Literature DB >> 26899530

Performance characteristics and associated outcomes for an automated surveillance tool for bloodstream infection.

Jessica P Ridgway1, Xiaowu Sun2, Ying P Tabak2, Richard S Johannes2, Ari Robicsek3.   

Abstract

BACKGROUND: The objective of this study was to evaluate performance metrics and associated patient outcomes of an automated surveillance system, the blood Nosocomial Infection Marker (NIM).
METHODS: We reviewed records of 237 patients with and 36,927 patients without blood NIM using the National Healthcare Safety Network (NHSN) definition for laboratory-confirmed bloodstream infection (BSI) as the gold standard. We matched cases with noncases by propensity score and estimated attributable mortality and cost of NHSN-reportable central line-associated bloodstream infections (CLABSIs) and non-NHSN-reportable BSIs.
RESULTS: For patients with central lines (CL), the blood NIM had 73.2% positive predictive value (PPV), 99.9% negative predictive value (NPV), 89.2% sensitivity, and 99.7% specificity. For all patients regardless of CL status, the blood NIM had 53.6% PPV, 99.9% NPV, 84.0% sensitivity, and 99.9% specificity. For CLABSI cases compared with noncases, mortality was 17.5% versus 9.4% (P = .098), and median charge was $143,935 (interquartile range [IQR], $89,794-$257,447) versus $115,267 (IQR, $74,937-$173,053) (P < .01). For non-NHSN-reportable BSI cases compared with noncases, mortality was 23.6% versus 6.7% (P < .0001), and median charge was $86,927 (IQR, $54,728-$156,669) versus $62,929 (IQR, $36,743-$115,693) (P < .0001).
CONCLUSIONS: The NIM is an effective screening tool for BSI. Both NHSN-reportable and nonreportable BSI cases were associated with increased mortality and cost.
Copyright © 2016 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Electronic surveillance; central line–associated bloodstream infection; electronic health record; outcomes

Mesh:

Year:  2016        PMID: 26899530     DOI: 10.1016/j.ajic.2015.12.044

Source DB:  PubMed          Journal:  Am J Infect Control        ISSN: 0196-6553            Impact factor:   2.918


  6 in total

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Journal:  J Korean Acad Nurs       Date:  2020-08       Impact factor: 0.984

2.  A Combination Antibiogram Evaluation for Pseudomonas aeruginosa in Respiratory and Blood Sources from Intensive Care Unit (ICU) and Non-ICU Settings in U.S. Hospitals.

Authors:  Laura Puzniak; Daryl D DePestel; Arjun Srinivasan; Gang Ye; John Murray; Sanjay Merchant; C Andrew DeRyke; Vikas Gupta
Journal:  Antimicrob Agents Chemother       Date:  2019-03-27       Impact factor: 5.191

3.  Trends in resistant Enterobacteriaceae and Acinetobacter species in hospitalized patients in the United States: 2013-2017.

Authors:  Vikas Gupta; Gang Ye; Melanie Olesky; Kenneth Lawrence; John Murray; Kalvin Yu
Journal:  BMC Infect Dis       Date:  2019-08-23       Impact factor: 3.090

4.  Carbapenem-Nonsusceptible Gram-Negative Pathogens in ICU and Non-ICU Settings in US Hospitals in 2017: A Multicenter Study.

Authors:  Eilish McCann; Arjun Srinivasan; C Andrew DeRyke; Gang Ye; Daryl D DePestel; John Murray; Vikas Gupta
Journal:  Open Forum Infect Dis       Date:  2018-09-21       Impact factor: 3.835

5.  Electronically assisted surveillance systems of healthcare-associated infections: a systematic review.

Authors:  H Roel A Streefkerk; Roel Paj Verkooijen; Wichor M Bramer; Henri A Verbrugh
Journal:  Euro Surveill       Date:  2020-01

6.  Automated digital reporting of clinical laboratory information to national public health surveillance systems, results of a EU/EEA survey, 2018.

Authors:  Katrin Claire Leitmeyer; Laura Espinosa; Eeva Kaarina Broberg; Marc Jean Struelens
Journal:  Euro Surveill       Date:  2020-10
  6 in total

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