医院安排人工智能:一个简单,可复制和有效的模型
Corentin Biot1, Tressy Tabbuso1, Yoann Marechal2
1Pediatrics, CHU (Centre Hospitalier Universitaire) Charleroi-Chimay, Charleroi, BEL.
Cureus
|January 15, 2026
概括
人工智能 (AI) 大型语言模型 (LLM) 自动化医院安排,减少行政任务和提高公平性. 这种人工智能驱动的系统简化了复杂的班次分配,提高了员工满意度和组织效率.
科学领域:
- 医疗保健管理部门的管理.
- 人工智能的人工智能
- 运营研究 运营研究
背景情况:
- 医院安排是复杂的,涉及服务需求,员工偏好和缺席.
- 传统的日程安排方法会造成行政负担和员工不满.
- 自动化安排可以提高护理的效率和质量.
研究的目的:
- 探索人工智能大型语言模型 (LLM) 用于自动化医院安排.
- 为了简化日程安排,减少手工劳动,提高公平性.
- 为非IT专业人士开发一个用户友好的系统.
主要方法:
- 使用ChatGPT将自然语言指令翻译成VBA宏.
- 使用人工智能生成的VBA创建自动值班和日常活动计划.
- 通过微软Excel收集员工偏好以生成日程表.
- 确保公平的班次分配和角色优先级.
主要成果:
- 显著减少了创建日程表的行政时间.
- 通过一致的规则应用,提高时间表的公平性.
- 尽量减少团队冲突,提高组织效率和员工满意度.
- 由非IT专业人员开发的系统,不需要高级编程技能.
结论:
- 整合微软Excel和AI LLMs为医院安排提供了一个简单,可重复的解决方案.
- 由人工智能驱动的系统减少了行政负担,并促进了公平.
- 这种可适应的模型可以使其他面临类似安排挑战的行业受益.
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