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Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language
The Shared Meaning Model (SMM) is a grounded theory, derived in a previous study. This model demonstrates pathways for communication between nurse and primary care providers (PCPs) in the nursing home (NH), In this study we used the SMM for feasibility testing of a clinical decision support app (CDS...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682660/ http://dx.doi.org/10.1093/geroni/igab046.3202 |
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author | Owen, Donna Ashcraft, Alyce Johnson, Kyle Song, Huaxin Culberson, John |
author_facet | Owen, Donna Ashcraft, Alyce Johnson, Kyle Song, Huaxin Culberson, John |
author_sort | Owen, Donna |
collection | PubMed |
description | The Shared Meaning Model (SMM) is a grounded theory, derived in a previous study. This model demonstrates pathways for communication between nurse and primary care providers (PCPs) in the nursing home (NH), In this study we used the SMM for feasibility testing of a clinical decision support app (CDS app) using a descriptive, structured observational design. This study also provided a forum for initial testing of the SMM. The CDS app algorithm provided a common language to assess a resident with the goal of sharing this information with a PCP. The CDS app guided licensed vocational nurses (LVNs) (N=10) in assessing a standardized nursing home resident in a simulation setting experiencing symptoms of a potential urinary tract infection (UTI). Interviews with LVNs provided details of CDS app usability and concerns about using the CDS app with NH residents. Videos recorded LVNs interacting with the resident while using the CDS app on an iPad®. Time-stamps logged duration of the assessment. Bookmarked segments were used for discussion in LVN interviews. Videos were coded for eye contact, conversation, and touch between LVN and resident and documented personalized interactions. Findings indicated areas (lab values, drug names) for changes to language in the algorithm. In less than 12 minutes the CDS app enabled LVNs to collect information based on language used by PCPs to make decisions about the presence of a UTI. Relationships between initial constructs in the SMM were supported. This CDS app holds promise for building a common language to enhance interprofessional communication. |
format | Online Article Text |
id | pubmed-8682660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86826602021-12-20 Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language Owen, Donna Ashcraft, Alyce Johnson, Kyle Song, Huaxin Culberson, John Innov Aging Abstracts The Shared Meaning Model (SMM) is a grounded theory, derived in a previous study. This model demonstrates pathways for communication between nurse and primary care providers (PCPs) in the nursing home (NH), In this study we used the SMM for feasibility testing of a clinical decision support app (CDS app) using a descriptive, structured observational design. This study also provided a forum for initial testing of the SMM. The CDS app algorithm provided a common language to assess a resident with the goal of sharing this information with a PCP. The CDS app guided licensed vocational nurses (LVNs) (N=10) in assessing a standardized nursing home resident in a simulation setting experiencing symptoms of a potential urinary tract infection (UTI). Interviews with LVNs provided details of CDS app usability and concerns about using the CDS app with NH residents. Videos recorded LVNs interacting with the resident while using the CDS app on an iPad®. Time-stamps logged duration of the assessment. Bookmarked segments were used for discussion in LVN interviews. Videos were coded for eye contact, conversation, and touch between LVN and resident and documented personalized interactions. Findings indicated areas (lab values, drug names) for changes to language in the algorithm. In less than 12 minutes the CDS app enabled LVNs to collect information based on language used by PCPs to make decisions about the presence of a UTI. Relationships between initial constructs in the SMM were supported. This CDS app holds promise for building a common language to enhance interprofessional communication. Oxford University Press 2021-12-17 /pmc/articles/PMC8682660/ http://dx.doi.org/10.1093/geroni/igab046.3202 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstracts Owen, Donna Ashcraft, Alyce Johnson, Kyle Song, Huaxin Culberson, John Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language |
title | Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language |
title_full | Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language |
title_fullStr | Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language |
title_full_unstemmed | Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language |
title_short | Technology Guided Assessment for Urinary Tract Infection: Creating a Common Interprofessional Language |
title_sort | technology guided assessment for urinary tract infection: creating a common interprofessional language |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682660/ http://dx.doi.org/10.1093/geroni/igab046.3202 |
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