Hertfordshire Business School, University of Hertfordshire, Hatfield, UK
Hertfordshire Business School, University of Hertfordshire, Hatfield, UK.
BMJ Open. 2021 Mar 22;11(3):e044074. doi: 10.1136/bmjopen-2020-044074.
Artificial intelligence (AI) offers great potential for transforming healthcare delivery leading to better patient-outcomes and more efficient care delivery. However, despite these advantages, integration of AI in healthcare has not kept pace with technological advancements. Previous research indicates the importance of understanding various organisational factors that shape integration of new technologies in healthcare. Therefore, the aim of this study is to provide an overview of the existing organisational factors influencing adoption of AI in healthcare from the perspectives of different relevant stakeholders. By conducting this review, the various organisational factors that facilitate or hinder AI implementation in healthcare could be identified.
This study will follow the Joanna Briggs Institute framework, which includes the following stages: (1) defining and aligning objectives and questions, (2) developing and aligning the inclusions criteria with objectives and questions, (3) describing the planned approach to evidence searching and selection, (4) searching for the evidence, (5) selecting the evidence, (6) extracting the evidence, (7) charting the evidence, and summarising the evidence with regard to the objectives and questions.The databases searched will be MEDLINE (Ovid), CINAHL (Plus), PubMed, Cohrane Library, Scopus, MathSciNet, NICE Evidence, OpenGrey, O'REILLY and Social Care Online from January 2000 to June 2021. Search results will be reported based on The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews guidelines. The review will adopt diffusion of innovations theory, technology acceptance model and stakeholder theory as guiding conceptual models. Narrative synthesis will be used to integrate the findings.
Ethics approval will not be sought for this scoping review as it only includes information from previously published studies. The results will be disseminated through publication in a peer-reviewed journal. In addition, to ensure its findings reach relevant stakeholders, they will be presented at relevant conferences.
人工智能(AI)为改善患者预后和提高医疗服务效率提供了巨大的潜力,有望改变医疗服务的提供方式。然而,尽管存在这些优势,人工智能在医疗保健领域的整合并没有跟上技术进步的步伐。先前的研究表明,理解各种组织因素对于理解新技术在医疗保健中的整合至关重要。因此,本研究旨在从不同相关利益相关者的角度概述影响人工智能在医疗保健中采用的现有组织因素。通过进行这项综述,可以确定促进或阻碍医疗保健中人工智能实施的各种组织因素。
本研究将遵循 Joanna Briggs 研究所的框架,包括以下阶段:(1)定义和调整目标和问题,(2)制定和调整与目标和问题一致的纳入标准,(3)描述证据搜索和选择的计划方法,(4)搜索证据,(5)选择证据,(6)提取证据,(7)图表证据,并根据目标和问题总结证据。将搜索的数据库包括 MEDLINE(Ovid)、CINAHL(Plus)、PubMed、Cochrane Library、Scopus、MathSciNet、NICE Evidence、OpenGrey、O'REILLY 和 Social Care Online,时间范围为 2000 年 1 月至 2021 年 6 月。搜索结果将根据系统评价和荟萃分析扩展的首选报告项目进行报告,以扩大审查指南。该审查将采用创新扩散理论、技术接受模型和利益相关者理论作为指导概念模型。将使用叙述性综合来整合研究结果。
本范围审查不需要伦理批准,因为它只包括以前发表的研究的信息。研究结果将通过发表在同行评审期刊上进行传播。此外,为了确保研究结果能够到达相关利益攸关方,将在相关会议上进行介绍。