协调

IF 0.8 Q4 NURSING
H. Vrijhoef
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In a rapid review covering the evidence base for promising AI application scenarios for nursing care, Seibert et al. found that from a sample of 292 included studies, most (29.8%) describe AI applications in hospital settings. Further, they report that ‘care coordination and communication are frequent topics, which among others, include AI approaches classifying information in nursing documentation, supporting decision-making, and yielding information for coordination and continuity of care’. However, only a few publications went beyond proof-of-concept studies and few studies have assessed the effects of AI on clinical and organizational outcomes. In a perspective piece, London writes that the ability of AI systems to overcome fragmented, uncoordinated, and unwarranted medical practices is frustrated by the degree to which the ecosystems in which AI systems are being developed suffer from these same shortcomings. Moreover, he argues that the current state of AI has the potential to simply add another dimension to unnecessary variation in clinical care. To get a better grip on the value of AI for improving patient care, London points to applying a framework for indicating the level of maturity of AI systems and the level of evidence supporting specific claims to clinical utility. Further, he makes a point for implementation science to play a greater role in structuring and evaluating proposals to implement AI systems in healthcare settings. To stimulate research in this field and to clarify whether, how and when AI lives up to its promise regarding care coordination, the International Journal of Care Coordination will launch a special issue inviting authors to submit relevant work. Please visit the journal’s website for details about the special issue on CoordinAtIon scheduled for early 2024. In the current issue of the International Journal of Care Coordination, Kokorelias et al. present the findings of a scoping review regarding the implementation characteristics of dementia-specific navigation programs to help the integration of care across various settings. Based on 22 studies, mostly from the United States, key factors to the successful implementation of navigation programs for persons living with dementia were identified. With these factors fitting the constructs of the Consolidated Framework for Implementation Research (CFIR), a theoretical foundation to guide the implementation of dementia-specific navigation was provided. By exploring the experiences of older adults with complex care needs who have received services from a Canadian hospital-to-home transition patient navigation program, Kokorelias et al. were able to share important lessons. 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引用次数: 0

