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Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review

BACKGROUND: Nursing care is increasingly supported by computerized information systems and decision support aids. Since the advent of handheld computer devices (HCDs), there has been limited exploration of their use in nursing practice. OBJECTIVE: The study aimed to understand the professional and c...

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Autores principales: Glanville, David, Hutchinson, Anastasia, Khaw, Damien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9972202/
https://www.ncbi.nlm.nih.gov/pubmed/36780222
http://dx.doi.org/10.2196/39987
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author Glanville, David
Hutchinson, Anastasia
Khaw, Damien
author_facet Glanville, David
Hutchinson, Anastasia
Khaw, Damien
author_sort Glanville, David
collection PubMed
description BACKGROUND: Nursing care is increasingly supported by computerized information systems and decision support aids. Since the advent of handheld computer devices (HCDs), there has been limited exploration of their use in nursing practice. OBJECTIVE: The study aimed to understand the professional and clinical impacts of the use of mobile health apps in nursing to assist clinical decision-making in acute care settings. The study also aimed to explore the scope of published research and identify key nomenclature with respect to research in this emerging field within nursing practice. METHODS: This scoping review involved a tripartite search of electronic databases (CINAHL, Embase, MEDLINE, and Google Scholar) using preliminary, broad, and comprehensive search terms. The included studies were hand searched for additional citations. Two researchers independently screened the studies for inclusion and appraised quality using structured critical appraisal tools. RESULTS: Of the 2309 unique studies screened, 28 (1.21%) were included in the final analyses: randomized controlled trials (n=3, 11%) and quasi-experimental (n=9, 32%), observational (n=10, 36%), mixed methods (n=2, 7%), qualitative descriptive (n=2, 7%), and diagnostic accuracy (n=2, 7%) studies. Studies investigated the impact of HCDs on nursing decisions (n=12, 43%); the effectiveness, safety, and quality of care (n=9, 32%); and HCD usability, uptake, and acceptance (n=14, 50%) and were judged to contain moderate-to-high risk of bias. The terminology used to describe HCDs was heterogenous across studies, comprising 24 unique descriptors and 17 individual concepts that reflected 3 discrete technology platforms (“PDA technology,” “Smartphone/tablet technology,” and “Health care–specific technology”). Study findings varied, as did the range of decision-making modalities targeted by HCD interventions. Interventions varied according to the level of clinician versus algorithmic judgment: unstructured clinical judgment, structured clinical judgment, and computerized algorithmic judgment. CONCLUSIONS: The extant literature is varied but suggests that HCDs can be used effectively to support aspects of acute nursing care. However, there is a dearth of high-level evidence regarding this phenomenon and studies exploring the degree to which HCD implementation may affect acute nursing care delivery workflow. Additional targeted research using rigorous experimental designs is needed in this emerging field to determine the true potential of HCDs in optimizing acute nursing care.
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spelling pubmed-99722022023-03-01 Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review Glanville, David Hutchinson, Anastasia Khaw, Damien J Med Internet Res Review BACKGROUND: Nursing care is increasingly supported by computerized information systems and decision support aids. Since the advent of handheld computer devices (HCDs), there has been limited exploration of their use in nursing practice. OBJECTIVE: The study aimed to understand the professional and clinical impacts of the use of mobile health apps in nursing to assist clinical decision-making in acute care settings. The study also aimed to explore the scope of published research and identify key nomenclature with respect to research in this emerging field within nursing practice. METHODS: This scoping review involved a tripartite search of electronic databases (CINAHL, Embase, MEDLINE, and Google Scholar) using preliminary, broad, and comprehensive search terms. The included studies were hand searched for additional citations. Two researchers independently screened the studies for inclusion and appraised quality using structured critical appraisal tools. RESULTS: Of the 2309 unique studies screened, 28 (1.21%) were included in the final analyses: randomized controlled trials (n=3, 11%) and quasi-experimental (n=9, 32%), observational (n=10, 36%), mixed methods (n=2, 7%), qualitative descriptive (n=2, 7%), and diagnostic accuracy (n=2, 7%) studies. Studies investigated the impact of HCDs on nursing decisions (n=12, 43%); the effectiveness, safety, and quality of care (n=9, 32%); and HCD usability, uptake, and acceptance (n=14, 50%) and were judged to contain moderate-to-high risk of bias. The terminology used to describe HCDs was heterogenous across studies, comprising 24 unique descriptors and 17 individual concepts that reflected 3 discrete technology platforms (“PDA technology,” “Smartphone/tablet technology,” and “Health care–specific technology”). Study findings varied, as did the range of decision-making modalities targeted by HCD interventions. Interventions varied according to the level of clinician versus algorithmic judgment: unstructured clinical judgment, structured clinical judgment, and computerized algorithmic judgment. CONCLUSIONS: The extant literature is varied but suggests that HCDs can be used effectively to support aspects of acute nursing care. However, there is a dearth of high-level evidence regarding this phenomenon and studies exploring the degree to which HCD implementation may affect acute nursing care delivery workflow. Additional targeted research using rigorous experimental designs is needed in this emerging field to determine the true potential of HCDs in optimizing acute nursing care. JMIR Publications 2023-02-13 /pmc/articles/PMC9972202/ /pubmed/36780222 http://dx.doi.org/10.2196/39987 Text en ©David Glanville, Anastasia Hutchinson, Damien Khaw. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.02.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Review
Glanville, David
Hutchinson, Anastasia
Khaw, Damien
Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review
title Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review
title_full Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review
title_fullStr Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review
title_full_unstemmed Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review
title_short Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review
title_sort handheld computer devices to support clinical decision-making in acute nursing practice: systematic scoping review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9972202/
https://www.ncbi.nlm.nih.gov/pubmed/36780222
http://dx.doi.org/10.2196/39987
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