Validation of electronic health record data to identify hospital-associated <i>Clostridioides difficile</i> infections for retrospective research
<i>Clostridioides difficile</i> infection (CDI) research relies upon accurate identification of cases when using electronic health record (EHR) data. We developed and validated a multi-component algorithm to identify hospital-associated CDI using EHR data and determined that the tandem of CDI-specific treatment and laboratory testing has 97% accuracy in identifying HA-CDI cases.
Authors
- Michael Ray (ORCID: https://orcid.org/0000-0001-7670-9639)
- Jessina C. McGregor (ORCID: https://orcid.org/0000-0002-6093-5444)
- Jon P. Furuno (ORCID: https://orcid.org/0000-0002-8853-5733)
- Kelly Royster
- Kathleen L Lacanilao
- Maela Robyne Lazaro
- Luke Strnad (ORCID: https://orcid.org/0000-0002-1583-9453)
Institutions
- Portland State University (US)
- Oregon State University (US)
- Legacy Health (US)
- Oregon Health & Science University (US)
Publication Details
- Journal
- Infection Control and Hospital Epidemiology
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1017/ice.2024.140
- Citations
- 3
- Primary Topic
- Clostridium difficile and Clostridium perfringens research
- Type
- article
- Field-Weighted Citation Impact
- 1.17
Funders
- Oregon Health and Science University
- National Institutes of Health