Validity of International Classification of Diseases codes in identifying illicit drug use target conditions using medical record data as a reference standard: A systematic review.
Background: The twenty-first century opioid crisis has spurred interest in using International Classification of Diseases (ICD) code algorithms to identify patients using illicit drugs from administrative healthcare data. We conducted a systematic review of studies that validated ICD code algorithms...
| Publicado en: | Drug & Alcohol Dependence Vol. 208 |
|---|---|
| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Mar2020
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=141844422&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141844422 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03768716 3S6 jtl: Drug & Alcohol Dependence issn: 03768716 maglogo: N pubinfo: dt: Mar2020 vid: 208 pid: 1004 pub: Elsevier B.V. artinfo: ui: 141844422 141844422 NLM31982637 141844422 10.1016/j.drugalcdep.2019.107825 NLM31982637 141844422 ppct: 1 formats: tig: atl: Validity of International Classification of Diseases codes in identifying illicit drug use target conditions using medical record data as a reference standard: A systematic review. aug: au: McGrew, Kaitlin M. Homco, Juell B. Garwe, Tabitha Dao, Hanh Dung Williams, Mary B. Drevets, Douglas A. Jafarzadeh, S. Reza Zhao, Yan Daniel Carabin, Hélène affil: Department of Biostatistics & Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States sug: subj: Resource Databases Standards International Classification of Diseases Standards Substance Use Disorders Diagnosis Medical Records Standards Human Substance Use Disorders Epidemiology Reproducibility of Results Weights and Measures Algorithms Ferrans and Powers Quality of Life Index ab: Background: The twenty-first century opioid crisis has spurred interest in using International Classification of Diseases (ICD) code algorithms to identify patients using illicit drugs from administrative healthcare data. We conducted a systematic review of studies that validated ICD code algorithms for illicit drug use against a reference standard of medical record data.Methods: Systematic searches of MEDLINE, EMBASE, PsycINFO, and Web of Science were conducted for studies published between 1980 and 2018 in English, French, Italian, or Spanish. We included validation studies of ICD-9 or ICD-10 code algorithms for an illicit drug use target condition (e.g., illicit drug use, abuse, or dependence (UAD), illicit drug use-related complications) given the sensitivity or specificity was reported or could be calculated. Bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies Version 2 (QUADAS-2) tool.Results: Six of the 1210 articles identified met the inclusion criteria. For validation studies of broad UAD (n = 4), the specificity was nearly perfect, but the sensitivity ranged from 47% to 83%, with higher sensitivities tending to occur in higher prevalence populations. For validation studies of injection drug use (IDU)-associated infective endocarditis (n = 2), sensitivity and specificity were poor due to the lack of an ICD code for IDU. For all six studies, the risk of bias for the QUADAS-2 "reference standard" and "flow/timing domains" was scored as "unclear" due to insufficient reporting.Conclusions: Few studies have validated ICD code algorithms for illicit drug use target conditions, and available evidence is challenging to interpret due to inadequate reporting. PROSPERO Registration: CRD42019118401. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|