ArticleDrug and alcohol dependence2020
Validity of ICD-based algorithms to estimate the prevalence of injection drug use among infective endocarditis hospitalizations in the absence of a reference standard.
Article in Drug and alcohol dependence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Accuracy of data routinely collected by Australian hospitals for identifying infective endocarditis, causative organisms and clinical outcomes: a diagnostic accuracy study.Internal medicine journal · 2026Article
- Large Language Models Accurately Identify People Who Inject Drugs From Infectious Diseases Discharge Summaries in an Australian Hospital.Drug and alcohol review · 2026Article
- Burden of Injection Drug Use-Related Infection Hospitalizations in Tennessee, 2016-2023.Open forum infectious diseases · 2026Article
- Sensitivity and Specificity of Natural Language Processing Systems for Identification of Hospitalized People Who Use Drugs.Open forum infectious diseases · 2025Article
- The Clinical and Molecular Characteristics of Community-AssociatedOpen forum infectious diseases · 2025Article
- Sexually Transmitted Infection (STI) Incidence, STI Screening, and Human Immunodeficiency Virus Preexposure Prophylaxis Uptake in United States Veterans With Opioid Use Disorder in Long Island, New York.Open forum infectious diseases · 2024Article
- Impact of Potential Case Misclassification by Administrative Diagnostic Codes on Outcome Assessment of Observational Study for People Who Inject Drugs.Open forum infectious diseases · 2024Article
- Five-Year Cardiovascular Outcomes after Infective Endocarditis in Patients with versus without Drug Use History.Journal of personalized medicine · 2022Article
- Natural Language Processing and Machine Learning to Identify People Who Inject Drugs in Electronic Health Records.Open forum infectious diseases · 2022Article
- Misclassification Error-Adjusted Prevalence of Injection Drug Use Among Infective Endocarditis Hospitalizations in the United States: A Serial Cross-Sectional Analysis of the 2007-2016 National Inpatient Sample.American journal of epidemiology · 2021Article
- HIV detection by an emergency department HIV screening program during a regional outbreak among people who inject drugs.PloS one · 2021Article
- Use of ICD-10 Codes for Identification of Injection Drug Use-Associated Infective Endocarditis Is Nonspecific and Obscures Critical Findings on Impact of Medications for Opioid Use Disorder.Open forum infectious diseases · 2020Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundInternational Classification of Diseases (ICD) code algorithms are routinely used to estimate the frequency of illicit injection drug use (IDU)-associated hospitalizations in administrative health datasets despite a lack of evidence regarding their validity. We aimed to measure the sensitivity and specificity of ICD code algorithms used to estimate the prevalence of current/recent IDU among infective endocarditis (IE) hospitalizations without a reference standard.
methodsWe reviewed medical records of 321 patients aged 18-64 years old from an urban academic hospital with an IE diagnosis between 2007 and 2017. Diagnostic tests for IDU included self-reported IDU in medical records; a drug use, abuse and dependence (UAD) ICD algorithm; a Hepatitis C Virus (HCV) ICD algorithm; and a combination drug UAD/HCV ICD algorithm. Sensitivity, specificity and the misclassification error (ME)-adjusted IDU prevalence were estimated using Bayesian latent class models.
resultsThe combination algorithm had the highest sensitivity and lowest specificity. Sensitivity increased for the drug UAD algorithm in the ICD-10 period compared to the ICD-9 period. The ME-adjusted current/recent IDU prevalence estimated using the drug UAD and HCV algorithms was 23 % (95 % Bayesian credible interval: 16 %, 31 %). The unadjusted prevalence estimate from the drug UAD algorithm underestimated the ME-adjusted prevalence, while the combination algorithm overestimated it.
conclusionThe validity of ICD code algorithms for IDU among IE hospitalizations is imperfect and differs between ICD-9 and ICD-10. Commonly used ICD-based algorithms could lead to substantially biased prevalence estimates in IDU-associated hospitalizations when using administrative health data.
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