Purpose

The availability of genetic test data within the electronic health record (EHR) is a pillar of the US vision for an interoperable health IT infrastructure and a learning health system. Although EHRs have been highly investigated, evaluation of the information systems used by the genetic labs has received less attention—but is necessary for achieving optimal interoperability. This study aimed to characterize how US genetic testing labs handle their information processing tasks.

Methods

We followed a qualitative research method that included interviewing lab representatives and a panel discussion to characterize the information flow models.

Results

Ten labs participated in the study. We identified three generic lab system models and their relevant characteristics: a backbone system with additional specialized systems for interpreting genetic results, a brokering system that handles housekeeping and communication, and a single primary system for results interpretation and report generation.

Conclusion

Labs have heterogeneous workflows and generally have a low adoption of standards when sending genetic test reports back to EHRs. Core interpretations are often delivered as free text, limiting their computational availability for clinical decision support tools. Increased provision of genetic test data in discrete and standard-based formats by labs will benefit individual and public health.

中文翻译：

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用于基因检测报告的流行实验室信息系统和数据通信模式的定性研究

目的

电子健康记录 (EHR) 中基因检测数据的可用性是美国实现可互操作的健康 IT 基础设施和学习型健康系统愿景的支柱。尽管对 EHR 进行了深入研究，但对基因实验室使用的信息系统的评估受到的关注较少，但对于实现最佳互操作性是必要的。本研究旨在描述美国基因检测实验室如何处理其信息处理任务。

方法

我们采用了一种定性研究方法，包括采访实验室代表和小组讨论来描述信息流模型。

结果

十个实验室参与了这项研究。我们确定了三个通用实验室系统模型及其相关特征：一个主干系统，带有用于解释遗传结果的额外专门系统，一个处理内务和通信的代理系统，以及一个用于结果解释和报告生成的单一主要系统。

结论

实验室具有异构的工作流程，并且在将基因检测报告发送回 EHR 时通常采用较低的标准。核心解释通常以自由文本的形式提供，限制了它们在临床决策支持工具中的计算可用性。实验室以离散和基于标准的格式提供更多的基因检测数据将有利于个人和公共健康。