Impact of Potential Case Misclassification by Administrative Diagnostic Codes on Outcome Assessment of Observational Study for People Who Inject Drugs

David Goodman-Meza; Michihiko Goto; Anabel Salimian; Steven Shoptaw; Alex A T Bui; Adam J Gordon; Matthew B Goetz

doi:10.1093/ofid/ofae030

Back

Impact of Potential Case Misclassification by Administrative Diagnostic Codes on Outcome Assessment of Observational Study for People Who Inject Drugs

Journal article

Open access

Peer reviewed

Impact of Potential Case Misclassification by Administrative Diagnostic Codes on Outcome Assessment of Observational Study for People Who Inject Drugs

David Goodman-Meza, Michihiko Goto, Anabel Salimian, Steven Shoptaw, Alex A T Bui, Adam J Gordon and Matthew B Goetz

Open forum infectious diseases, Vol.11(2), ofae030

02/01/2024

DOI: 10.1093/ofid/ofae030

PMCID: PMC10878055

PMID: 38379573

Files and links (1)

url

https://doi.org/10.1093/ofid/ofae030View

Published (Version of record) Open Access

Abstract

Abstract Introduction Initiation of medications for opioid use disorder (MOUD) within the hospital setting may improve outcomes for people who inject drugs (PWID) hospitalized due to an infection. Many studies used International Classification of Diseases (ICD) codes to identify PWID, although these may be misclassified and thus, inaccurate. We hypothesized that bias from misclassification of PWID using ICD codes may impact analyses of MOUD outcomes. Methods We analyzed a cohort of 36,868 cases of patients diagnosed with Staphylococcus aureus bacteremia at 124 US Veterans Health Administration (VHA) hospitals between 2003 and 2014. To identify PWID, we implemented an ICD code-based algorithm and a natural language processing (NLP) algorithm for classification of admission notes. We analyzed outcomes of prescribing MOUD as an inpatient using both approaches. Our primary outcome was 365-day all-cause mortality. We fit mixed effects Cox regression models with receipt or not of MOUD during the index hospitalization as the primary predictor and 365-day mortality as the outcome. Results NLP identified 2,389 cases as PWID, while ICD codes identified 6,804 cases as PWID. In the cohort identified by NLP, receipt of inpatient MOUD was associated with a protective effect on 365-day survival (AHR 0.48, 95%CI 0.29-0.81, p<0.01) compared to those not receiving MOUD. There was no significant effect of MOUD receipt in the cohort identified by ICD codes (AHR 1.00, 95%CI 0.77-1.30, p=0.99). Conclusion MOUD was protective of all-cause mortality when NLP was used to identify PWID, but not significant when ICD codes were used to identify the analytic subjects.

Details

Title: Subtitle: Impact of Potential Case Misclassification by Administrative Diagnostic Codes on Outcome Assessment of Observational Study for People Who Inject Drugs
Creators: David Goodman-Meza
Michihiko Goto - University of Iowa
Anabel Salimian - University of California, Los Angeles
Steven Shoptaw - University of California, Los Angeles
Alex A T Bui
Adam J Gordon - VA Salt Lake City Healthcare System
Matthew B Goetz - University of California, Los Angeles
Resource Type: Journal article
Publication Details: Open forum infectious diseases, Vol.11(2), ofae030
DOI: 10.1093/ofid/ofae030
PMID: 38379573
PMCID: PMC10878055
NLM abbreviation: Open Forum Infect Dis
ISSN: 2328-8957
eISSN: 2328-8957
Publisher: Oxford University Press
Grant note: DOI: 10.13039/100000026, name: National Institute on Drug Abuse; DOI: 10.13039/100018192, name: CHIPTS; DOI: 10.13039/100007185, name: UCLA; DOI: 10.13039/100007813, name: Center for AIDS Research
Language: English
Electronic publication date: 01/16/2024
Date published: 02/01/2024
Academic Unit: Internal Medicine
Record Identifier: 9984548411302771

Metrics

4 Record Views

4 Times Cited - Web of Science