohol Depend
January 2025
University of Miami Miller School of Medicine, Department of Public Health Sciences, United States.
Introduction: Prevalence estimates of opioid use disorder (OUD) at local levels are critical for public health planning and surveillance, yet largely unavailable across the US especially at the local county level.
Methods: We used a Bayesian evidence synthesis approach to estimate the prevalence of OUD for 57 counties across New York State for 2017-2019 and compare rates of OUD across counties as well as assess the extent of undiagnosed OUD. We developed a generative model to assess conditional probabilistic relations between different subgroups of the OUD population defined by diagnosis, treatment, and overdose fatality.
Inj Prev
January 2025
Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
Background: In 2020, Maryland had the fourth-highest opioid overdose mortality rate in the USA. We describe substances identified in postmortem toxicology screening and designated as cause of death (COD) for overdose decedents in Maryland, including specific combinations of substances designated as COD.
Methods: We performed a retrospective analysis of N=5442 adult overdose decedents (ie, manner of death unintentional or undetermined) in Maryland between January 2020 and December 2021.
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