Dilemmas and prospects of artificial intelligence technology in the data management of medical informatization in China: A new perspective on SPRAY-type AI applications.

IF 2.2 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Lu Lu, Yun Zhong, Shuqing Luo, Sichen Liu, Zhongzhou Xiao, Jinru Ding, Jin Shao, Hailong Fu, Jie Xu
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引用次数: 0

Abstract

Objectives: This study aims to address the critical challenges of data integrity, accuracy, consistency, and precision in the application of electronic medical record (EMR) data within the healthcare sector, particularly within the context of Chinese medical information data management. The research seeks to propose a solution in the form of a medical metadata governance framework that is efficient and suitable for clinical research and transformation. Methods: The article begins by outlining the background of medical information data management and reviews the advancements in artificial intelligence (AI) technology relevant to the field. It then introduces the "Service, Patient, Regression, base/Away, Yeast" (SPRAY)-type AI application as a case study to illustrate the potential of AI in EMR data management. Results: The research identifies the scarcity of scientific research on the transformation of EMR data in Chinese hospitals and proposes a medical metadata governance framework as a solution. This framework is designed to achieve scientific governance of clinical data by integrating metadata management and master data management, grounded in clinical practices, medical disciplines, and scientific exploration. Furthermore, it incorporates an information privacy security architecture to ensure data protection. Conclusion: The proposed medical metadata governance framework, supported by AI technology, offers a structured approach to managing and transforming EMR data into valuable scientific research outcomes. This framework provides guidance for the identification, cleaning, mining, and deep application of EMR data, thereby addressing the bottlenecks currently faced in the healthcare scenario and paving the way for more effective clinical research and data-driven decision-making.

人工智能技术在中国医疗信息化数据管理中的困境与前景:SPRAY型人工智能应用的新视角。
研究目的本研究旨在解决电子病历(EMR)数据在医疗保健领域应用中,尤其是在中国医疗信息数据管理中面临的数据完整性、准确性、一致性和精确性等关键挑战。研究试图以医疗元数据管理框架的形式提出解决方案,该框架既高效又适用于临床研究和转化。研究方法文章首先概述了医疗信息数据管理的背景,并回顾了与该领域相关的人工智能(AI)技术的发展。然后,文章介绍了 "服务、患者、回归、基底/途径、酵母"(SPRAY)型人工智能应用作为案例研究,以说明人工智能在 EMR 数据管理中的潜力。研究结果研究发现,中国医院在 EMR 数据转化方面的科学研究十分匮乏,并提出了医疗元数据治理框架作为解决方案。该框架以临床实践、医学学科和科学探索为基础,通过整合元数据管理和主数据管理,实现对临床数据的科学治理。此外,该框架还纳入了信息隐私安全架构,以确保数据得到保护。结论在人工智能技术的支持下,拟议的医疗元数据管理框架为管理 EMR 数据并将其转化为有价值的科研成果提供了一种结构化方法。该框架为 EMR 数据的识别、清理、挖掘和深度应用提供了指导,从而解决了医疗保健领域目前面临的瓶颈问题,为更有效的临床研究和数据驱动决策铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Health Informatics Journal
Health Informatics Journal HEALTH CARE SCIENCES & SERVICES-MEDICAL INFORMATICS
CiteScore
7.80
自引率
6.70%
发文量
80
审稿时长
6 months
期刊介绍: Health Informatics Journal is an international peer-reviewed journal. All papers submitted to Health Informatics Journal are subject to peer review by members of a carefully appointed editorial board. The journal operates a conventional single-blind reviewing policy in which the reviewer’s name is always concealed from the submitting author.
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