Gazzarata Roberta, Chronaki Catherine, Ricciardi Francesco, Giuliani Francesco, Zampognaro Paolo, Mercalli Franco, Allocca Carlo, Gaeta Eugenio, Fico Giuseppe, Cangioli Giorgio
HL7 Europe, Brussels, Belgium.
Casa Sollievo della Sofferenza Research Hospital, San Giovanni Rotondo, Italy.
Stud Health Technol Inform. 2023 Oct 20;309:106-110. doi: 10.3233/SHTI230751.
Telemedicine can provide benefits in patient affected by chronic diseases or elderly citizens as part of standard routine care supported by digital health. The GATEKEEPER (GK) Project was financed to create a vendor independent platform to be adopted in medical practice and to demonstrate its effect, benefit value, and scalability in 8 connected medical use cases with some independent pilots. This paper, after a description of the GK platform architecture, is focused on the creation of a FHIR (Fast Healthcare Interoperability Resource) IG (Implementation Guide) and its adoption in specific use cases. The final aim is to combine conventional data, collected in the hospital, with unconventional data, coming from wearable devices, to exploit artificial intelligence (AI) models designed to evaluate the effectiveness of a new parsimonious risk prediction model for Type 2 diabetes (T2D).
作为数字健康支持的标准常规护理的一部分,远程医疗可以为慢性病患者或老年公民带来益处。GATEKEEPER(GK)项目获得资助,旨在创建一个独立于供应商的平台,以便在医疗实践中采用,并通过一些独立试点在8个相关医疗用例中展示其效果、效益价值和可扩展性。本文在描述了GK平台架构之后,重点介绍了FHIR(快速医疗保健互操作性资源)IG(实施指南)的创建及其在特定用例中的应用。最终目标是将医院收集的传统数据与可穿戴设备产生的非传统数据相结合,以利用人工智能(AI)模型来评估一种新的简约型2型糖尿病(T2D)风险预测模型的有效性。