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

奇纳 可用性 梅德林 术语 观察研究 医学 系统回顾 护理部 临床决策支持系统 批判性评价 决策支持系统 计算机科学 替代医学 心理干预 人工智能 病理 人机交互 哲学 语言学 法学 政治学
作者
David Glanville,Anastasia Hutchinson,Damien Khaw
出处
期刊:Journal of Medical Internet Research [JMIR Publications]
卷期号:25: e39987-e39987 被引量:6
标识
DOI:10.2196/39987
摘要

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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