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Study: Vital Sign Information in EHR Can Reduce Sepsis Risk

March 17, 2014
by Gabriel Perna
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Researchers at UC Davis Medical Center say that routine data found in an electronic health record (EHR) of a hospitalized patient can be used to reduce the risk of sepsis.

The researchers analyzed data from the EHRs of 741 patients with sepsis at UC Davis Medical Center during 2010. What they found was the inclusion of vital signs — blood pressure, respiratory rate, and temperature — and serum white blood cell count in the EHR accurately predicted high lactate levels and sepsis. In particular, lactate levels, blood pressure, and respiratory rate were determined to be the three measures, the researchers say, which can pinpoint the likelihood that a patient will die from the disease.

“EHRs have become essential resources for providing relevant information on patients’ medical histories and improving the quality of care,” study co-author Tim Albertson, chair of UC Davis Department of Internal Medicine, said in a statement. “We have shown that they can also be powerful resources for identifying best practices in medicine and reducing patient mortality.”

According to the UC Davis researchers, patients are rarely screened for blood lactate levels because sepsis is very hard to distinguish in its early stages. The blood test also lacks specificity, as many patients with elevated lactate do not have sepsis.

The team is looking to discover a sepsis-risk algorithm that can be automatically calculated in the EHR. “Rather than using a ‘gut-level’ approach in an uncertain situation, physicians can instead use a decision-making tool that 'learns' from patient histories to identify health status and probable outcomes. Another benefit of the sepsis predictor is that it is based on routine measures, so it can be used anywhere — on the battlefield or in a rural hospital in a third-world country," stated Ilias Tagkopoulos, assistant professor of computer science at UC Davis and senior author of the study.

The study is published in the current issue of the Journal of the American Medical Informatics Association.

Read the source article at Health News



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