医疗保健专业人员对患者护理中人工智能的看法：对不同层面阻碍因素和促进因素的系统评价

Healthcare professionals' perspectives on artificial intelligence in patient care: a systematic review of hindering and facilitating factors on different levels.

作者信息

Henzler Dennis, Schmidt Sebastian, Koçar Ayca, Herdegen Sophie, Lindinger Georg L, Maris Menno T, Bak Marieke A R, Willems Dick L, Tan Hanno L, Lauerer Michael, Nagel Eckhard, Hindricks Gerhard, Dagres Nikolaos, Konopka Magdalena J

机构信息

Institute of Management for Medicine and Health Sciences, University of Bayreuth, Prieserstr. 2, Bayreuth, 95444, Germany.

Department of Ethics, Law and Humanities, Amsterdam UMC, De Boelelaan 1089a, Amsterdam, 1081 HV, The Netherlands.

出版信息

BMC Health Serv Res. 2025 May 1;25(1):633. doi: 10.1186/s12913-025-12664-2.

DOI:10.1186/s12913-025-12664-2

PMID:40312413

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12046968/

Abstract

BACKGROUND

Artificial intelligence (AI) applications present opportunities to enhance the diagnosis, prognosis, and treatment of various diseases. To successfully integrate and utilize AI in healthcare, it is crucial to understand the perspectives of healthcare professionals and to address challenges they associate with AI adoption at an early stage. Therefore, the aim of this review is to provide a comprehensive overview of empirical studies that explore healthcare professionals' perspectives on AI in healthcare.

METHODS

The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. The databases MEDLINE, PsycINFO, and Web of Science were searched in the timeline of 2017 to 2024 using terms related to 'healthcare professionals', 'artificial intelligence', and 'perspectives'. Eligible were peer-reviewed articles that employed quantitative, qualitative, or mixed-methods approaches. Extracted facilitating and hindering factors were analysed according to the dimensions of the socio-ecological model.

RESULTS

Our search yielded 4,499 articles published up to February 2024. After title abstract screening, 150 full-texts were assessed for eligibility, and 72 studies were ultimately included in our synthesis. The extracted perspectives on AI were thematically analyzed using the socioecological model in order to identify various levels of influence and to categorize them into facilitating and hindering factors. In total, we identified 49 facilitating and 43 hindering factors across all levels of the socioecological model. CONCLUSIONS: The findings from this review can serve as a foundation for developing guidelines for AI implementation adressing various stakeholders, from healthcare professionals to policymakers. Future research should focus on the empirical adoption of AI applications and, if possible, further examine the hindering factors associated with different types of AI.

摘要

背景

人工智能（AI）应用为增强各种疾病的诊断、预后和治疗提供了机会。为了在医疗保健领域成功整合和利用人工智能，了解医疗保健专业人员的观点并在早期阶段应对他们与采用人工智能相关的挑战至关重要。因此，本综述的目的是全面概述探索医疗保健专业人员对医疗保健中人工智能观点的实证研究。

方法

本综述按照系统评价和荟萃分析的首选报告项目框架进行。在2017年至2024年的时间范围内，使用与“医疗保健专业人员”、“人工智能”和“观点”相关的术语对MEDLINE、PsycINFO和科学网数据库进行了检索。符合条件的是采用定量、定性或混合方法的同行评审文章。根据社会生态模型的维度对提取的促进因素和阻碍因素进行了分析。

结果

我们的检索共得到截至2024年2月发表的4499篇文章。经过标题摘要筛选，对150篇全文进行了资格评估，最终有72项研究纳入我们的综述。使用社会生态模型对提取的关于人工智能的观点进行了主题分析，以确定不同层次的影响，并将其分为促进因素和阻碍因素。我们在社会生态模型的所有层次上总共确定了49个促进因素和43个阻碍因素。