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Complexity of biomedical data models in cardiology: the Intranet-based AF registry.

机译:心脏病学中生物医学数据模型的复杂性:基于Intranet的AF注册中心。

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Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with major complications. Ongoing research is focused on new pacing devices for alternative treatment of this disease. The objective of an AF registry is to store prospectively all relevant data covering clinical information, quality of life and device parameters and by this means provide a platform for long-term follow-up. For statistical analysis, categorical and numerical items are required, thus a high-granular data structure must be defined and implemented in the clinical setting. Facing the limits of formalization, we developed an XML-based documentation scheme consisting of 619 items in eight tables and implemented it with state-of-the-art Intranet technology. At present detailed information on 88 patients is recorded. The pacing device generates per patient and follow-up visit a file consisting of approximately 400-500 parameters provided on a floppy disk, which are transferred by means of a specific interface into the database. Success factors for integration of a complex research database into the routine workflow of a busy university hospital are interfaces between data sources to enable non-redundant data entry, intensive fine tuning by iterative software engineering and benefit for the clinical users in form of clinical reports and patient-specific summaries. Data quality must be assured by plausibility checks. To get an overview of this complex dataset we developed a dedicated visualization tool. Due to the high number of items a large patient collective must be recruited for statistical evaluation. Interinstitutional cooperation is required for a consensus on common minimal documentation schemes to enable pooling of data.
机译:心房颤动(AF)是最常见的心律不齐,并伴有重大并发症。正在进行的研究集中在可替代该疾病的新型起搏设备上。 AF注册中心的目标是前瞻性地存储涵盖临床信息,生活质量和设备参数的所有相关数据,从而为长期随访提供平台。为了进行统计分析,需要分类和数字项,因此必须在临床环境中定义和实现高粒度数据结构。面对形式化的局限,我们开发了一个基于XML的文档计划,该计划由八个表中的619个项目组成,并使用最新的Intranet技术实现了该计划。目前记录了有关88位患者的详细信息。起搏设备会为每个患者生成一个文件,并在后续访问中生成一个文件,该文件由软盘上提供的大约400-500个参数组成,这些参数通过特定的接口传输到数据库中。将复杂的研究数据库集成到繁忙的大学医院的日常工作流程中的成功因素是数据源之间的接口,以实现非冗余数据输入,通过迭代软件工程进行的密集微调,以及通过临床报告和特定于患者的摘要。必须通过合理性检查来确保数据质量。为了获得此复杂数据集的概述,我们开发了专用的可视化工具。由于项目数量众多,必须招募大量患者进行统计评估。需要机构间合作,以便就共同的最小文件编制计划达成共识,以实现数据汇总。

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