摘要

人工智能(AI)系统已越来越多地用于卫生保健领域,这些系统可能有助于发展和增强人类在诊断、治疗和患者护理和卫生保健系统管理方面的能力。据称,人工智能系统有能力改变医疗保健,例如,改进风险预测,增强患者与护理提供者的关系,优化操作和资源分配。此外,人工智能将在院前警报和住院方面帮助患者完成整个旅程,并最终为院后护理创造途径。Seibert等人对人工智能在护理领域应用前景的证据基础进行了快速回顾,发现从292项纳入的研究样本中,大多数(29.8%)描述了人工智能在医院环境中的应用。此外,他们报告说,“护理协调和沟通是常见的话题,其中包括人工智能方法对护理文档中的信息进行分类,支持决策,并为协调和护理的连续性提供信息”。然而,只有少数出版物超越了概念验证研究,很少有研究评估了人工智能对临床和组织结果的影响。在一篇观点文章中,伦敦写道,人工智能系统克服碎片化、不协调和无根据的医疗实践的能力,因开发人工智能系统的生态系统遭受这些同样缺陷的程度而受挫。此外,他认为,人工智能的现状有可能给临床护理的不必要变化增加另一个维度。为了更好地把握人工智能在改善患者护理方面的价值,London指出,可以应用一个框架来表明人工智能系统的成熟程度,以及支持特定临床效用主张的证据水平。此外,他提出了实施科学在构建和评估在医疗保健环境中实施人工智能系统的建议方面发挥更大作用的观点。为了促进这一领域的研究,并阐明人工智能是否、如何以及何时实现其在护理协调方面的承诺,《国际护理协调杂志》将推出一个特刊,邀请作者提交相关工作。请访问该杂志的网站,了解定于2024年初出版的《协调》特刊的详细信息。在最新一期的《国际护理协调杂志》上,Kokorelias等人发表了一项关于痴呆症特定导航程序的实施特征的范围审查结果,以帮助整合各种环境下的护理。根据22项研究(主要来自美国),确定了痴呆患者导航项目成功实施的关键因素。这些因素符合实施研究综合框架(CFIR)的构建,为指导痴呆症特异性导航的实施提供了理论基础。Kokorelias等人通过探索接受加拿大医院到家庭过渡病人导航项目服务的具有复杂护理需求的老年人的经验,能够分享重要的经验教训。这项定性研究的一个重要见解是,患者导航员可以很好地提高向社区居住的老年人提供的护理质量,并且可以解决多个医疗保健机构之间护理协调方面的差距。Kallio等人探讨了在芬兰背景下,为有特殊需要的儿童提供服务领域的未来专业人员如何为跨专业合作做好准备。在8所大学的24门课程中,有38门课程侧重于跨专业合作。考虑到跨专业合作的需要,Kallio等人发现,这些课程大多只提供给某个研究项目,而不与其他学科互动,这是矛盾的。从他们的分析中得出的重要建议可能对芬兰和其他地方的研究具有相关性。这期《国际护理协调杂志》的最后一篇论文是Hynes和Thomas的一篇重点文章,他们提出了一个新的医疗保健和护理协调的综合理论模型。他们认为,尽管护理模型已经发展到衡量护理协调的各个方面,但目前的理论模型仍未改变。他们提出的模型预计将作为社论
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CoordinAtIon
Artificial Intelligence (AI) systems have been increasingly used in health care with the potential that such systems may help develop and augment the capacity of humans in diagnostics, therapeutics, and management of patient care and health care systems. It is claimed that AI systems have the capability to transform health care by, for example, improving risk prediction, augmenting patient– care provider relationships, and optimizing operations and resource allocation. Moreover, it is indicated that AI will be helping the complete journey of patients in terms of prehospital alert and in-hospital stay, and eventually, creating a pathway for post-hospital care. In a rapid review covering the evidence base for promising AI application scenarios for nursing care, Seibert et al. found that from a sample of 292 included studies, most (29.8%) describe AI applications in hospital settings. Further, they report that ‘care coordination and communication are frequent topics, which among others, include AI approaches classifying information in nursing documentation, supporting decision-making, and yielding information for coordination and continuity of care’. However, only a few publications went beyond proof-of-concept studies and few studies have assessed the effects of AI on clinical and organizational outcomes. In a perspective piece, London writes that the ability of AI systems to overcome fragmented, uncoordinated, and unwarranted medical practices is frustrated by the degree to which the ecosystems in which AI systems are being developed suffer from these same shortcomings. Moreover, he argues that the current state of AI has the potential to simply add another dimension to unnecessary variation in clinical care. To get a better grip on the value of AI for improving patient care, London points to applying a framework for indicating the level of maturity of AI systems and the level of evidence supporting specific claims to clinical utility. Further, he makes a point for implementation science to play a greater role in structuring and evaluating proposals to implement AI systems in healthcare settings. To stimulate research in this field and to clarify whether, how and when AI lives up to its promise regarding care coordination, the International Journal of Care Coordination will launch a special issue inviting authors to submit relevant work. Please visit the journal’s website for details about the special issue on CoordinAtIon scheduled for early 2024. In the current issue of the International Journal of Care Coordination, Kokorelias et al. present the findings of a scoping review regarding the implementation characteristics of dementia-specific navigation programs to help the integration of care across various settings. Based on 22 studies, mostly from the United States, key factors to the successful implementation of navigation programs for persons living with dementia were identified. With these factors fitting the constructs of the Consolidated Framework for Implementation Research (CFIR), a theoretical foundation to guide the implementation of dementia-specific navigation was provided. By exploring the experiences of older adults with complex care needs who have received services from a Canadian hospital-to-home transition patient navigation program, Kokorelias et al. were able to share important lessons. One important insight from this qualitative study is that patient navigators are well-positioned to improve the quality of care delivered to community-dwelling older adults and that they may address gaps in the coordination of care across multiple healthcare settings. Kallio et al. explored how future professionals in the field of service provision to children with special needs are being prepared for interprofessional collaboration in the Finnish context. From 24 curricula at eight universities, 38 courses focused on interprofessional collaboration. Considering the need for interprofessional collaboration, Kallio et al. found it contradictory that most of these courses were provided exclusively to a certain study programme without interaction with other disciplines. Important recommendations follow from their analysis that may hold relevance for studies in Finland and elsewhere. The final paper in this issue of the International Journal of Care Coordination is a focus article by Hynes and Thomas who propose a new integrated theoretical model of healthcare and care coordination. They argue that whereas care models have evolved to measure aspects of care coordination, current theoretical models remained unchanged. Their proposed model is expected to serve as Editorial
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来源期刊
CiteScore
3.10
自引率
14.30%
发文量
15
期刊介绍: The International Journal of Care Coordination (formerly published as the International Journal of Care Pathways) provides an international forum for the latest scientific research in care coordination. The Journal publishes peer-reviewed original articles which describe basic research to a multidisciplinary field as well as other broader approaches and strategies hypothesized to improve care coordination. The Journal offers insightful overviews and reflections on innovation, underlying issues, and thought provoking opinion pieces in related fields. Articles from multidisciplinary fields are welcomed from leading health care academics and policy-makers. Published articles types include original research, reviews, guidelines papers, book reviews, and news items.
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