Center for Advanced Studies, Research and Development in Sardinia (CRS4), Loc. Piscina Manna, Ed.1, 09010 Pula, CA, Italy.
Center for Advanced Studies, Research and Development in Sardinia (CRS4), Loc. Piscina Manna, Ed.1, 09010 Pula, CA, Italy.
Int J Med Inform. 2018 Dec;120:147-156. doi: 10.1016/j.ijmedinf.2018.10.007. Epub 2018 Oct 17.
The increasing usage of high throughput sequencing in personalized medicine brings new challenges to the realm of healthcare informatics. Patient records need to accommodate data of unprecedented size and complexity as well as keep track of their production process. In this work we present a solution for integrating genomic data into electronic health records via openEHR archetypes.
We use the popular Variant Call Format as the base format to represent genetic test results within openEHR. We evaluate existing openEHR archetypes to determine what can be extended or specialized and what needs to be developed ex novo.
Eleven new archetypes have been developed, while an existing one has been specialized to represent genomic data. We show their applicability to rare genetic diseases and compare our approach to HL7 FHIR.
The proposed model allows to represent genetic test results in health records in a structured format. It supports different levels of abstraction, allowing both automated processing and clinical decision support. It is extensible via external references, allowing to keep track of data provenance and adapt to future domain changes.
高通量测序在个性化医疗中的应用越来越广泛，这给医疗保健信息学领域带来了新的挑战。患者记录需要容纳前所未有的规模和复杂性的数据，并跟踪其生产过程。在这项工作中，我们提出了一种通过 openEHR 原型将基因组数据集成到电子健康记录中的解决方案。
我们使用流行的 Variant Call Format 作为基础格式，在 openEHR 中表示遗传测试结果。我们评估现有的 openEHR 原型，以确定可以扩展或专门化的内容，以及需要从头开发的内容。
已经开发了 11 个新原型，同时对一个现有原型进行了专门化，以表示基因组数据。我们展示了它们在罕见遗传疾病中的适用性，并将我们的方法与 HL7 FHIR 进行了比较。
所提出的模型允许以结构化格式在健康记录中表示遗传测试结果。它支持不同的抽象级别，允许自动处理和临床决策支持。它可以通过外部引用进行扩展，允许跟踪数据来源，并适应未来的领域变化。
