浅谈人工智能医疗设备应用下医学装备管理新挑战

A brief discussion on the new challenges of medical equipment management under the application of artificial intelligence medical equipment

摘要

本文针对AI医疗设备应用场景，系统分析医学装备管理的核心挑战：在设备全生命周期管理中，存在采购选型与临床需求脱节、运维故障定位难且响应周期长的问题；技术更新方面，因AI技术迭代迅速，设备升级需经复杂测试审批流程，且与医院现有信息系统兼容性不足；人员能力层面，缺乏兼具医学、工程与AI知识的复合型人才，医护人员对设备的操作适应度与信任度也有待提升。为应对上述挑战，提出优化设备全生命周期管理、建立敏捷技术更新机制、加强人员培训与能力建设等策略，以期为医院提升AI医疗设备管理水平提供实践参考，助力医疗行业平稳推进智能化转型。

Abstract

This paper examines emerging challenges in medical equipment management within the context of AI-powered healthcare devices, conducting an in-depth analysis of key issues. In terms of data management, critical challenges include inconsistent quality standards, fragmented data integration difficulties, and prominent risks in data security and privacy protection. Regarding technological updates, the rapid iteration of AI technologies necessitates lengthy and costly processes for rigorous testing, validation, and approval of equipment upgrades. System compatibility issues and integration complexities also require substantial human and material resources for system modifications. Personnel challenges involve both a shortage of interdisciplinary professionals with expertise in both medicine and AI, as well as difficulties such as operational discomfort, insufficient trust, or over-reliance among medical staff. To address these challenges, the paper proposes strategies including establishing data quality control and security systems, optimizing technology update mechanisms, and enhancing staff training programs. These measures aim to improve the management level of AI-powered medical devices and facilitate better adaptation of the healthcare industry to intelligent development trends.

关键词

人工智能 / 医疗设备 / 医学装备管理 / 医院管理 / 医疗技术

Key words

artificial intelligence / medical equipment / medical equipment management / hospital management / medical technology

参考文献

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