C. difficile Infections
3,669general acute care hospitals reported in 2018
Reported C. difficile Infections Among Hospitalized Patients
196,969C. difficile infections in 2018
Changes over Time
29%significant decrease in SIR from 2015 national baseline to 2018 (lower SIRs are better)
C. difficile Infections
When a person takes antibiotics, good bacteria in the gut are destroyed for several months. During this time, patients can get sick from Clostridioides difficile (C. difficile), bacteria that often cause serious or even deadly diarrhea. People who have other illnesses or conditions requiring prolonged use of antibiotics, and the elderly, are at greater risk of acquiring this disease particularly within a healthcare setting. Preventing HAIs such as C. difficile infections is a CDC priority. The CDC provides national data on infection rates through the National Healthcare Safety Network. Standardized Infection Ratios (SIRs) are summary statistics that allow monitoring of HAIs over time.
The Standardized Infection Ratio for C. difficile Infections was 0.71 across general acute care hospitals in 2018.
- CDI Infection
- Information for Patients
- A Guide to the Standardized Infection Ratio
- Healthcare-Associated Infections Data and Statistics
- HAI Data Summary: Story of Progress 2006-2016
- National and State Healthcare-Associated Infections Progress Report
- FAQs about the HAI Progress Report
- Antibiotic Resistance Threats in the United States, 2019
- Data profiles for Healthcare-Associated Infections include information for Central Line-Associated Bloodstream Infection (CLABSI), Catheter-Associated Urinary Tract Infection (CAUTI), Surgical Site Infections (SSI), Clostridioides difficile (C. difficile) infections, MRSA Bacteremia, and Ventilator-Associated Events (VAE).
- All HAI data provided on this page are maintained by the CDC's National Healthcare Safety Network (NHSN).
- Data are only displayed for U.S. states/territories for which at least 5 facilities reported an HAI in the given report year.
- HAI information available in the Patient Safety Portal include data from 2015 through 2018.
- Map legends are classified using the Jenks Natural Breaks method.
- See the Current HAI Progress Report Technical Appendix for the full methodology and details about the data. Past HAI Progress Reports are described in the Data Archive.