Rising Injection-Related Infections amid Declining Overdose Deaths in the Southeast
Location
Lion's Eye Center
Event Website
https://publichealth.lsuhsc.edu/honorsday/2026/
Start Date
7-4-2026 11:30 AM
End Date
7-4-2026 1:30 PM
Description
Background: Although opioid overdose deaths have recently stabilized or declined in parts of the southeastern United States, injection-related infections (IRIs) continue to rise. This evolving syndemic of substance use disorder (SUD) and infectious complications is often under-identified due to limitations in ICD-10 coding, provider documentation variability, and underreporting of injection drug use. Consequently, health systems lack reliable tools to quantify IRI burden and evaluate trends.
Objectives: To develop and validate an ICD-10–based algorithm to accurately identify four IRI phenotypes (endocarditis, vertebral osteomyelitis/epidural abscess, bacteremia & deep infections, and skin & soft tissue infections (SSTI)) and to quantify its diagnostic performance against gold-standard manual chart review.
Methods: We conducted a retrospective analysis of a multi-hospital electronic medical record dataset within a single health system from January 1, 2023 to January 1, 2025. Phenotype-specific ICD-10 codes for IRI diagnoses were combined with SUD-related ICD-10 codes and temporally linked evidence of SUD using an iterative modeling approach. Validation was performed through blinded manual chart review by two independent reviewers using predefined adjudication criteria. Inter-rater reliability was assessed using Cohen’s kappa. Algorithm performance was summarized using positive predictive value (PPV).
Results: The algorithm identified 710 true positive, 158 suspected positive, and 175 false positive encounters. Strict PPV was 68%, and inclusive PPV was 83%. Inter-rater reliability was strong (κ = 0.86). Over the study period, IRI encounters increased, while opioid overdose admissions remained stable.
Conclusions: Injection-related infections are rising despite stabilization of overdose admissions in this southeastern health system. A validated ICD-10 algorithm enables scalable identification of IRIs without reliance on structured data fields or natural language processing.
Recommendations: This validated algorithm may strengthen public health surveillance, inform resource allocation, support addiction medicine integration and infectious disease service planning, and enable health system–level monitoring of injection-related infection trends as the opioid crisis evolves beyond overdose mortality alone.
Recommended Citation
Dicken, Patrick, "Rising Injection-Related Infections amid Declining Overdose Deaths in the Southeast" (2026). School of Public Health Delta Omega Honors Day Poster Sessions. 7.
https://digitalscholar.lsuhsc.edu/dohd/2026/2026/7
Rising Injection-Related Infections amid Declining Overdose Deaths in the Southeast
Lion's Eye Center
Background: Although opioid overdose deaths have recently stabilized or declined in parts of the southeastern United States, injection-related infections (IRIs) continue to rise. This evolving syndemic of substance use disorder (SUD) and infectious complications is often under-identified due to limitations in ICD-10 coding, provider documentation variability, and underreporting of injection drug use. Consequently, health systems lack reliable tools to quantify IRI burden and evaluate trends.
Objectives: To develop and validate an ICD-10–based algorithm to accurately identify four IRI phenotypes (endocarditis, vertebral osteomyelitis/epidural abscess, bacteremia & deep infections, and skin & soft tissue infections (SSTI)) and to quantify its diagnostic performance against gold-standard manual chart review.
Methods: We conducted a retrospective analysis of a multi-hospital electronic medical record dataset within a single health system from January 1, 2023 to January 1, 2025. Phenotype-specific ICD-10 codes for IRI diagnoses were combined with SUD-related ICD-10 codes and temporally linked evidence of SUD using an iterative modeling approach. Validation was performed through blinded manual chart review by two independent reviewers using predefined adjudication criteria. Inter-rater reliability was assessed using Cohen’s kappa. Algorithm performance was summarized using positive predictive value (PPV).
Results: The algorithm identified 710 true positive, 158 suspected positive, and 175 false positive encounters. Strict PPV was 68%, and inclusive PPV was 83%. Inter-rater reliability was strong (κ = 0.86). Over the study period, IRI encounters increased, while opioid overdose admissions remained stable.
Conclusions: Injection-related infections are rising despite stabilization of overdose admissions in this southeastern health system. A validated ICD-10 algorithm enables scalable identification of IRIs without reliance on structured data fields or natural language processing.
Recommendations: This validated algorithm may strengthen public health surveillance, inform resource allocation, support addiction medicine integration and infectious disease service planning, and enable health system–level monitoring of injection-related infection trends as the opioid crisis evolves beyond overdose mortality alone.
https://digitalscholar.lsuhsc.edu/dohd/2026/2026/7