Hospital-acquired infections (HAI) play a key component in the modern hospital, with an increased emphasis on lowering rates for Medicare payments and improved patient outcomes. Hospitals have been trying to capture data on the subject, and the University of Michigan-Michigan Medicine (UM) has been at the forefront of that effort.
In their latest paper, a joint effort with RAND that published this week in the Journal of Hospital Medicine, UM and RAND researchers suggest that the massive effort to reduce HAIs has been missing a key element: hospital occupancy and staffing ratios. None of the tracking measures take into account how full a hospital was during the hospitalization that the patient acquired the infection; metrics like the percentage of available beds with patients in them, and therefore how thinly-stretched the staff were, have yet to be taken into account when measuring HAI-risk.
The researchers shared the initial findings from using the approach on real-world data, related to the digestive tract infection known as “C. diff” or Clostridium difficile. The study used data from 558,829 patient discharges at 327 hospitals across California, between 2008 and 2012. It focused on patients who had come to the hospitals’ emergency rooms for care for a heart attack, heart failure or pneumonia.
In all, 2,045 patients developed a C. diff infection after they reached the hospital. The researchers adjusted for many factors that differed among all the patients, including age, gender, income, education and more. The authors then compared C. diff infection rates with hospital occupancy information, and looked for a correlation between the two factors.
The researchers expected to find that as occupancy went up, so would the infection rates, as staff would be stretched thinner and cut corners to compensate. But what they found was more complicated.
The team broke occupancy into four levels: low (0 to 25 percent), two classes of moderate (25 percent to 50 percent and 51 percent to 75 percent), and high (76 percent to completely full). A patient’s C. diff infection risk was highest when the hospital was in the middle (moderate) range of occupancy on the day the patient was admitted. And when the researchers looked at the average occupancy over the patient’s stay, the risk of C. diff infection was more than three times higher when the hospital was moderately full (between 25 percent and 75 percent), compared with less than 25 percent or more than 75 percent occupancy.
“Our initial results indicate a complex relationship between hospital occupancy and outcomes, and merit further evaluation,” including analysis of hospital protocols that might be triggered or modified when a hospital is in high or low occupancy, says Mahshid Abir, M.D., M.Sc., the lead author of the study.
“The theory that infection rates will go up with occupancy, because of staff cutting corners with steps like handwashing, may seem logical but this model shows it’s not as simple as that,” says Abir, who leads the UM Acute Care Research Unit and is a member of the UM Institute for Healthcare Policy and Innovation. “The impacts of emergency department crowding on patient outcomes have been studied extensively, but the effects of occupancy levels on inpatients has been neglected – despite the fact that a crowded ED is often a function of high inpatient occupancy. Some hospitals may be implementing operational factors during high occupancy that improve HAIs; we need to study what those are.”
Based on their initial findings, Abir and her co-authors call for collection of hospital occupancy data by infection control officers, so that more precise measurements of occupancy can be used when examining HAIs and other preventable threats to patient health and safety.
Editor’s Note: For more information about preventing C. diff at your facility, check out “3 Ways to Knock C. diff Rates Down to Zero.”