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Impact of Potential Case Misclassification by Administrative Diagnostic Codes on Outcome Assessment of Observational

David Goodman-Meza1,2,3, Michihiko Goto4,5, Anabel Salimian1

  • 1Division of Infectious Diseases, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.

Open Forum Infectious Diseases
|February 21, 2024
PubMed
Abstract

Insights

Medications for opioid use disorder (MOUD) improve survival for people who inject drugs (PWID) hospitalized with infections. Natural language processing (NLP) identified this benefit, unlike ICD codes which showed no significant effect.

Area of Science:

  • Clinical Medicine
  • Public Health
  • Infectious Diseases

Background:

  • Initiating medications for opioid use disorder (MOUD) during hospitalization may improve outcomes for people who inject drugs (PWID) with infections.
  • Previous studies often used International Classification of Diseases (ICD) codes to identify PWID, but these codes can be inaccurate due to misclassification.
  • This misclassification may bias analyses of MOUD effectiveness.

Purpose of the Study:

  • To investigate the impact of misclassification bias from ICD codes on the analysis of MOUD outcomes in hospitalized PWID.
  • To compare the effectiveness of MOUD on 365-day mortality using different methods for identifying PWID.

Main Methods:

  • A cohort of 36,868 patients with *Staphylococcus aureus* bacteremia from 2003-2014 in Veterans Affairs hospitals was analyzed.
  • Two algorithms were used to identify PWID: an ICD code-based algorithm and a natural language processing (NLP) algorithm analyzing admission notes.
  • Mixed-effects Cox regression models assessed the association between inpatient MOUD receipt and 365-day all-cause mortality.

Main Results:

  • NLP identified 2,389 PWID, while ICD codes identified 6,804 PWID.
  • In the NLP-identified cohort, inpatient MOUD was associated with a significant protective effect on 365-day survival (aHR, 0.48; P < .01).
  • No significant effect of MOUD on survival was found in the ICD code-identified cohort (aHR, 1.00; P = .99).

Conclusions:

  • MOUD demonstrated a protective effect against all-cause mortality when PWID were identified using NLP.
  • The protective effect of MOUD was not significant when PWID were identified using ICD codes, highlighting potential bias.
  • Accurate identification of PWID is crucial for evaluating the effectiveness of MOUD in improving patient outcomes.

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