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188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations
BACKGROUND: Antibiotic prescribing varies amongst clinicians, which can result in inappropriate or overuse. Inappropriate antibiotics can increase the risk of adverse drug events and multi-drug-resistant organisms (MDRO). Decreasing variability and increasing alignment with guideline-based therapy m...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6254171/ http://dx.doi.org/10.1093/ofid/ofy210.201 |
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author | Shah, Nirav Acree, Mary Ellen Patros, Clayton Suseno, Mira Grant, Jennifer Fleming, Gary Hadsell, Bryce Semel, Jeffery Hebert, Courtney Singh, Kamaljit Peterson, Lance |
author_facet | Shah, Nirav Acree, Mary Ellen Patros, Clayton Suseno, Mira Grant, Jennifer Fleming, Gary Hadsell, Bryce Semel, Jeffery Hebert, Courtney Singh, Kamaljit Peterson, Lance |
author_sort | Shah, Nirav |
collection | PubMed |
description | BACKGROUND: Antibiotic prescribing varies amongst clinicians, which can result in inappropriate or overuse. Inappropriate antibiotics can increase the risk of adverse drug events and multi-drug-resistant organisms (MDRO). Decreasing variability and increasing alignment with guideline-based therapy may improve antimicrobial stewardship and outcomes. METHODS: We developed a point of care stewardship tool embedded in the electronic health record (EHR) that provides empiric antibiotic recommendations for four syndromes, urinary tract infection (UTI), abdominal biliary infection (ABI), pneumonia, and cellulitis. We identified key variables that alter antibiotic selection or need for infectious disease (ID) consultation such as allergy history, immunosuppression and risk factors for MDRO, and mortality. We created algorithms of preferred empiric antibiotic choices based on national and hospital guidelines using these risk factors. We used a weighted incidence syndromic combined antibiogram (WISCA) prediction model to recommend ID consultation when likelihood of coverage was below a defined threshold. We also incorporated a home-grown epidemiologic tool that takes real-time data from outpatient clinics on incidence of influenza-like-illness (ILI) to recommend influenza PCR testing during periods of high ILI risk. Data on risk factors and WISCA variables including demographics, allergy history, ICD10 codes, vitals, laboratories, and microbiology results were extracted in real-time from the EHR and sent via URL into a web server which has an embedded Windows ASP.NET C# web site and an SQL server database. The web server was then embedded back into the EHR. This tool stores recommendations into the database for stewardship auditing. RESULTS: Thirteen key and 20 WISCA variables are extracted from the EHR in real-time. There are eight distinct antibiotic recommendations for UTI and ABI, 12 for cellulitis, and 40 for pneumonia. An illustration of the ASAP tool is shown in Figure 1. CONCLUSION: ASAP is an HER-embedded platform that provides clinicians access to personalized antibiotic prescribing tied to best practices and optimal stewardship initiatives. Future work will look into the tool’s effect on variation in care, antibiotic prescribing, and outcomes. DISCLOSURES: All authors: No reported disclosures. |
format | Online Article Text |
id | pubmed-6254171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-62541712018-11-28 188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations Shah, Nirav Acree, Mary Ellen Patros, Clayton Suseno, Mira Grant, Jennifer Fleming, Gary Hadsell, Bryce Semel, Jeffery Hebert, Courtney Singh, Kamaljit Peterson, Lance Open Forum Infect Dis Abstracts BACKGROUND: Antibiotic prescribing varies amongst clinicians, which can result in inappropriate or overuse. Inappropriate antibiotics can increase the risk of adverse drug events and multi-drug-resistant organisms (MDRO). Decreasing variability and increasing alignment with guideline-based therapy may improve antimicrobial stewardship and outcomes. METHODS: We developed a point of care stewardship tool embedded in the electronic health record (EHR) that provides empiric antibiotic recommendations for four syndromes, urinary tract infection (UTI), abdominal biliary infection (ABI), pneumonia, and cellulitis. We identified key variables that alter antibiotic selection or need for infectious disease (ID) consultation such as allergy history, immunosuppression and risk factors for MDRO, and mortality. We created algorithms of preferred empiric antibiotic choices based on national and hospital guidelines using these risk factors. We used a weighted incidence syndromic combined antibiogram (WISCA) prediction model to recommend ID consultation when likelihood of coverage was below a defined threshold. We also incorporated a home-grown epidemiologic tool that takes real-time data from outpatient clinics on incidence of influenza-like-illness (ILI) to recommend influenza PCR testing during periods of high ILI risk. Data on risk factors and WISCA variables including demographics, allergy history, ICD10 codes, vitals, laboratories, and microbiology results were extracted in real-time from the EHR and sent via URL into a web server which has an embedded Windows ASP.NET C# web site and an SQL server database. The web server was then embedded back into the EHR. This tool stores recommendations into the database for stewardship auditing. RESULTS: Thirteen key and 20 WISCA variables are extracted from the EHR in real-time. There are eight distinct antibiotic recommendations for UTI and ABI, 12 for cellulitis, and 40 for pneumonia. An illustration of the ASAP tool is shown in Figure 1. CONCLUSION: ASAP is an HER-embedded platform that provides clinicians access to personalized antibiotic prescribing tied to best practices and optimal stewardship initiatives. Future work will look into the tool’s effect on variation in care, antibiotic prescribing, and outcomes. DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2018-11-26 /pmc/articles/PMC6254171/ http://dx.doi.org/10.1093/ofid/ofy210.201 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 Shah, Nirav Acree, Mary Ellen Patros, Clayton Suseno, Mira Grant, Jennifer Fleming, Gary Hadsell, Bryce Semel, Jeffery Hebert, Courtney Singh, Kamaljit Peterson, Lance 188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations |
title | 188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations |
title_full | 188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations |
title_fullStr | 188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations |
title_full_unstemmed | 188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations |
title_short | 188. A Novel Inpatient Antibiotic Stewardship Assistance Program (ASAP) Using Real-Time Electronic Health Record Data, Prediction Modeling and Epidemiologic Data to Provide Personalized Empiric Antibiotic Recommendations |
title_sort | 188. a novel inpatient antibiotic stewardship assistance program (asap) using real-time electronic health record data, prediction modeling and epidemiologic data to provide personalized empiric antibiotic recommendations |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6254171/ http://dx.doi.org/10.1093/ofid/ofy210.201 |
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