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Researchers propose social network modeling to fight hospital infections

Date:
October 22, 2013
Source:
University of Maryland
Summary:
Researchers are helping to prevent costly and deadly infections acquired by hospitalized patients by using computer models that simulate interactions between patients and health care workers to determine if these interactions are a source for spreading multi-drug resistant organisms.

In these illustrations of dense (left) and sparse (right) patient ICU social networks, patients that share a nurse are connected by a link, while patients that share a physician have the same color (black/grey).
Credit: University of Maryland

Two researchers at the University of Maryland's Robert H. Smith School of Business have teamed up with a researcher at American University to develop a framework to help prevent costly and deadly infections acquired by hospitalized patients. According to the Department of Health and Human Services (HHS), these transmissions strike one out of every 20 inpatients, drain billions of dollars from the national health care system and cause tens of thousands of deaths annually.

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The research of Sean Barnes, Smith School assistant professor of operations management; Bruce Golden, the Smith School's France-Merrick Chair in Management Science; and Edward Wasil of American's Kogod School of Business, utilized computer models that simulate the interactions between patients and health care workers to determine if these interactions are a source for spreading multi-drug resistant organisms (MDROs). Their study shows a correlation of a "sparse, social network structure" with low infection transmission rates.

This study comes in advance of HHS' 2015 launch and enforcement of a new initiative that penalizes hospitals at an estimated average rate of $208,642 for violating specific requirements for infection control. In response, the study's authors have introduced a conceptual framework for hospitals to model their social networks to predict and minimize the spread of bacterial infections that often are resistant to antibiotic treatments.

The authors manipulated and tracked the dynamics of the social network in a mid-Atlantic hospital's intensive care unit. They focused on interactions between patients and health care workers -- primarily nurses -- and the multiple competing factors that can affect transmission.

"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 next step is to enable hospitals to adapt this framework, which is based on maximizing staff-to-patient ratio to ensure fewer nurses and physicians come in contact with each patient, especially high-risk patients.

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


Story Source:

The above story is based on materials provided by University of Maryland. Note: Materials may be edited for content and length.


Journal Reference:

  1. Sean Barnes, Bruce Golden, Edward Wasil. Exploring the effects of network structure and healthcare worker behavior on the transmission of hospital-acquired infections. IIE Transactions on Healthcare Systems Engineering, 2012; 2 (4): 259 DOI: 10.1080/19488300.2012.736120

Cite This Page:

University of Maryland. "Researchers propose social network modeling to fight hospital infections." ScienceDaily. ScienceDaily, 22 October 2013. <www.sciencedaily.com/releases/2013/10/131022170826.htm>.
University of Maryland. (2013, October 22). Researchers propose social network modeling to fight hospital infections. ScienceDaily. Retrieved October 30, 2014 from www.sciencedaily.com/releases/2013/10/131022170826.htm
University of Maryland. "Researchers propose social network modeling to fight hospital infections." ScienceDaily. www.sciencedaily.com/releases/2013/10/131022170826.htm (accessed October 30, 2014).

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