Comparison of coding data with clinical diagnosis of antibiotic-resistant healthcare-associated infections

Seamus Horan1, Vivian K Y Leung2, Paul M Kinsella3

  • 1Victorian Infectious Diseases Service, The Royal Melbourne Hospital, Parkville, Australia.

PubMed
Abstract

Insights

International Classification of Disease (ICD) coding data for detecting multidrug-resistant organism healthcare-associated infections (MRO HAIs) has limited accuracy. ICD coding is unlikely to be sufficient for guiding prevention or quality metrics.

Area of Science:

  • Healthcare epidemiology
  • Infectious disease surveillance
  • Medical informatics

Background:

  • International Classification of Disease (ICD) coding is increasingly used for detecting hospital-acquired complications.
  • Evidence regarding the accuracy of ICD coding for specific complications like multidrug-resistant organism healthcare-associated infections (MRO HAIs) is limited.
  • MRO HAIs are associated with increased patient morbidity and mortality.

Purpose of the Study:

  • To compare the accuracy of ICD coding against clinical diagnosis for identifying MRO HAIs.
  • To evaluate the positive predictive value (PPV) and sensitivity of ICD codes for MRO HAIs.

Main Methods:

  • Retrospective review of hospital admissions coded with MRO HAIs in 2023.
  • Calculation of PPV for MRO HAI codes, including a secondary calculation excluding expected resistance patterns.
  • Estimation of coding sensitivity using cases of healthcare-associated ESBL bacteremia.

Main Results:

  • The overall PPV for MRO HAI codes was 62%.
  • Excluding specific, clinically irrelevant resistance patterns improved the PPV to 73%.
  • The sensitivity for detecting healthcare-associated ESBL bacteremia was low at 27%.

Conclusions:

  • ICD coding data alone is likely insufficient for accurately determining the presence of MRO HAIs.
  • The accuracy of current ICD coding practices may not support their use in guiding infection prevention strategies.
  • MRO HAI coding lacks the reliability needed for use as a quality metric.

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