Erschienen in:
01.08.2010
The Clinical Application of a PACS-Dependent 12-Lead ECG and Image Information System in E-Medicine and Telemedicine
verfasst von:
Jui-Chien Hsieh, Hsiu-Chiung Lo
Erschienen in:
Journal of Imaging Informatics in Medicine
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Ausgabe 4/2010
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Abstract
This study presents a software technology to transform paper-based 12-lead electrocardiography (ECG) examination into (1) 12-lead ECG electronic diagnoses (e-diagnoses) and (2) mobile diagnoses (m-diagnoses) in emergency telemedicine. While Digital Imaging and Communications in Medicine (DICOM)-based images are commonly used in hospitals, the development of computerized 12-lead ECG is impeded by heterogeneous data formats of clinically used 12-lead ECG instrumentations, such as Standard Communications Protocol (SCP) ECG and Extensible Markup Language (XML) ECG. Additionally, there is no data link between clinically used 12-lead ECG instrumentations and mobile devices. To realize computerized 12-lead ECG examination procedures and ECG telemedicine, this study develops a DICOM-based 12-lead ECG information system capable of providing clinicians with medical images and waveform-based ECG diagnoses via Picture Archiving and Communication System (PACS). First, a waveform-based DICOM-ECG converter transforming clinically used SCP-ECG and XML-ECG to DICOM is applied to PACS for image- and waveform-based DICOM file manipulation. Second, a mobile Structured Query Language database communicating with PACS is installed in physicians’ mobile phones so that they can retrieve images and waveform-based ECG ubiquitously. Clinical evaluations of this system indicated the following. First, this developed PACS-dependent 12-lead ECG information system improves 12-lead ECG management and interoperability. Second, this system enables the remote physicians to perform ubiquitous 12-lead ECG and image diagnoses, which enhances the efficiency of emergency telemedicine. These findings prove the effectiveness and usefulness of the PACS-dependent 12-lead ECG information system, which can be easily adopted in telemedicine.