Validity of ICD-based algorithms to estimate the prevalence of injection drug use among infective endocarditis hospitalizations in the absence of a reference standard.

Background: International 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 sensi...

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Publicado en:Drug & Alcohol Dependence Vol. 209
Autores principales: McGrew, Kaitlin M., Carabin, Hélène, Garwe, Tabitha, Jafarzadeh, S. Reza, Williams, Mary B., Zhao, Yan Daniel, Drevets, Douglas A.
Formato: research Journal Article
Publicado: Elsevier B.V. Apr2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2020
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      pub: Elsevier B.V.
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        10.1016/j.drugalcdep.2020.107906
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        atl: Validity of ICD-based algorithms to estimate the prevalence of injection drug use among infective endocarditis hospitalizations in the absence of a reference standard.
      aug:
        au:
          McGrew, Kaitlin M.
          Carabin, Hélène
          Garwe, Tabitha
          Jafarzadeh, S. Reza
          Williams, Mary B.
          Zhao, Yan Daniel
          Drevets, Douglas A.
        affil: Department of Biostatistics & Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, United States
      sug:
        subj:
          Endocarditis Epidemiology
          International Classification of Diseases Standards
          Algorithms
          Substance Abuse, Intravenous Epidemiology
          Hospitalization Trends
          Endocarditis Diagnosis
          Prevalence
          Young Adult
          Reproducibility of Results
          Human
          Substance Abuse, Intravenous Diagnosis
          Probability
          Cross Sectional Studies
          Adult
          Female
          Middle Age
          Male
          Weights and Measures
          Adolescence
          Retrospective Design
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Adolescent: 13-18 years
          Female
          Male
      ab: Background: International 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.Methods: We 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.Results: The 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.Conclusion: The 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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