arXiv:2603.23513cs.CLcs.AI2026-03被引 1

开源AI病历记录工具Berta降低医疗成本,保障数据安全。

Berta: an open-source, modular tool for AI-enabled clinical documentation

论文配图:Berta: an open-source, modular tool for AI-enabled clinical documentation
图 1 · 摘自论文原文
  • 基于语音识别与大模型的模块化系统,数据全程保留在医院内部
  • 8个月服务198名医生,生成超2.8万小时语音,成本低于30美元/人/月
  • 适合关注数据主权与可复用性的医疗机构推广使用

商业AI病历记录系统每月每位医生收费99至600美元,为黑箱运行且不将数据回传机构,限制了数据治理、质量改进和临床流程控制。我们开发了Berta,一款开源模块化AI病历记录平台,并在阿尔伯塔省卫生服务(AHS)部署了定制版本,集成其现有的Snowflake AI数据云基础设施。系统结合自动语音识别与大语言模型,同时确保所有临床数据保留在安全的AHS环境中。在2024年11月至2025年7月的八个月内,198名急诊医生在105个城乡医疗机构中使用该系统,共产生22,148次临床会话及超过2,800小时音频。使用量从每月680次增长至5,530次。平均运营成本低于每位医生每月30美元,相比商业方案降低70%-95%。目前AHS已批准扩展至850名医生。这是首个与现有医疗系统基础设施整合的省级规模AI病历记录部署。通过开源Berta,我们提供了一种可复现、低成本的替代方案,帮助医疗机构在自有安全环境中灵活适配,支持数据主权并推动对AI病历技术的透明评估。

原文摘要 · Abstract (English)

Commercial AI scribes cost \$99-600 per physician per month, operate as opaque systems, and do not return data to institutional infrastructure, limiting organizational control over data governance, quality improvement, and clinical workflows. We developed Berta, an open-source modular scribe platform for AI-enabled clinical documentation, and deployed a customized implementation within Alberta Health Services (AHS) integrated with their existing Snowflake AI Data Cloud infrastructure. The system combines automatic speech recognition with large language models while retaining all clinical data within the secure AHS environment. During eight months (November 2024 to July 2025), 198 emergency physicians used the system in 105 urban and rural facilities, generating 22148 clinical sessions and more than 2800 hours of audio. The use grew from 680 to 5530 monthly sessions. Operating costs averaged less than \$30 per physician per month, a 70-95% reduction compared to commercial alternatives. AHS has since approved expansion to 850 physicians. This is the first provincial-scale deployment of an AI scribe integrated with existing health system infrastructure. By releasing Berta as open source, we provide a reproducible, cost-effective alternative that health systems can adapt to their own secure environments, supporting data sovereignty and informed evaluation of AI documentation technology.

AI医疗病历生成数据安全开源工具

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