Researchers at the University of Maryland and American University have developed a framework to help prevent deadly infections in hospital patients. They found that a "sparse social network structure," where each patient encountered only a few care providers was correlated with low infection transmission rates.

Researchers Sean Barnes, Bruce Golden and Edward Wasil used computers simulating the interactions between patients and healthcare workers to determine how they helped spread infectious organisms. They manipulated and tracked the social network interactions in an intensive care unit, focusing on the interactions between patients and healthcare workers, primarily nurses.

In an effective sparse network, fewer patients share a nurse, whereas in a potentially harmful dense network, more patients share a nurse.

"The basic reality is that healthcare workers frequently cover for one another due to meetings, breaks and sick leave," said Barnes. "These factors, along with the operating health care-worker-to-patient ratios and patient lengths of stay, can significantly affect transmission in an ICU...But they also can be better controlled."

The researchers developed a framework based on making sure fewer nurses and doctors have contact with each patient, especially those at high risk of infection. This conceptual framework allows hospitals to model their social networks to predict and minimize the spread of antibiotic-resistant bacterial infections.

Barnes believes hospitals could adopt this framework. "The health care industry's electronic records movement could soon generate data that captures the structure of patient-healthcare worker interactions in addition to multiple competing, related factors that can affect MDRO transmission," he said.

Antibiotic-resistant bacterial transmissions affect one in 20 inpatients, cause tens of thousands of deaths yearly, and cost billions of dollars, according to the U.S. Department of Health and Human Services.

The study is called "Exploring the Effects of Network Structure and Healthcare Worker Behavior on the Transmission of Hospital-Acquired Infections" and appears in a recent issue of IIE Transactions on Healthcare Systems Engineering.