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163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program

BACKGROUND: Surveillance is an essential aspect of infection prevention. Despite the high morbidity and mortality associated with procedure-related Cardiac Implantable Electronic Device (CIED) infections, methods for identifying them are limited. The objective of this study was to develop an algorit...

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Autores principales: Asundi, Archana, Stanislawski, Maggie, Mehta, Payal, Mull, Hillary, Schweizer, Marin, Ho, P Michael, Gupta, Kalpana, Branch-Elliman, Westyn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252973/
http://dx.doi.org/10.1093/ofid/ofy209.033
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author Asundi, Archana
Stanislawski, Maggie
Mehta, Payal
Mull, Hillary
Schweizer, Marin
Ho, P Michael
Gupta, Kalpana
Branch-Elliman, Westyn
author_facet Asundi, Archana
Stanislawski, Maggie
Mehta, Payal
Mull, Hillary
Schweizer, Marin
Ho, P Michael
Gupta, Kalpana
Branch-Elliman, Westyn
author_sort Asundi, Archana
collection PubMed
description BACKGROUND: Surveillance is an essential aspect of infection prevention. Despite the high morbidity and mortality associated with procedure-related Cardiac Implantable Electronic Device (CIED) infections, methods for identifying them are limited. The objective of this study was to develop an algorithm with electronic flags to facilitate detection of CIED infections in a large, multi-center cohort. METHODS: A sample of patients who underwent CIED procedures entered into the VA Clinical Assessment Reporting and Tracking Electrophysiology (CART-EP) program from FY 2007 to 2015 were included in the nested case–control study. After cohort creation, data from this review process were combined with electronic variables (e.g., microbiology orders, ICD 9/10 codes) to develop a preliminary algorithm that categorized patients as high, intermediate, or low risk of CIED infection. RESULTS: A total of 1,014 unique patients out of a cohort of 5,955 procedures underwent manual review. Among these cases, 59 CIED infections and 955 controls were identified. Electronic variables predictive of CIED infection included ICD 9/10 infection codes and microbiology orders (table). ICD 9/10 codes had excellent PPV for flagging infections but sensitivity was limited (47.5%, see figure). Adding microbiology order flags increased sensitivity but lowered specificity. Specificity in patients without either flag was outstanding (99%). [Image: see text] CONCLUSION: Absence of ICD 9/10 and microbiology orders is highly specific for ruling out CIED infections. The discriminatory abilities of the algorithm for intermediate probability flags (+microbiology/−ICD9/10) need improvement. In patients without ICD codes, at least microbiology orders should be used as a flag to streamline review of possible device infections. Refinement of this tool using other clinical flags may improve operating characteristics and clinical utility. DISCLOSURES: W. Branch-Elliman, Veterans’ Integrated Service Network Career Development Award: Investigator, Research grant. American Heart Association: Investigator, Research grant.
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spelling pubmed-62529732018-11-28 163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program Asundi, Archana Stanislawski, Maggie Mehta, Payal Mull, Hillary Schweizer, Marin Ho, P Michael Gupta, Kalpana Branch-Elliman, Westyn Open Forum Infect Dis Abstracts BACKGROUND: Surveillance is an essential aspect of infection prevention. Despite the high morbidity and mortality associated with procedure-related Cardiac Implantable Electronic Device (CIED) infections, methods for identifying them are limited. The objective of this study was to develop an algorithm with electronic flags to facilitate detection of CIED infections in a large, multi-center cohort. METHODS: A sample of patients who underwent CIED procedures entered into the VA Clinical Assessment Reporting and Tracking Electrophysiology (CART-EP) program from FY 2007 to 2015 were included in the nested case–control study. After cohort creation, data from this review process were combined with electronic variables (e.g., microbiology orders, ICD 9/10 codes) to develop a preliminary algorithm that categorized patients as high, intermediate, or low risk of CIED infection. RESULTS: A total of 1,014 unique patients out of a cohort of 5,955 procedures underwent manual review. Among these cases, 59 CIED infections and 955 controls were identified. Electronic variables predictive of CIED infection included ICD 9/10 infection codes and microbiology orders (table). ICD 9/10 codes had excellent PPV for flagging infections but sensitivity was limited (47.5%, see figure). Adding microbiology order flags increased sensitivity but lowered specificity. Specificity in patients without either flag was outstanding (99%). [Image: see text] CONCLUSION: Absence of ICD 9/10 and microbiology orders is highly specific for ruling out CIED infections. The discriminatory abilities of the algorithm for intermediate probability flags (+microbiology/−ICD9/10) need improvement. In patients without ICD codes, at least microbiology orders should be used as a flag to streamline review of possible device infections. Refinement of this tool using other clinical flags may improve operating characteristics and clinical utility. DISCLOSURES: W. Branch-Elliman, Veterans’ Integrated Service Network Career Development Award: Investigator, Research grant. American Heart Association: Investigator, Research grant. Oxford University Press 2018-11-26 /pmc/articles/PMC6252973/ http://dx.doi.org/10.1093/ofid/ofy209.033 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Asundi, Archana
Stanislawski, Maggie
Mehta, Payal
Mull, Hillary
Schweizer, Marin
Ho, P Michael
Gupta, Kalpana
Branch-Elliman, Westyn
163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program
title 163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program
title_full 163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program
title_fullStr 163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program
title_full_unstemmed 163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program
title_short 163. Development of an Electronic Flagging Tool for Identifying Cardiac Device Infections: Insights from the VA CART Program
title_sort 163. development of an electronic flagging tool for identifying cardiac device infections: insights from the va cart program
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252973/
http://dx.doi.org/10.1093/ofid/ofy209.033
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