Cargando…
Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study
BACKGROUND: Inappropriate antimicrobial use is a crucial determinant of mortality in hospitalized patients with bloodstream infections. Current literature reporting on the impact of clinical decision support systems on optimizing antimicrobial prescription and reducing the time to appropriate antimi...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605697/ https://www.ncbi.nlm.nih.gov/pubmed/36320200 http://dx.doi.org/10.1093/ofid/ofac522 |
_version_ | 1784818130640437248 |
---|---|
author | Chen, Chii-Shiang Huang, Tsi-Shu Lee, Susan Shin-Jung Chien, Fu-Chin Yang, Ching-Hsiang Li, Sin-Sian Hsu, Chia-Jung Sy, Cheng Len Wu, Kuan-Sheng |
author_facet | Chen, Chii-Shiang Huang, Tsi-Shu Lee, Susan Shin-Jung Chien, Fu-Chin Yang, Ching-Hsiang Li, Sin-Sian Hsu, Chia-Jung Sy, Cheng Len Wu, Kuan-Sheng |
author_sort | Chen, Chii-Shiang |
collection | PubMed |
description | BACKGROUND: Inappropriate antimicrobial use is a crucial determinant of mortality in hospitalized patients with bloodstream infections. Current literature reporting on the impact of clinical decision support systems on optimizing antimicrobial prescription and reducing the time to appropriate antimicrobial therapy is limited. METHODS: Kaohsiung Veterans General Hospital implemented a hospital-wide, knowledge-based, active-delivery clinical decision support system, named RAPID (Real-time Alert for antimicrobial Prescription from virtual Infectious Diseases experts), to detect whether there was an antimicrobial agent–pathogen mismatch when a blood culture result was positive. Once RAPID determines the current antimicrobials as inappropriate, an alert text message is immediately sent to the clinicians in charge. This study evaluated how RAPID impacted the time to appropriate antimicrobial therapy among patients with bloodstream infections. RESULTS: During the study period, 633 of 11 297 recorded observations (5.6%) were determined as inappropriate antimicrobial prescriptions. The time to appropriate antimicrobial therapy was significantly shortened after the implementation of RAPID (1.65 vs 2.45 hours, P < .001), especially outside working hours (1.24 vs 6.43 hours, P < .001), in the medical wards (1.40 vs 2.14 hours, P < .001), in participants with candidemia (0.74 vs 5.36 hours, P < .001), and for bacteremia due to non-multidrug-resistant organisms (1.66 vs 2.49 hours, P < .001). CONCLUSIONS: Using a knowledge-based clinical decision support system to reduce the time to appropriate antimicrobial therapy in a real-world scenario is feasible and effective. Our results support the continued use of RAPID. |
format | Online Article Text |
id | pubmed-9605697 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-96056972022-10-31 Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study Chen, Chii-Shiang Huang, Tsi-Shu Lee, Susan Shin-Jung Chien, Fu-Chin Yang, Ching-Hsiang Li, Sin-Sian Hsu, Chia-Jung Sy, Cheng Len Wu, Kuan-Sheng Open Forum Infect Dis Major Article BACKGROUND: Inappropriate antimicrobial use is a crucial determinant of mortality in hospitalized patients with bloodstream infections. Current literature reporting on the impact of clinical decision support systems on optimizing antimicrobial prescription and reducing the time to appropriate antimicrobial therapy is limited. METHODS: Kaohsiung Veterans General Hospital implemented a hospital-wide, knowledge-based, active-delivery clinical decision support system, named RAPID (Real-time Alert for antimicrobial Prescription from virtual Infectious Diseases experts), to detect whether there was an antimicrobial agent–pathogen mismatch when a blood culture result was positive. Once RAPID determines the current antimicrobials as inappropriate, an alert text message is immediately sent to the clinicians in charge. This study evaluated how RAPID impacted the time to appropriate antimicrobial therapy among patients with bloodstream infections. RESULTS: During the study period, 633 of 11 297 recorded observations (5.6%) were determined as inappropriate antimicrobial prescriptions. The time to appropriate antimicrobial therapy was significantly shortened after the implementation of RAPID (1.65 vs 2.45 hours, P < .001), especially outside working hours (1.24 vs 6.43 hours, P < .001), in the medical wards (1.40 vs 2.14 hours, P < .001), in participants with candidemia (0.74 vs 5.36 hours, P < .001), and for bacteremia due to non-multidrug-resistant organisms (1.66 vs 2.49 hours, P < .001). CONCLUSIONS: Using a knowledge-based clinical decision support system to reduce the time to appropriate antimicrobial therapy in a real-world scenario is feasible and effective. Our results support the continued use of RAPID. Oxford University Press 2022-10-06 /pmc/articles/PMC9605697/ /pubmed/36320200 http://dx.doi.org/10.1093/ofid/ofac522 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://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 (https://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 | Major Article Chen, Chii-Shiang Huang, Tsi-Shu Lee, Susan Shin-Jung Chien, Fu-Chin Yang, Ching-Hsiang Li, Sin-Sian Hsu, Chia-Jung Sy, Cheng Len Wu, Kuan-Sheng Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study |
title | Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study |
title_full | Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study |
title_fullStr | Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study |
title_full_unstemmed | Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study |
title_short | Using a Knowledge-Based Clinical Decision Support System to Reduce the Time to Appropriate Antimicrobial Therapy in Hospitalized Patients With Bloodstream Infections: A Single-Center Observational Study |
title_sort | using a knowledge-based clinical decision support system to reduce the time to appropriate antimicrobial therapy in hospitalized patients with bloodstream infections: a single-center observational study |
topic | Major Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605697/ https://www.ncbi.nlm.nih.gov/pubmed/36320200 http://dx.doi.org/10.1093/ofid/ofac522 |
work_keys_str_mv | AT chenchiishiang usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT huangtsishu usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT leesusanshinjung usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT chienfuchin usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT yangchinghsiang usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT lisinsian usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT hsuchiajung usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT sychenglen usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy AT wukuansheng usingaknowledgebasedclinicaldecisionsupportsystemtoreducethetimetoappropriateantimicrobialtherapyinhospitalizedpatientswithbloodstreaminfectionsasinglecenterobservationalstudy |