Suppr超能文献

基于人工智能的临床决策支持系统参与式设计的挑战和促进方法:系统评价方案。

Challenges and Facilitation Approaches for the Participatory Design of AI-Based Clinical Decision Support Systems: Protocol for a Scoping Review.

机构信息

Care & Technology Lab, Furtwangen University, Furtwangen, Germany.

Human-Technology Interaction Lab, Department of Neurosurgery, University Medical Center Freiburg, Freiburg im Breisgau, Germany.

出版信息

JMIR Res Protoc. 2024 Sep 5;13:e58185. doi: 10.2196/58185.

Abstract

BACKGROUND

In the last few years, there has been an increasing interest in the development of artificial intelligence (AI)-based clinical decision support systems (CDSS). However, there are barriers to the successful implementation of such systems in practice, including the lack of acceptance of these systems. Participatory approaches aim to involve future users in designing applications such as CDSS to be more acceptable, feasible, and fundamentally more relevant for practice. The development of technologies based on AI, however, challenges the process of user involvement and related methods.

OBJECTIVE

The aim of this review is to summarize and present the main approaches, methods, practices, and specific challenges for participatory research and development of AI-based decision support systems involving clinicians.

METHODS

This scoping review will follow the Joanna Briggs Institute approach to scoping reviews. The search for eligible studies was conducted in the databases MEDLINE via PubMed; ACM Digital Library; Cumulative Index to Nursing and Allied Health; and PsycInfo. The following search filters, adapted to each database, were used: Period January 01, 2012, to October 31, 2023, English and German studies only, abstract available. The scoping review will include studies that involve the development, piloting, implementation, and evaluation of AI-based CDSS (hybrid and data-driven AI approaches). Clinical staff must be involved in a participatory manner. Data retrieval will be accompanied by a manual gray literature search. Potential publications will then be exported into reference management software, and duplicates will be removed. Afterward, the obtained set of papers will be transferred into a systematic review management tool. All publications will be screened, extracted, and analyzed: title and abstract screening will be carried out by 2 independent reviewers. Disagreements will be resolved by involving a third reviewer. Data will be extracted using a data extraction tool prepared for the study.

RESULTS

This scoping review protocol was registered on March 11, 2023, at the Open Science Framework. The full-text screening had already started at that time. Of the 3,118 studies screened by title and abstract, 31 were included in the full-text screening. Data collection and analysis as well as manuscript preparation are planned for the second and third quarter of 2024. The manuscript should be submitted towards the end of 2024.

CONCLUSIONS

This review will describe the current state of knowledge on participatory development of AI-based decision support systems. The aim is to identify knowledge gaps and provide research impetus. It also aims to provide relevant information for policy makers and practitioners.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58185.

摘要

背景

在过去的几年中,人们对开发基于人工智能(AI)的临床决策支持系统(CDSS)越来越感兴趣。然而,这些系统在实践中的成功实施存在障碍,包括对这些系统的接受度不足。参与式方法旨在让未来的用户参与设计 CDSS 等应用程序,以提高其可接受性、可行性,并从根本上更符合实践需求。然而,基于人工智能的技术的发展,对用户参与和相关方法提出了挑战。

目的

本综述旨在总结和介绍参与式研究和开发涉及临床医生的基于人工智能的决策支持系统的主要方法、方法、实践和具体挑战。

方法

本范围综述将遵循乔安娜·布里格斯研究所(Joanna Briggs Institute)的范围综述方法。合格研究的检索在 MEDLINE 数据库中的 PubMed、ACM 数字图书馆、护理和相关健康综合索引以及 PsycInfo 中进行。使用了适应每个数据库的以下搜索过滤器:期间 2012 年 1 月 1 日至 2023 年 10 月 31 日,仅英语和德语研究,可获取摘要。范围综述将包括涉及开发、试验、实施和评估基于 AI 的 CDSS(混合和数据驱动 AI 方法)的研究。临床人员必须以参与式的方式参与。数据检索将伴随手动灰色文献搜索。然后将潜在出版物导出到参考管理软件中,并删除重复项。之后,将获得的论文集转移到系统综述管理工具中。将对所有出版物进行筛选、提取和分析:标题和摘要筛选将由 2 位独立评审员进行。如有分歧,将邀请第三位评审员参与解决。使用为研究准备的数据提取工具提取数据。

结果

本范围综述方案于 2023 年 3 月 11 日在开放科学框架(Open Science Framework)上注册。当时已经开始全文筛选。在通过标题和摘要筛选的 3118 项研究中,有 31 项进入全文筛选。数据收集和分析以及手稿准备计划在 2024 年第二和第三季度进行。手稿应在 2024 年底提交。

结论

本综述将描述参与式开发基于人工智能的决策支持系统的现状。目的是确定知识差距并提供研究动力。它还旨在为政策制定者和从业者提供相关信息。

国际注册报告标识符(IRRID):DERR1-10.2196/58185。

相似文献

5
Health Care Social Robots in the Age of Generative AI: Protocol for a Scoping Review.
JMIR Res Protoc. 2025 Apr 14;14:e63017. doi: 10.2196/63017.

本文引用的文献

1
Artificial intelligence for clinical decision support for monitoring patients in cardiovascular ICUs: A systematic review.
Front Med (Lausanne). 2023 Mar 31;10:1109411. doi: 10.3389/fmed.2023.1109411. eCollection 2023.
2
A Sociotechnical Systems Framework for the Application of Artificial Intelligence in Health Care Delivery.
J Cogn Eng Decis Mak. 2022 Dec;16(4):194-206. doi: 10.1177/15553434221097357. Epub 2022 May 11.
3
Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke.
PLoS One. 2023 Jan 11;18(1):e0279088. doi: 10.1371/journal.pone.0279088. eCollection 2023.
4
Recommendations for the extraction, analysis, and presentation of results in scoping reviews.
JBI Evid Synth. 2023 Mar 1;21(3):520-532. doi: 10.11124/JBIES-22-00123.
5
Clinical Decision Support Systems.
Visc Med. 2021 Dec;37(6):491-498. doi: 10.1159/000519420. Epub 2021 Sep 28.
7
[Categorizing methods used in participatory research].
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2021 Feb;64(2):146-155. doi: 10.1007/s00103-020-03267-9. Epub 2020 Dec 29.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验