Comparison of Medicare claims-based <i>Clostridioides difficile</i> infection epidemiologic case classification algorithms to medical record review by the Emerging Infections Program using a linked cohort, 2016–2021

ICD-10-CM codes in Medicare claims data had high sensitivity compared to laboratory-confirmed CDI reported to EIP. Claims-based epidemiologic classification algorithms had moderate concordance with EIP classification of onset location. Misclassification of CDI onset location using Medicare algorithms may bias findings of claims-based CDI studies.

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Publication Details

Journal
Infection Control and Hospital Epidemiology
Published
2025-03-26
DOI
https://doi.org/10.1017/ice.2024.204
Citations
1
Primary Topic
Clostridium difficile and Clostridium perfringens research
Type
article
Field-Weighted Citation Impact
1.40
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article

Comparison of Medicare claims-based Clostridioides difficile infection epidemiologic case classification algorithms to medical record review by the Emerging Infections Program using a linked cohort, 2016–2021

Lauren Korhonen, Scott K. Fridkin, Ghinwa Dumyati, Jill Szydlowski et al.
1 citations
Infection Control and Hospital Epidemiology
Clostridium difficile and Clostridium perfringens research
1.40
article

Comparison of Medicare claims-based Clostridioides difficile infection epidemiologic case classification algorithms to medical record review by the Emerging Infections Program using a linked cohort, 2016–2021

Lauren Korhonen, Scott K. Fridkin, Ghinwa Dumyati, Jill Szydlowski, Dustin W. Currie, James Baggs, Sujan Reddy, Kelly M Hatfield, Chantal Lewis, Alice Guh, Sophia V. Kazakova, Dana Goodenough, Joseph D. Lutgring, Danyel Olson, Maria Correa, Christopher Wilson
article en
1 citations

Abstract

ICD-10-CM codes in Medicare claims data had high sensitivity compared to laboratory-confirmed CDI reported to EIP. Claims-based epidemiologic classification algorithms had moderate concordance with EIP classification of onset location. Misclassification of CDI onset location using Medicare algorithms may bias findings of claims-based CDI studies.

Infection Control and Hospital EpidemiologyVol. 46(5)
Centers for Disease Control and Prevention (US), Emory University (US), University of Rochester Medical Center (US), Yale University (US), Centers for Disease Control and Prevention (UG), Tennessee Department of Health (US), CDC Foundation (US)
Good health and well-being
Openalex Percentile: Top 23%
Clostridium difficile and Clostridium perfringens research
1.40
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