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Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study
BACKGROUND: Rapid response systems (RRSs) are essential components of patient safety systems; however, limited evidence exists regarding their effectiveness and optimal structures. We aimed to assess the activation patterns and outcomes of RRS implementation with/without a real-time automatic alerti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643026/ https://www.ncbi.nlm.nih.gov/pubmed/34863275 http://dx.doi.org/10.1186/s13049-021-00979-y |
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author | You, Seung-Hun Jung, Sun-Young Lee, Hyun Joo Kim, Sulhee Yang, Eunjin |
author_facet | You, Seung-Hun Jung, Sun-Young Lee, Hyun Joo Kim, Sulhee Yang, Eunjin |
author_sort | You, Seung-Hun |
collection | PubMed |
description | BACKGROUND: Rapid response systems (RRSs) are essential components of patient safety systems; however, limited evidence exists regarding their effectiveness and optimal structures. We aimed to assess the activation patterns and outcomes of RRS implementation with/without a real-time automatic alerting system (AAS) based on electronic medical records (EMRs). METHODS: We retrospectively analyzed clinical data of patients for whom the RRS was activated in the surgical wards of a tertiary university hospital. We compared the code rate, in-hospital mortality, unplanned intensive care unit (ICU) admission, and other clinical outcomes before and after applying RRS and AAS as follows: pre-RRS (January 2013–July 2015), RRS without AAS (August 2015–November 2016), and RRS with AAS (December 2016–December 2017). RESULTS: In-hospital mortality per 1000 admissions decreased from 15.1 to 12.9 after RRS implementation (p < 0.001). RRS activation per 1000 admissions increased from 14.4 to 26.3 after AAS implementation. The severity of patients’ condition calculated using the modified early warning score increased from 2.5 (± 2.1) in the RRS without AAS to 3.6 (± 2.1) (p < 0.001) in the RRS with AAS. The total and preventable code rates and in-hospital mortality rates were comparable between the RRS implementation periods without/with AAS. ICU duration and mortality results improved in patients with RRS activation and unplanned ICU admission. The data of RRS non-activated group remained unaltered during the study. CONCLUSIONS: Real-time AAS based on EMRs might help identify unstable patients. Early detection and intervention with RRS may improve patient outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13049-021-00979-y. |
format | Online Article Text |
id | pubmed-8643026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86430262021-12-06 Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study You, Seung-Hun Jung, Sun-Young Lee, Hyun Joo Kim, Sulhee Yang, Eunjin Scand J Trauma Resusc Emerg Med Original Research BACKGROUND: Rapid response systems (RRSs) are essential components of patient safety systems; however, limited evidence exists regarding their effectiveness and optimal structures. We aimed to assess the activation patterns and outcomes of RRS implementation with/without a real-time automatic alerting system (AAS) based on electronic medical records (EMRs). METHODS: We retrospectively analyzed clinical data of patients for whom the RRS was activated in the surgical wards of a tertiary university hospital. We compared the code rate, in-hospital mortality, unplanned intensive care unit (ICU) admission, and other clinical outcomes before and after applying RRS and AAS as follows: pre-RRS (January 2013–July 2015), RRS without AAS (August 2015–November 2016), and RRS with AAS (December 2016–December 2017). RESULTS: In-hospital mortality per 1000 admissions decreased from 15.1 to 12.9 after RRS implementation (p < 0.001). RRS activation per 1000 admissions increased from 14.4 to 26.3 after AAS implementation. The severity of patients’ condition calculated using the modified early warning score increased from 2.5 (± 2.1) in the RRS without AAS to 3.6 (± 2.1) (p < 0.001) in the RRS with AAS. The total and preventable code rates and in-hospital mortality rates were comparable between the RRS implementation periods without/with AAS. ICU duration and mortality results improved in patients with RRS activation and unplanned ICU admission. The data of RRS non-activated group remained unaltered during the study. CONCLUSIONS: Real-time AAS based on EMRs might help identify unstable patients. Early detection and intervention with RRS may improve patient outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13049-021-00979-y. BioMed Central 2021-12-04 /pmc/articles/PMC8643026/ /pubmed/34863275 http://dx.doi.org/10.1186/s13049-021-00979-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Original Research You, Seung-Hun Jung, Sun-Young Lee, Hyun Joo Kim, Sulhee Yang, Eunjin Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study |
title | Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study |
title_full | Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study |
title_fullStr | Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study |
title_full_unstemmed | Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study |
title_short | Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study |
title_sort | incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643026/ https://www.ncbi.nlm.nih.gov/pubmed/34863275 http://dx.doi.org/10.1186/s13049-021-00979-y |
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