An ontology-based approach facilitating unified querying of biosignals and patient records.
Electrocardiography serves as the gold standard for the noninvasive diagnosis of heart disease. Comparison and review between current and previous ECG recordings and clinical data may considerably leverage the physician's diagnostic accuracy. However, clinical data and ECGs are located in heterogeneous and disparate computer systems. On top of this, the plethora of different and mainly proprietary formats for ECG recording and storing, impedes the efforts towards aggregation of medical information. In this paper we propose an approach towards the seamless integration of and access to disparate and heterogeneous sources of medical information, through a semantically enhanced platform called SCP-ECG Integrated Access (SEIA). SEIA provides the means to contextualize SCP-ECG biosignals, by semantically structuring the clinical information they contain. The semantic annotation procedure is enhanced with further processing of the biosignal, including waveform recognition and feature extraction, for automatic or semiautomatic insertion of annotations where missing. Diagnosis and evaluation of a patient's clinical condition is facilitated through integrated temporal comparison of the medical information derived from successive ECGs, in terms of their features and annotations, along with clinical data and measurements originating from the Electronic Medical Record (EMR).
Kokkinaki
Alexandra
A
Lab of Medical Informatics, The Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece. alko@med.auth.gr
Chouvarda
Ioanna
I
Maglaveras
Nicos
N
D003195:Computer Communication Networks; D016494:Computer Security; D003199:Computer Systems; D003628:Database Management Systems; D004562:Electrocardiography / Q000295:instrumentation* / Q000379:methods; D006801:Humans; D016247:Information Storage and Retrieval; D007256:Information Systems; D008491:Medical Informatics Applications; D016347:Medical Records Systems, Computerized; D008991:Monitoring, Physiologic / Q000379:methods; D011381:Programming Languages; D012984:Software; D018511:Systems Integration; D014584:User-Computer Interface