Vyne Medical与客户之间的紧密合作推动持续改进-动脉网

Tight Collaboration Between Vyne Medical and Client Drives Continuous Improvement

Healthcare IT Today 等信源发布 2025-11-04 17:06

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AI has proven itself as a way to remove the burden of scanning, identifying, and uploading information. For

人工智能已经被证明是一种消除扫描、识别和上传信息负担的方法。对于

Nemours Children’s Health

内穆尔儿童健康中心

, AI solutions from

，来自

Vyne Medical

维纳医学

completely restructured and optimized their document handling practices.

彻底重组并优化了他们的文件处理实践。

Cathy Murphy, HIM Operations Manager at Nemours Children’s Health, gives an account in this video at the AHIMA Annual Conference of what data management consisted of before automation, and how Vyne Medical’s automated systems have transformed their practices. With the same staff, they can meet turnaroud times consistently and relieve clerical burdens on staff..

凯茜·墨菲是内穆尔儿童健康中心的HIM运营经理，她在AHIMA年度会议上的这段视频中讲述了自动化之前的数据管理情况，以及Vyne Medical的自动化系统如何改变了他们的实践。在员工人数不变的情况下，他们能够持续满足周转时间，并减轻员工的文书负担。

Andrew Loeffler, Technical Project Manager at Vyne Medical, meets with Nemours every two weeks to check on the progress of current data collection projects and discover new ones. Most of the operations that used to be performed through a sequence of manual steps are now available through the Vyne Medical API.

Vyne Medical的技术项目经理安德鲁·洛夫勒每两周与Nemours会面一次，检查当前数据收集项目的进展并发现新项目。过去通过一系列手动步骤执行的大部分操作现在都可以通过Vyne Medical API实现。

They continuously look at processes that are still done manually to find automation possibilities..

他们不断查看仍然手动完成的流程，以寻找自动化可能性。

Their old system revolved around a health information management system that had been originally designed for the accounts payable department. It was never adequate for larger needs such as patient registration, labs, and referrals.

他们的旧系统围绕着一个最初为应付账款部门设计的健康信息管理系统，这个系统始终无法满足诸如患者登记、实验室和转诊等更大需求。

Nemours at that time had three separate teams for data entry, a total of 50 people. A clerical team handled legal and other such documents, a second team handled referrals, and a third processed lab data such as imaged and diagnostic reports. They had to make sure each incoming document went into the right record..

当时，内穆尔有三个独立的数据录入团队，共计50人。一个文职团队负责处理法律文件及其他类似文档，第二个团队负责处理转诊事宜，第三个团队则负责处理实验室数据，如影像和诊断报告。他们必须确保每份 incoming 文件进入正确的记录。

The two Vyne Medical modules that took on these tasks were

这两个承担这些任务的Vyne Medical模块是

HealthyData

健康数据

, which extracts actionable information from faxes and scans, and

，该系统从传真和扫描件中提取可操作的信息，并且

LabDE

实验室

, which enters lab data into the EHR. These tools were born out of the

，将实验室数据输入电子健康记录（EHR）。这些工具源于

merger between Vyne Medical and Extract Systems

Vyne Medical 与 Extract Systems 的合并

. Both tools rely on machine learning and natural language processing. Loeffler describes how they compare the fields they suggest with the corrections made by a staff person, and refine the AI model.

这两种工具都依赖于机器学习和自然语言处理。洛弗勒描述了他们如何将系统建议的字段与工作人员所做的修正进行比较，从而优化人工智能模型。

Now Nemours has combined its staff into a single team, everyone trained to handle all tasks. Much a referral is automated. Searching for data is easy.

现在，内穆尔将其员工合并为一个团队，所有人都接受过处理所有任务的培训。大部分转诊是自动化的。数据搜索非常容易。

In summary, Loeffler suggests that providers find an important but easy task to “get something up and running,” then grow from there. Watch the video for more details about the data environment at Nemours and what AI automation can accomplish.

总之，洛夫勒建议供应商找一个重要的但简单的任务“让某些东西先运行起来”，然后在此基础上逐步扩展。观看视频以了解更多关于内穆尔的数据环境以及人工智能自动化能够实现的成果。

Learn more about Nemours Children’s Health:

了解更多关于Nemours儿童健康的信息：

https://www.nemours.org/

Learn more about Vyne Medical:

了解有关 Vyne Medical 的更多信息：

https://vynemedical.com/

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