A health informatics team at UC San Francisco has used electronic health records to track down a source of a common hospital-acquired infection by tracing the movements of more than 85,000 patients over a three-year period.
In a study published this week in JAMA Internal Medicine, the UCSF researchers described how they used time and location stamps – which are entered in EHRs whenever patients undergo procedures, or are moved to different parts of the hospital – to map 435,000 patient location changes throughout the UCSF Medical Center between 2013 and 2016. Their target was a bacterium known as Clostridium difficile (colloquially called “C. diff”), the leading cause of infections in health care settings. The complex interactions and location changes that take place in hospitals often make it difficult to identify the source of these infections.
“During hospitalization, patients visit many procedural and diagnostic common areas, presenting opportunities for contact with contaminated surfaces. However, these potential exposures are not typically captured in analyses evaluating disease transmission,” the study’s abstract notes. “EHR data allow us to track patients in time and space, but these data are not typically leveraged for infection control quality improvement efforts. We evaluated whether using a room within 24 hours of a patient with CDI was associated with increased risk of CDI in specific areas across our hospital.”
Sara Murray, M.D., M.A.S., assistant professor of medicine at UCSF, and her team were able to use the data to construct a map of where all patients with C. diff infections had travelled in the hospital over the course of the three-year study period. Murray and colleagues then looked to see what happened to the patients who visited the same locations within 24 hours of an infected patient, the period in which that location was considered, for the purposes of the study, to be “potentially contaminated.”
Patients who passed through a space while it was potentially contaminated were considered “exposed” to C. diff. The team then calculated the odds of C. diff infection as a result of exposure by comparing infection rates over the next two months for those considered exposed to rates for those who passed through the same spaces at a time it hadn’t recently been used by a patient with C. diff. This controlled for the different characteristics of patients who visited these spaces, which could confound the results.
The analysis used in the new study revealed that one location – a particular CT scanner in the Emergency Department – was a significant source of exposure-related infections. Patients who entered that scanner within 24 hours after C. diff-positive patients were more than twice as likely to become infected with the bacterium themselves: 4 percent of the patients who were considered exposed in the scanner contracted C. diff within two months; the overall rate of infection for patients who passed through the scanner was 1.6 percent.
The hospital moved swiftly to standardize the cleaning practices for that scanner to match those used in other radiology suites. No other sites at the hospital raised concerns regarding C. diff transmission in the three years under review.
A story on UCSF’s web site quoted Nirai Sehgal, M.D., MPH, vice president and chief quality officer for UCSF Health and professor of medicine at UCSF, who was not involved in the study. “This shows the potential for what can happen when thoughtful data scientists leverage electronic health records to tackle a common health care problem,” Sehgal said. “Their novel approach helped bolster our infection prevention strategies but also demonstrated the answers that can come from studying the vast sources of data generated through a patient's hospitalization.”
