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Experience in Developing an FHIR Medical Data Management Platform to Provide Clinical Decision Support

机译:开发FHIR医疗数据管理平台以提供临床决策支持的经验

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摘要

This paper is an extension of work originally presented to pHealth 2019—16th International Conference on Wearable, Micro and Nano Technologies for Personalized Health. To provide an efficient decision support, it is necessary to integrate clinical decision support systems (CDSSs) in information systems routinely operated by healthcare professionals, such as hospital information systems (HISs), or by patients deploying their personal health records (PHR). CDSSs should be able to use the semantics and the clinical context of the data imported from other systems and data repositories. A CDSS platform was developed as a set of separate microservices. In this context, we implemented the core components of a CDSS platform, namely its communication services and logical inference components. A fast healthcare interoperability resources (FHIR)-based CDSS platform addresses the ease of access to clinical decision support services by providing standard-based interfaces and workflows. This type of CDSS may be able to improve the quality of care for doctors who are using HIS without CDSS features. The HL7 FHIR interoperability standards provide a platform usable by all HISs that are FHIR enabled. The platform has been implemented and is now productive, with a rule-based engine processing around 50,000 transactions a day with more than 400 decision support models and a Bayes Engine processing around 2000 transactions a day with 128 Bayesian diagnostics models.
机译:本文是对最初提交给pHealth 2019(第16届国际可穿戴,微米和纳米技术用于个性化健康的会议)的工作的扩展。为了提供有效的决策支持,有必要将临床决策支持系统(CDSS)集成到由医疗保健专业人员日常操作的信息系统中,例如医院信息系统(HIS)或部署个人健康记录(PHR)的患者。 CDSS应该能够使用从其他系统和数据存储库导入的数据的语义和临床环境。 CDSS平台是作为一组单独的微服务开发的。在这种情况下,我们实现了CDSS平台的核心组件,即其通信服务和逻辑推理组件。基于快速医疗保健互操作性资源(FHIR)的CDSS平台通过提供基于标准的界面和工作流程,简化了获得临床决策支持服务的过程。对于使用没有CDSS功能的HIS的医生,这种类型的CDSS可能能够提高他们的护理质量。 HL7 FHIR互操作性标准提供了所有启用了FHIR的HIS均可使用的平台。该平台已经实施,现在已经可以生产,基于规则的引擎每天处理约50,000个事务,具有400多个决策支持模型,而Bayes引擎每天处理约2000个事务,具有128个贝叶斯诊断模型。

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