Researchers propose social network modeling to fight hospital infections. 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.
Full Press Release Below.
SOURCE: UMD's Robert H.
Smith School of Business
COLLEGE PARK, Md. (Oct. 22,2013)– 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.
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.
The study, "Exploring the
Effects of Network Structure and Healthcare Worker Behavior on the
Transmission of Hospital-Acquired Infections," appears in a recent issue
of the peer-reviewed IIE Transactions on Healthcare Systems Engineering.
The study was partially funded by the Robert H. Smith School of Business
Center for Health Information and Decision Systems.
A full copy of the study is available
at: http://www.tandfonline.com/doi/abs/10.1080/19488300.2012.736120?journalCode=uhse20#.UmV9WPmsjlN
Contact:
Sean Barnes
Co-author/Researcher
UMD's Robert H. Smith School of Business
sbarnes@rhsmith.umd.edu
Greg Muraski
301-892-0973
gmuraski@rhsmith.umd.edu
/PRNewswire-USNewswire -- Oct. 22,
2013/
SOURCE Robert H. Smith School of
Business
Web Site: http://www.rhsmith.umd.edu
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Tuesday, October 22, 2013
Health Tech News: Researchers propose social network modeling to fight hospital infections
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