Stakeholder Perspectives on Clinical Decision Support Tools to Inform Clinical Artificial Intelligence Implementation: Protocol for a Framework Synthesis for Qualitative Evidence.
Stakeholder Perspectives on Clinical Decision Support Tools to Inform Clinical Artificial Intelligence Implementation: Protocol for a Framework Synthesis for Qualitative Evidence.
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DOI：
10.2196/33145
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发表时间：
2022-04-01
影响因子：
1.7
通讯作者：
Beyer, Fiona R.
中科院分区：
文献类型：
--
作者：
Al-Zubaidy, Mohaimen;Hogg, H. D. Jeffry;Maniatopoulos, Gregory;Talks, James;Teare, Marion Dawn;Keane, Pearse A.;Beyer, Fiona R.
关键词：
定量系统综述已确定临床人工智能（AI）赋能工具在现实世界应用中具有足够性能。据我们所知，尚无已发表的报告或方案综合全面的利益相关者观点。缺乏这样一个严谨的基础使“AI鸿沟”长期存在，这继续延误患者受益。
本研究的目的是综合任何医疗环境中计算机化临床决策支持工具的利益相关者观点。综合研究结果将为未来研究以及将AI应用于医疗服务提供信息。
检索策略将使用MEDLINE（Ovid）、Scopus、CINAHL（EBSCO）、ACM数字图书馆和科学引文索引（Web of Science）。在去重之后，将由2名独立评审员进行标题、摘要和全文筛选，并由第三位主题专家进行仲裁。将对纳入研究的质量进行评估以支持解读。将进行最适合的框架综合，由2名独立评审员逐行编码。在适当情况下，这些研究结果将被归入由非采用、放弃、扩大规模、传播和可持续性框架所定义的22个先验主题中的一个。对于异常结果将归纳生成新的领域。研究咨询小组（包括患者和非专业代表）将反复审查结果在主题中的归类。
2021年5月从PROSPERO（CRD42021256005）获得研究注册。最终检索于4月进行，在撰写本文时筛选仍在进行中。全文数据分析将于2021年10月完成。我们预计该研究将于2021年末提交以便开放获取发表。
本文描述了一项定性证据综合的方案，旨在确定所有相关利益相关者在实施计算机化临床决策支持工具方面的障碍和促进因素。本研究结果旨在加速从AI赋能的临床工具中为患者带来益处。
PROSPERO CRD42021256005；https://tinyurl.com/r4x3thvp
DERR1 - 10.2196/33145
Quantitative systematic reviews have identified clinical artificial intelligence (AI)-enabled tools with adequate performance for real-world implementation. To our knowledge, no published report or protocol synthesizes the full breadth of stakeholder perspectives. The absence of such a rigorous foundation perpetuates the “AI chasm,” which continues to delay patient benefit. The aim of this research is to synthesize stakeholder perspectives of computerized clinical decision support tools in any health care setting. Synthesized findings will inform future research and the implementation of AI into health care services. The search strategy will use MEDLINE (Ovid), Scopus, CINAHL (EBSCO), ACM Digital Library, and Science Citation Index (Web of Science). Following deduplication, title, abstract, and full text screening will be performed by 2 independent reviewers with a third topic expert arbitrating. The quality of included studies will be appraised to support interpretation. Best-fit framework synthesis will be performed, with line-by-line coding completed by 2 independent reviewers. Where appropriate, these findings will be assigned to 1 of 22 a priori themes defined by the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability framework. New domains will be inductively generated for outlying findings. The placement of findings within themes will be reviewed iteratively by a study advisory group including patient and lay representatives. Study registration was obtained from PROSPERO (CRD42021256005) in May 2021. Final searches were executed in April, and screening is ongoing at the time of writing. Full text data analysis is due to be completed in October 2021. We anticipate that the study will be submitted for open-access publication in late 2021. This paper describes the protocol for a qualitative evidence synthesis aiming to define barriers and facilitators to the implementation of computerized clinical decision support tools from all relevant stakeholders. The results of this study are intended to expedite the delivery of patient benefit from AI-enabled clinical tools. PROSPERO CRD42021256005; https://tinyurl.com/r4x3thvp DERR1-10.2196/33145
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影响因子：
4
作者：
Carroll C;Booth A;Cooper K
通讯作者：
Cooper K
影响因子：
5.4
作者：
Maniatopoulos, Gregory;Procter, Rob;Boyd, Alan
通讯作者：
Boyd, Alan
影响因子：
7.4
作者：
Greenhalgh T;Wherton J;Papoutsi C;Lynch J;Hughes G;A'Court C;Hinder S;Fahy N;Procter R;Shaw S
通讯作者：
Shaw S
影响因子：
30.8
作者：
Muehlematter, Urs J.;Daniore, Paola;Vokinger, Kerstin N.
通讯作者：
Vokinger, Kerstin N.
DOI：
10.1016/j.ijmedinf.2015.09.005
发表时间：
2015-12-01
影响因子：
4.9
作者：
Miller, Anne;Moon, Brian;Montella, Diane
通讯作者：
Montella, Diane