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Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care
Background The purpose of this article is to describe neonatal intensive care unit clinician perceptions of a continuous predictive analytics technology and how those perceptions influenced clinician adoption. Adopting and integrating new technology into care is notoriously slow and difficult; real...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494616/ https://www.ncbi.nlm.nih.gov/pubmed/31042807 http://dx.doi.org/10.1055/s-0039-1688478 |
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author | Kitzmiller, Rebecca R. Vaughan, Ashley Skeeles-Worley, Angela Keim-Malpass, Jessica Yap, Tracey L. Lindberg, Curt Kennerly, Susan Mitchell, Claire Tai, Robert Sullivan, Brynne A. Anderson, Ruth Moorman, Joseph R. |
author_facet | Kitzmiller, Rebecca R. Vaughan, Ashley Skeeles-Worley, Angela Keim-Malpass, Jessica Yap, Tracey L. Lindberg, Curt Kennerly, Susan Mitchell, Claire Tai, Robert Sullivan, Brynne A. Anderson, Ruth Moorman, Joseph R. |
author_sort | Kitzmiller, Rebecca R. |
collection | PubMed |
description | Background The purpose of this article is to describe neonatal intensive care unit clinician perceptions of a continuous predictive analytics technology and how those perceptions influenced clinician adoption. Adopting and integrating new technology into care is notoriously slow and difficult; realizing expected gains remain a challenge. Methods Semistructured interviews from a cross-section of neonatal physicians ( n = 14) and nurses ( n = 8) from a single U.S. medical center were collected 18 months following the conclusion of the predictive monitoring technology randomized control trial. Following qualitative descriptive analysis, innovation attributes from Diffusion of Innovation Theory-guided thematic development. Results Results suggest that the combination of physical location as well as lack of integration into work flow or methods of using data in care decisionmaking may have delayed clinicians from routinely paying attention to the data. Once data were routinely collected, documented, and reported during patient rounds and patient handoffs, clinicians came to view data as another vital sign. Through clinicians' observation of senior physicians and nurses, and ongoing dialogue about data trends and patient status, clinicians learned how to integrate these data in care decision making (e.g., differential diagnosis) and came to value the technology as beneficial to care delivery. Discussion The use of newly created predictive technologies that provide early warning of illness may require implementation strategies that acknowledge the risk–benefit of treatment clinicians must balance and take advantage of existing clinician training methods. |
format | Online Article Text |
id | pubmed-6494616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-64946162020-03-01 Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care Kitzmiller, Rebecca R. Vaughan, Ashley Skeeles-Worley, Angela Keim-Malpass, Jessica Yap, Tracey L. Lindberg, Curt Kennerly, Susan Mitchell, Claire Tai, Robert Sullivan, Brynne A. Anderson, Ruth Moorman, Joseph R. Appl Clin Inform Background The purpose of this article is to describe neonatal intensive care unit clinician perceptions of a continuous predictive analytics technology and how those perceptions influenced clinician adoption. Adopting and integrating new technology into care is notoriously slow and difficult; realizing expected gains remain a challenge. Methods Semistructured interviews from a cross-section of neonatal physicians ( n = 14) and nurses ( n = 8) from a single U.S. medical center were collected 18 months following the conclusion of the predictive monitoring technology randomized control trial. Following qualitative descriptive analysis, innovation attributes from Diffusion of Innovation Theory-guided thematic development. Results Results suggest that the combination of physical location as well as lack of integration into work flow or methods of using data in care decisionmaking may have delayed clinicians from routinely paying attention to the data. Once data were routinely collected, documented, and reported during patient rounds and patient handoffs, clinicians came to view data as another vital sign. Through clinicians' observation of senior physicians and nurses, and ongoing dialogue about data trends and patient status, clinicians learned how to integrate these data in care decision making (e.g., differential diagnosis) and came to value the technology as beneficial to care delivery. Discussion The use of newly created predictive technologies that provide early warning of illness may require implementation strategies that acknowledge the risk–benefit of treatment clinicians must balance and take advantage of existing clinician training methods. Georg Thieme Verlag KG 2019-03 2019-05-01 /pmc/articles/PMC6494616/ /pubmed/31042807 http://dx.doi.org/10.1055/s-0039-1688478 Text en 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-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Kitzmiller, Rebecca R. Vaughan, Ashley Skeeles-Worley, Angela Keim-Malpass, Jessica Yap, Tracey L. Lindberg, Curt Kennerly, Susan Mitchell, Claire Tai, Robert Sullivan, Brynne A. Anderson, Ruth Moorman, Joseph R. Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care |
title | Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care |
title_full | Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care |
title_fullStr | Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care |
title_full_unstemmed | Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care |
title_short | Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care |
title_sort | diffusing an innovation: clinician perceptions of continuous predictive analytics monitoring in intensive care |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494616/ https://www.ncbi.nlm.nih.gov/pubmed/31042807 http://dx.doi.org/10.1055/s-0039-1688478 |
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