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Title: Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review
Epworth Authors: Glanville, David
Hutchinson, Ana
Khaw, Damien
Keywords: Acute Care
Clinical Decision Making
Decision Making
Handheld Computer Devices
Mobile Computing
Mobile Health
Mobile Phone
Smart Phones
Mobile Health Apps
Scoping Review
eLearning Department
Academic and Medical Services, Epworth HealthCare, Victoria, Australia
Issue Date: Feb-2023
Publisher: JMIR Publications
Citation: J Med Internet Res . 2023 Feb 13;25:e39987
Abstract: 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.
DOI: 10.2196/39987
PubMed URL:
ISSN: 1438-8871
Journal Title: Journal of Medical Internet Research
Type: Journal Article
Affiliated Organisations: Centre for Quality and Patient Safety Research - Epworth HealthCare Partnership, Institute of Health Transformation, Deakin University, Burwood, Australia
Type of Clinical Study or Trial: Scoping Review
Appears in Collections:Health Administration

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