Validation of electronic health record data to identify hospital-associated Clostridioides difficile infections for retrospective research

Michael J Ray; Kathleen L Lacanilao; Maela Robyne Lazaro; Luke C Strnad; Jon P Furuno; Kelly Royster; Jessina C McGregor

doi:10.1017/ice.2024.140

Validation of electronic health record data to identify hospital-associated Clostridioides difficile infections for retrospective research

Infect Control Hosp Epidemiol. 2024 Oct 16;45(12):1-3. doi: 10.1017/ice.2024.140. Online ahead of print.

Authors

Michael J Ray^{1

2}, Kathleen L Lacanilao¹, Maela Robyne Lazaro¹, Luke C Strnad^{2

3}, Jon P Furuno¹, Kelly Royster⁴, Jessina C McGregor^{1

2}

Affiliations

¹ Oregon State University College of Pharmacy, Department of Pharmacy Practice, Portland, OR, USA.
² Oregon Health & Science University-Portland State University School of Public Health, Portland, OR, USA.
³ Oregon Health & Science University School of Medicine, Division of Infectious Diseases, Portland, OR, USA.
⁴ Legacy Health, Pharmacy, Portland, OR, USA.

Abstract

Clostridioides difficile 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.