Objectives: The data interchange in the Czech healthcare environment is mostly based on national standards. This paper describes a utilization of international standards and nomenclatures for building a pilot semantic interoperability platform (SIP) that would serve to exchange information among electronic health record systems (EHR-Ss) in Czech healthcare. The work was performed by the national research project of the „Information Society program. Methods: At the beginning of the project a set of requirements the SIP should meet was formulated. Several communication standards (openEHR, HL7 v3, DICOM) were analyzed and HL7 v3 was selected to exchange health records in our solution. Two systems were included in our pilot environment: WinMedicalc 2000 and ADAMEKj EHR. Results: HL7-based local information models were created to describe the information content of both systems. The concepts from our original information models were mapped to coding systems supported by HL7 (LOINC, SNOMED CT and ICD-10) and the data exchange via HL7 v3 messages was implemented and tested by querying patient administration data. As a gateway between local EHR systems and the HL7 message- based infrastructure, a configurable HL7 Broker was developed. Conclusions: Anationwide implementation of a full-scale SIP based on HL7 v3 would include adopting and translating appropriate international coding systems and nomenclatures, and developing implementation guidelines facilitating the migration from national standards to international ones. Our pilot study showed that our approach is feasible but it would demand a huge effort to fully integrate the Czech healthcare system into the European e-health context.

This paper deals with design of an automatic detector for classification of selected cardiac arrhythmias. The proposed algorithms employ the continuous wavelet transform (CWT) combined with an analysis of its contour envelopes. The CWT was used in a detector of R-waves, to distinguish between normal and abnormal beats, and for detection of atrial premature contractions (APCs) and premature ventricular contractions (PVCs). The algorithm was validated by extensive testing on the MIT/BIH database. Searching for a local maximum in wavelet contour envelopes efficiently detects R- peaks. The overall accuracy of its detection tested on 48 half-hour signals is 99.5%. Two types of classifications were tested: 1. classification based on the contour envelope and the detection of significant points with overall accuracy 94.6%, 96.1% for the sinus rhythm (SR), 30.4% APCs, 71.2% PVCs and 2. the localization of maximum of square modulus of CWT coefficients in the area of QRS complex for the determination of PVCs between SR, right bundle branch block (RBBB), APC and other narrow complex arrhythmias with the accuracy 96.8%.