PDF(Pubmed)
Abstract：
UNASSIGNED: The use of artificial intelligence (AI), which can emulate human intelligence and enhance clinical results, has grown in healthcare decision-making due to the digitalization effects and the COVID-19 pandemic. The purpose of this study was to determine the scope of applications of AI tools in the decision-making process in healthcare service delivery networks.
UNASSIGNED: This study used a qualitative method to conduct a systematic review of the existing reviews. Review articles published between 2000 and 2024 in English-language were searched in PubMed, Scopus, ProQuest, and Cochrane databases. The CASP (Critical Appraisal Skills Programme) Checklist for Systematic Reviews was used to evaluate the quality of the articles. Based on the eligibility criteria, the final articles were selected and the data extraction was done independently by 2 authors. Finally, the thematic analysis approach was used to analyze the data extracted from the selected articles.
UNASSIGNED: Of the 14 219 identified records, 18 review articles were eligible and included in the analysis, which covered the findings of 669 other articles. The quality assessment score of all reviewed articles was high. And, the thematic analysis of the data identified 3 main themes including clinical decision-making, organizational decision-making, and shared decision-making; which originated from 8 subthemes.
UNASSIGNED: This study revealed that AI tools have been applied in various aspects of healthcare decision-making. The use of AI can improve the quality, efficiency, and effectiveness of healthcare services by providing accurate, timely, and personalized information to support decision-making. Further research is needed to explore the best practices and standards for implementing AI in healthcare decision-making.
UNASSIGNED: This study used a qualitative method to conduct a systematic review of the existing reviews. Review articles published between 2000 and 2024 in English-language were searched in PubMed, Scopus, ProQuest, and Cochrane databases. The CASP (Critical Appraisal Skills Programme) Checklist for Systematic Reviews was used to evaluate the quality of the articles. Based on the eligibility criteria, the final articles were selected and the data extraction was done independently by 2 authors. Finally, the thematic analysis approach was used to analyze the data extracted from the selected articles.
UNASSIGNED: Of the 14 219 identified records, 18 review articles were eligible and included in the analysis, which covered the findings of 669 other articles. The quality assessment score of all reviewed articles was high. And, the thematic analysis of the data identified 3 main themes including clinical decision-making, organizational decision-making, and shared decision-making; which originated from 8 subthemes.
UNASSIGNED: This study revealed that AI tools have been applied in various aspects of healthcare decision-making. The use of AI can improve the quality, efficiency, and effectiveness of healthcare services by providing accurate, timely, and personalized information to support decision-making. Further research is needed to explore the best practices and standards for implementing AI in healthcare decision-making.
摘要：
■使用人工智能（AI），可以模仿人类智能并增强临床结果，由于数字化效应和COVID-19大流行，医疗保健决策的发展有所增长。这项研究的目的是确定AI工具在医疗服务交付网络决策过程中的应用范围。
■本研究采用定性方法对现有综述进行了系统综述。在PubMed中搜索了2000年至2024年之间以英语发表的评论文章，Scopus,ProQuest,和Cochrane数据库。CASP（关键评估技能计划）系统审查清单用于评估文章的质量。根据资格标准，最终的文章由2名作者独立进行,数据提取.最后,使用主题分析方法对从所选文章中提取的数据进行分析。
■在14219条确定的记录中，18篇评论文章符合条件，并包括在分析中，涵盖了其他669篇文章的调查结果。所有评论文章的质量评估得分较高。And,对数据的主题分析确定了3个主要主题，包括临床决策，组织决策，和共同决策；它起源于8个子主题。
■这项研究表明，人工智能工具已应用于医疗保健决策的各个方面。使用AI可以提高质量，效率,和医疗服务的有效性，通过提供准确的，及时,和个性化信息来支持决策。需要进一步的研究来探索在医疗保健决策中实施AI的最佳实践和标准。
■本研究采用定性方法对现有综述进行了系统综述。在PubMed中搜索了2000年至2024年之间以英语发表的评论文章，Scopus,ProQuest,和Cochrane数据库。CASP（关键评估技能计划）系统审查清单用于评估文章的质量。根据资格标准，最终的文章由2名作者独立进行,数据提取.最后,使用主题分析方法对从所选文章中提取的数据进行分析。
■在14219条确定的记录中，18篇评论文章符合条件，并包括在分析中，涵盖了其他669篇文章的调查结果。所有评论文章的质量评估得分较高。And,对数据的主题分析确定了3个主要主题，包括临床决策，组织决策，和共同决策；它起源于8个子主题。
■这项研究表明，人工智能工具已应用于医疗保健决策的各个方面。使用AI可以提高质量，效率,和医疗服务的有效性，通过提供准确的，及时,和个性化信息来支持决策。需要进一步的研究来探索在医疗保健决策中实施AI的最佳实践和标准。
