About: A passive monitoring tool using hospital administrative data enables earlier specific detection of healthcare-acquired infections

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A passive monitoring tool using hospital administrative data enables earlier specific detection of healthcare-acquired infections
Creator	Koehly, Laura Marcum, Christopher Reed-Tsochas, Felix Rewley, Jeffrey
Source	Elsevier; Medline; PMC
abstract	BACKGROUND: Healthcare-associated infections impose a significant burden on the health care system. Current methods for detecting these infections are constrained by combinations of high cost, long processing times, and imperfect accuracy, reducing their effectiveness. METHODS: We examine whether the quantity of time a patient spends in a ward with other patients clinically-suspected of infection, which we call co-presence, can be used as a tool to predict subsequent healthcare-associated infection. Compared to contact tracing, this leverages passively-collected electronic data rather than manually-collected data, allowing for improved monitoring. We abstracted all 133,304 inpatient records between 2011 and 2015 from a healthcare system in the UK. We calculate the AUROC for each of five pathogens based on co-presence time, the sensitivity and specificity for the test, and how much earlier co-presence would have predicted infection for the true positives. FINDINGS: Across the five pathogens, AUROC ranged from 0.92 to 0.99, and was 0.52 for the negative control. Optimal cut-points of co-presence ranged from 25 to 59 hours, and would have led to detection of true positives up to an average of one day earlier. INTERPRETATION: These findings show that co-presence time would help predict healthcare-acquired infection, and would do so earlier than the current standard of care. Using this measure prospectively in hospitals based on real-time data could limit the consequences of infection, both by being able to treat individual infected patients earlier, and by preventing potential secondary infections stemming from the original infected patient.
has issue date	2020-08-01(xsd:dateTime)
bibo:doi	10.1016/j.jhin.2020.07.031
bibo:pmid	32745591
has license	no-cc
sha1sum (hex)	edaa1ed7a818a7010794dac7afc9b0ec3bd3e320
schema:url	https://doi.org/10.1016/j.jhin.2020.07.031
resource representing a document's title	A passive monitoring tool using hospital administrative data enables earlier specific detection of healthcare-acquired infections
has PubMed Central identifier	PMC7395302
has PubMed identifier	32745591
schema:publication	J Hosp Infect
resource representing a document's body	covid:edaa1ed7a818a7010794dac7afc9b0ec3bd3e320#body_text
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