Problem-Oriented Medical Records for Describing Care Cases Using Multi-Tenants

Sabah Mohammed, J. Fiaidhi, Darien Sawyer
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Abstract

There are countless applications in healthcare for digital personal assistants helping clinicians as well as patients and their families. However, there is no conversational application to understand patient encounters and assist clinicians to describe their clinical cases in association with their medical record like the HL7 FHIR. Building such conversational service requires understanding of the charting schema used to record clinical cases in the clinical setting like the SOAP note as well as having the federated APIs to exchange messages not only between tenants (e.g. Patients and Physicians) but also with different servers including the FHIR electronic healthcare record server. In this paper we described the extension that we have added to our existing QL4POMR framework to have extended ability to represent clinical cases via the use of multi-tenants chatbots based on the SOAP note and the connectivity to the FHIR server. The extension to the QL4POMR uses the Google DialogFlow and the GraphQL-Yoga APIs. This research work is a continuation of our MITACS and NSERC funded work that has started in 2020.
使用多租户描述护理案例的问题导向医疗记录
数字个人助理在医疗保健领域有无数的应用,可以帮助临床医生、患者及其家属。然而,没有会话应用程序来了解患者的遭遇,并帮助临床医生描述他们的临床病例与他们的医疗记录,如HL7 FHIR。构建这样的会话服务需要理解用于在临床环境中记录临床病例的图表模式(如SOAP注释),以及使用联合api不仅在租户(例如Patients和Physicians)之间交换消息,而且还与不同的服务器(包括FHIR电子医疗记录服务器)交换消息。在本文中,我们描述了添加到现有QL4POMR框架中的扩展,通过使用基于SOAP注释和到FHIR服务器的连接的多租户聊天机器人,扩展了表示临床病例的能力。QL4POMR的扩展使用Google DialogFlow和GraphQL-Yoga api。这项研究工作是我们在2020年开始的MITACS和NSERC资助工作的延续。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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