Smart hospital: achieving interoperability and raw data collection from medical devices in clinical routine.

IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES
Frontiers in digital health Pub Date : 2024-03-06 eCollection Date: 2024-01-01 DOI:10.3389/fdgth.2024.1341475
Eimo Martens, Hans-Ulrich Haase, Giulio Mastella, Andreas Henkel, Christoph Spinner, Franziska Hahn, Congyu Zou, Augusto Fava Sanches, Julia Allescher, Daniel Heid, Elena Strauss, Melanie-Maria Maier, Mark Lachmann, Georg Schmidt, Dominik Westphal, Tobias Haufe, David Federle, Daniel Rueckert, Martin Boeker, Matthias Becker, Karl-Ludwig Laugwitz, Alexander Steger, Alexander Müller
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引用次数: 0

Abstract

Introduction: Today, modern technology is used to diagnose and treat cardiovascular disease. These medical devices provide exact measures and raw data such as imaging data or biosignals. So far, the Broad Integration of These Health Data into Hospital Information Technology Structures-Especially in Germany-is Lacking, and if data integration takes place, only non-Evaluable Findings are Usually Integrated into the Hospital Information Technology Structures. A Comprehensive Integration of raw Data and Structured Medical Information has not yet Been Established. The aim of this project was to design and implement an interoperable database (cardio-vascular-information-system, CVIS) for the automated integration of al medical device data (parameters and raw data) in cardio-vascular medicine.

Methods: The CVIS serves as a data integration and preparation system at the interface between the various devices and the hospital IT infrastructure. In our project, we were able to establish a database with integration of proprietary device interfaces, which could be integrated into the electronic health record (EHR) with various HL7 and web interfaces.

Results: In the period between 1.7.2020 and 30.6.2022, the data integrated into this database were evaluated. During this time, 114,858 patients were automatically included in the database and medical data of 50,295 of them were entered. For technical examinations, more than 4.5 million readings (an average of 28.5 per examination) and 684,696 image data and raw signals (28,935 ECG files, 655,761 structured reports, 91,113 x-ray objects, 559,648 ultrasound objects in 54 different examination types, 5,000 endoscopy objects) were integrated into the database. Over 10.2 million bidirectional HL7 messages (approximately 14,000/day) were successfully processed. 98,458 documents were transferred to the central document management system, 55,154 materials (average 7.77 per order) were recorded and stored in the database, 21,196 diagnoses and 50,353 services/OPS were recorded and transferred. On average, 3.3 examinations per patient were recorded; in addition, there are an average of 13 laboratory examinations.

Discussion: Fully automated data integration from medical devices including the raw data is feasible and already creates a comprehensive database for multimodal modern analysis approaches in a short time. This is the basis for national and international projects by extracting research data using FHIR.

智能医院:实现临床常规医疗设备的互操作性和原始数据收集。
简介如今,现代技术已被用于诊断和治疗心血管疾病。这些医疗设备可提供精确的测量数据和原始数据,如成像数据或生物信号。到目前为止,这些健康数据还没有被广泛整合到医院信息技术结构中(尤其是在德国),即使进行了数据整合,通常也只是将无价值的结果整合到医院信息技术结构中。原始数据和结构化医疗信息的全面整合尚未建立。本项目旨在设计和实施一个可互操作的数据库(心血管信息系统,CVIS),用于自动整合心血管医学中所有医疗设备数据(参数和原始数据):方法:CVIS 是各种设备与医院 IT 基础设施之间的数据集成和准备系统。在我们的项目中,我们建立了一个集成了专有设备接口的数据库,该数据库可通过各种 HL7 和网络接口集成到电子病历(EHR)中:在 2020 年 7 月 1 日至 2022 年 6 月 30 日期间,我们对整合到该数据库中的数据进行了评估。在此期间,共有 114 858 名患者被自动纳入数据库,其中 50 295 人的医疗数据已被输入。在技术检查方面,超过 450 万个读数(平均每个检查 28.5 个读数)、684,696 个图像数据和原始信号(28,935 个心电图文件、655,761 个结构化报告、91,113 个 X 光对象、54 种不同检查类型中的 559,648 个超声波对象、5,000 个内窥镜检查对象)被纳入数据库。成功处理了 1020 多万条双向 HL7 信息(每天约 14000 条)。98,458 份文件被传送到中央文件管理系统,55,154 份材料(平均每份订单 7.77 份)被记录并储存在数据库中,21,196 项诊断和 50,353 项服务/OPS 被记录并传送。平均每个病人记录了 3.3 次检查;此外,平均还有 13 次实验室检查:讨论:医疗设备的全自动数据整合(包括原始数据)是可行的,并且已经在短时间内为多模式现代分析方法创建了一个全面的数据库。这是通过使用 FHIR 提取研究数据开展国内和国际项目的基础。
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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来源期刊
CiteScore
4.20
自引率
0.00%
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0
审稿时长
13 weeks
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