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Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury
BACKGROUND: Acute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision supp...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7640650/ https://www.ncbi.nlm.nih.gov/pubmed/33148237 http://dx.doi.org/10.1186/s12911-020-01303-x |
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author | Howarth, Megan Bhatt, Meha Benterud, Eleanor Wolska, Anna Minty, Evan Choi, Kyoo-Yoon Devrome, Andrea Harrison, Tyrone G. Baylis, Barry Dixon, Elijah Datta, Indraneel Pannu, Neesh James, Matthew T. |
author_facet | Howarth, Megan Bhatt, Meha Benterud, Eleanor Wolska, Anna Minty, Evan Choi, Kyoo-Yoon Devrome, Andrea Harrison, Tyrone G. Baylis, Barry Dixon, Elijah Datta, Indraneel Pannu, Neesh James, Matthew T. |
author_sort | Howarth, Megan |
collection | PubMed |
description | BACKGROUND: Acute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision support tools have the potential to enhance recognition and management of AKI, there is limited description in the literature of how these tools were developed and whether they meet end-user expectations. METHODS: We developed and evaluated the content, acceptability, and usability of electronic clinical decision support tools for AKI care. Multi-component tools were developed within a hospital EMR (Sunrise Clinical Manager™, Allscripts Healthcare Solutions Inc.) currently deployed in Calgary, Alberta, and included: AKI stage alerts, AKI adverse medication warnings, AKI clinical summary dashboard, and an AKI order set. The clinical decision support was developed for use by multiple healthcare providers at the time and point of care on general medical and surgical units. Functional and usability testing for the alerts and clinical summary dashboard was conducted via in-person evaluation sessions, interviews, and surveys of care providers. Formal user acceptance testing with clinical end-users, including physicians and nursing staff, was conducted to evaluate the AKI order set. RESULTS: Considerations for appropriate deployment of both non-disruptive and interruptive functions was important to gain acceptability by clinicians. Functional testing and usability surveys for the alerts and clinical summary dashboard indicated that the tools were operating as desired and 74% (17/23) of surveyed healthcare providers reported that these tools were easy to use and could be learned quickly. Over three-quarters of providers (18/23) reported that they would utilize the tools in their practice. Three-quarters of the participants (13/17) in user acceptance testing agreed that recommendations within the order set were useful. Overall, 88% (15/17) believed that the order set would improve the care and management of AKI patients. CONCLUSIONS: Development and testing of EMR-based decision support tools for AKI with clinicians led to high acceptance by clinical end-users. Subsequent implementation within clinical environments will require end-user education and engagement in system-level initiatives to use the tools to improve care. |
format | Online Article Text |
id | pubmed-7640650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76406502020-11-04 Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury Howarth, Megan Bhatt, Meha Benterud, Eleanor Wolska, Anna Minty, Evan Choi, Kyoo-Yoon Devrome, Andrea Harrison, Tyrone G. Baylis, Barry Dixon, Elijah Datta, Indraneel Pannu, Neesh James, Matthew T. BMC Med Inform Decis Mak Research Article BACKGROUND: Acute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision support tools have the potential to enhance recognition and management of AKI, there is limited description in the literature of how these tools were developed and whether they meet end-user expectations. METHODS: We developed and evaluated the content, acceptability, and usability of electronic clinical decision support tools for AKI care. Multi-component tools were developed within a hospital EMR (Sunrise Clinical Manager™, Allscripts Healthcare Solutions Inc.) currently deployed in Calgary, Alberta, and included: AKI stage alerts, AKI adverse medication warnings, AKI clinical summary dashboard, and an AKI order set. The clinical decision support was developed for use by multiple healthcare providers at the time and point of care on general medical and surgical units. Functional and usability testing for the alerts and clinical summary dashboard was conducted via in-person evaluation sessions, interviews, and surveys of care providers. Formal user acceptance testing with clinical end-users, including physicians and nursing staff, was conducted to evaluate the AKI order set. RESULTS: Considerations for appropriate deployment of both non-disruptive and interruptive functions was important to gain acceptability by clinicians. Functional testing and usability surveys for the alerts and clinical summary dashboard indicated that the tools were operating as desired and 74% (17/23) of surveyed healthcare providers reported that these tools were easy to use and could be learned quickly. Over three-quarters of providers (18/23) reported that they would utilize the tools in their practice. Three-quarters of the participants (13/17) in user acceptance testing agreed that recommendations within the order set were useful. Overall, 88% (15/17) believed that the order set would improve the care and management of AKI patients. CONCLUSIONS: Development and testing of EMR-based decision support tools for AKI with clinicians led to high acceptance by clinical end-users. Subsequent implementation within clinical environments will require end-user education and engagement in system-level initiatives to use the tools to improve care. BioMed Central 2020-11-04 /pmc/articles/PMC7640650/ /pubmed/33148237 http://dx.doi.org/10.1186/s12911-020-01303-x Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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 | Research Article Howarth, Megan Bhatt, Meha Benterud, Eleanor Wolska, Anna Minty, Evan Choi, Kyoo-Yoon Devrome, Andrea Harrison, Tyrone G. Baylis, Barry Dixon, Elijah Datta, Indraneel Pannu, Neesh James, Matthew T. Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury |
title | Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury |
title_full | Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury |
title_fullStr | Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury |
title_full_unstemmed | Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury |
title_short | Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury |
title_sort | development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7640650/ https://www.ncbi.nlm.nih.gov/pubmed/33148237 http://dx.doi.org/10.1186/s12911-020-01303-x |
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