Five Dimensions of AI Readiness (AIR-5D) Framework- A Preparedness Assessment Tool for Healthcare Organizations.

Q2 Medicine Hospital Topics Pub Date : 2024-11-14 DOI:10.1080/00185868.2024.2427641
Vinaytosh Mishra
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Abstract

Background: Artificial Intelligence (AI) has transformative potential in healthcare, and it is very useful in areas such as drug discovery, diagnostics, and patient management. However, there is a lack of tools to assess healthcare organizations' readiness to adopt AI technologies. This study introduces the AI Readiness Five Dimension (AIR-5D) framework, addressing this gap. Methods: The AIR-5D framework was developed using a two-step process: identifying dimensions of AI readiness from literature and weighing these dimensions through expert focus groups. The Analytical Hierarchy Process (AHP) was employed to calculate weights, ensuring consistency and reliability. Results: The results identified five key dimensions: Opportunity Discovery (0.44), Data Management 90.22), IT Environment and Security (0.194), Risk Privacy and Governance (0.101), and Adoption of Technology (0.043). "Opportunity Discovery" was the most critical dimension, while "Adoption of Technology" ranked lowest. Six case studies demonstrated varying AI readiness (score between 3 and 4 on a scale of 5), highlighting challenges in moving beyond AI collaboration to optimization. Conclusions: The AIR-5D framework offers a structured approach for healthcare organizations to assess and enhance their AI readiness. It emphasizes the importance of understanding value, robust data management, and strategic alignment in successful AI adoption.

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人工智能准备度五维框架(AIR-5D)--医疗机构准备度评估工具。
背景:人工智能(AI)在医疗保健领域具有变革潜力,在药物发现、诊断和患者管理等领域非常有用。然而,目前还缺乏评估医疗机构是否准备好采用人工智能技术的工具。本研究引入了人工智能准备度五维(AIR-5D)框架,以弥补这一不足。方法:AIR-5D 框架的开发分为两个步骤:从文献中确定人工智能就绪度的各个维度,并通过专家焦点小组对这些维度进行权衡。采用层次分析法(AHP)计算权重,确保一致性和可靠性。结果结果确定了五个关键维度:机会发现 (0.44)、数据管理 (90.22)、IT 环境和安全 (0.194)、风险隐私和治理 (0.101) 以及技术采用 (0.043)。"机会发现 "是最关键的维度,而 "技术采用 "则排名最低。六项案例研究显示了不同的人工智能就绪程度(在 5 分制中得分介于 3 和 4 之间),凸显了从人工智能合作到优化的挑战。结论:AIR-5D 框架为医疗机构评估和加强其人工智能就绪程度提供了一种结构化方法。它强调了理解价值、健全的数据管理和战略调整对成功采用人工智能的重要性。
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来源期刊
Hospital Topics
Hospital Topics Medicine-Medicine (all)
CiteScore
1.90
自引率
0.00%
发文量
44
期刊介绍: Hospital Topics is the longest continuously published healthcare journal in the United States. Since 1922, Hospital Topics has provided healthcare professionals with research they can apply to improve the quality of access, management, and delivery of healthcare. Dedicated to those who bring healthcare to the public, Hospital Topics spans the whole spectrum of healthcare issues including, but not limited to information systems, fatigue management, medication errors, nursing compensation, midwifery, job satisfaction among managers, team building, and bringing primary care to rural areas. Through articles on theory, applied research, and practice, Hospital Topics addresses the central concerns of today"s healthcare professional and leader.
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