将Garmin可穿戴数据集成到基于fhir的医疗系统中,以提高互操作性。

Somayeh Abedian, Eugene Yesakov, Stanislav Ostrovskiy, Rada Hussein
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引用次数: 0

摘要

随着可穿戴技术在日常生活中变得越来越普遍,将患者生成的健康数据(PGHD)集成到临床系统中已成为数字健康的一个关键领域。本研究探讨了如何通过Fitrockr平台将心率、步数、睡眠模式和活动水平等数据(通过Garmin Vívoactive 4智能手表捕获)引入基于心率的医疗保健系统。我们将探讨这些数据如何与关键的快速医疗保健互操作性资源(FHIR)(如观察、设备和患者)保持一致。此外,我们评估了模块化开放研究环境(MORE)平台收集的数据集与FHIR的兼容性,并研究了将这些记录传输到FHIR服务器的可行性。这种级别的语义互操作性可以简化PGHD与医院信息系统或其他医疗保健信息系统(尤其是电子病历)的集成,从而增强它们对医疗服务的贡献,特别是在医疗决策方面,并作为临床决策支持系统(CDSS)的来源。本文还讨论了FHIR、openEHR和观察性医疗结果伙伴关系(OMOP)等标准如何协同工作,以确保临床实践和二次分析中可穿戴数据的一致性和有意义的集成。总之,我们反思了实时可穿戴数据可用性、可靠性和隐私在支持更加个性化、数据驱动的医疗保健体验方面的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating Garmin Wearable Data into FHIR-Based Health Systems for Improved Interoperability.

As wearable technologies become more common in everyday life, integrating Patient-Generated Health Data (PGHD) into clinical systems has emerged as a critical area in digital health. This study explores how data such as heart rate, step count, sleep patterns, and activity levels (captured in this study via the Garmin Vívoactive 4 smartwatch) can be brought into FHIR-based healthcare systems through the Fitrockr platform. We explore how these data align with key Fast Healthcare Interoperability Resources (FHIR), such as Observation, Device, and Patient. Additionally, we evaluate the compatibility of collected datasets by the Modular Open Research Environment (MORE) platform with FHIR and examine the feasibility of transferring these records to FHIR servers. This level of semantic interoperability could simplify the integration of PGHD into hospital information systems or other healthcare information systems and especially EHRs, thus enhancing their contribution to care delivery, especially in medical decision making and as a source for Clinical Decision Support Systems (CDSS). The paper also discusses how standards like FHIR, openEHR, and Observational Medical Outcomes Partnership (OMOP) can work together to ensure consistent, meaningful integration of wearable data for both clinical practice and secondary analysis. In summary, we reflect on the importance of real-time wearable data availability, reliability, and privacy in supporting a more personalized, data-driven healthcare experience.

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