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Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support

BACKGROUND: Literature supports appropriate testing as a key factor affecting hospital onset (HO) Clostridium difficile (CDIF). It was recognized that our institution was a significant outlier in HO CDIF with a standardized infection ratio (SIR) of 2.567 in the second quarter of 2016 compared with a...

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Autores principales: Donatoni, Gina, Mikolajczak, Anessa, Lewis, Steven, Daniels, Mark, Haviley, Corinne, Postelnick, Michael, Sutton, Sarah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5631012/
http://dx.doi.org/10.1093/ofid/ofx163.1014
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author Donatoni, Gina
Mikolajczak, Anessa
Lewis, Steven
Daniels, Mark
Haviley, Corinne
Postelnick, Michael
Sutton, Sarah
author_facet Donatoni, Gina
Mikolajczak, Anessa
Lewis, Steven
Daniels, Mark
Haviley, Corinne
Postelnick, Michael
Sutton, Sarah
author_sort Donatoni, Gina
collection PubMed
description BACKGROUND: Literature supports appropriate testing as a key factor affecting hospital onset (HO) Clostridium difficile (CDIF). It was recognized that our institution was a significant outlier in HO CDIF with a standardized infection ratio (SIR) of 2.567 in the second quarter of 2016 compared with a national SIR of 0.997. A February 2015 – April 2015 line list of CDIF LabID events were pulled from the National Healthcare Safety Network (NHSN) and medical records were reviewed for test appropriateness based on CDC/IDSA guidelines. Of these, 50% were related to inappropriate testing. Infection Prevention and Quality identified this as an opportunity for improvement and Executives dedicated resources to reduction efforts. METHODS: A report was created using our data warehouse to track specimens that were not collected within 24 hours of an order, as well as patients that had testing done in the previous 7 days. Physician and nurse education was completed on appropriate testing for CDIF, including symptoms and timely specimen collection. An enhanced order set was launched which embedded the testing algorithm into a series of cascading questions and best practice alerts (BPAs) which prompt the provider to reconsider ordering if the patient has less than 3 episodes of diarrhea in a 24 hour period, and/or has alternative explanations for diarrhea, including tube feedings and/or laxatives. Any CDIF test results from the past 30 days appear on the order screen to further guide physician ordering. RESULTS: Based on our NHSN data, HO CDIF cases were identified from October 2015 – September 2016, resulting in a peak (SIR) of 2.567. Since the interventions in November 2016, we have decreased our SIR to 0.356 in the first quarter of 2017. This shows a 50% overall decrease in HO CDIF. The data warehouse report showed 99% compliance of specimens collected within 24 hours of an order and only 5% of patients with an order in the past 7 days. CONCLUSION: By implementing targeted education and a sophisticated order entry process that includes decision support, as well as recent results and treatments in the electronic medical record, CDIF cases are being appropriately ordered and collected, ensuring appropriate classification within NHSN and a decrease in overall SIR DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-56310122017-11-07 Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support Donatoni, Gina Mikolajczak, Anessa Lewis, Steven Daniels, Mark Haviley, Corinne Postelnick, Michael Sutton, Sarah Open Forum Infect Dis Abstracts BACKGROUND: Literature supports appropriate testing as a key factor affecting hospital onset (HO) Clostridium difficile (CDIF). It was recognized that our institution was a significant outlier in HO CDIF with a standardized infection ratio (SIR) of 2.567 in the second quarter of 2016 compared with a national SIR of 0.997. A February 2015 – April 2015 line list of CDIF LabID events were pulled from the National Healthcare Safety Network (NHSN) and medical records were reviewed for test appropriateness based on CDC/IDSA guidelines. Of these, 50% were related to inappropriate testing. Infection Prevention and Quality identified this as an opportunity for improvement and Executives dedicated resources to reduction efforts. METHODS: A report was created using our data warehouse to track specimens that were not collected within 24 hours of an order, as well as patients that had testing done in the previous 7 days. Physician and nurse education was completed on appropriate testing for CDIF, including symptoms and timely specimen collection. An enhanced order set was launched which embedded the testing algorithm into a series of cascading questions and best practice alerts (BPAs) which prompt the provider to reconsider ordering if the patient has less than 3 episodes of diarrhea in a 24 hour period, and/or has alternative explanations for diarrhea, including tube feedings and/or laxatives. Any CDIF test results from the past 30 days appear on the order screen to further guide physician ordering. RESULTS: Based on our NHSN data, HO CDIF cases were identified from October 2015 – September 2016, resulting in a peak (SIR) of 2.567. Since the interventions in November 2016, we have decreased our SIR to 0.356 in the first quarter of 2017. This shows a 50% overall decrease in HO CDIF. The data warehouse report showed 99% compliance of specimens collected within 24 hours of an order and only 5% of patients with an order in the past 7 days. CONCLUSION: By implementing targeted education and a sophisticated order entry process that includes decision support, as well as recent results and treatments in the electronic medical record, CDIF cases are being appropriately ordered and collected, ensuring appropriate classification within NHSN and a decrease in overall SIR DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2017-10-04 /pmc/articles/PMC5631012/ http://dx.doi.org/10.1093/ofid/ofx163.1014 Text en © The Author 2017. 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
Donatoni, Gina
Mikolajczak, Anessa
Lewis, Steven
Daniels, Mark
Haviley, Corinne
Postelnick, Michael
Sutton, Sarah
Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support
title Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support
title_full Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support
title_fullStr Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support
title_full_unstemmed Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support
title_short Decrease of Hospital-Onset Clostridium difficile through Enhanced Electronic Decision Support
title_sort decrease of hospital-onset clostridium difficile through enhanced electronic decision support
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5631012/
http://dx.doi.org/10.1093/ofid/ofx163.1014
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