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Family practice was the first privatized part of the health care system in Croatia. Recently, 84 % of family practices are privatized. Other 16% of them left within health centers. In order to assess current status of use of the information and communication technology (ICT) in family practice, physicians specializing in the family medicine, being also the postgraduate students of the University of Zagreb, School of Medicine in the year 2004/05, have been surveyed. The sample consisted of 159 physicians. Some kind of information system (IS) exists in 62 % of family practices under lease, 42 % within health centers, and 91 % of completely private offices. Having IS in their offices, physicians use it primarily for administration: reporting, prescriptions, sick leaves, referrals and for billing. Usage of ICT in medical work, electronic medical records, was found at about 50 % of physicians. Doing research based on information stored in e-format, is conducting by 31 % of physicians. Based on e-information 35 % of physicians evaluate their work. About using e-sources of medical knowledge (bibliographic data bases, e-journals): 86 % physicians from private offices, 79% physicians working within health centers, 60 % physicians from offices under lease. Satisfaction with current information system is small (19 %). Their information needs are covered partially. 32 % of physicians said they can get enough information by using their information system. 40 % of physicians feel that ICT gave more efficiency to their work, and 25 % of physicians feel their patients are more satisfied since the IS was put into function. Considering different types of practices – young physicians working in health centers are less satisfied with their ISs than the other two groups of physicians coming from private practice. Data security was practiced by using a password, physical protection, and by daily archiving of data .

Keywords: information system, family practice, electronic medical record, Internet, computer security, bibliographic databases, consumer satisfaction

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 Hrvatski

The electrocardiogram (ECG) is one of the most common ways to record, in an non-invasive manner, a patient’s cardiac activity. Once recorded the information can be pre-processed and subsequently analyzed to assess if the patient is suffering from any forms of cardiac abnormality which may require clinical intervention. In the current study we investigate ways in which more can be obtained from the ECG through analysis of the diagnostic properties of body surface potential maps (BSPM). A set of 192 lead BSPMs recorded from a mixture of 116 normal and abnormal subjects (59 normal vs 57 old myocardial infarction) were analyzed. For each patient, diagnostic features were obtained by calculating isointegral measurements from the QRS, STT, and entire QRST segments. These isointegrals provide a measure of the mean distribution of potential during ventricular depolarization, repolarisation, and a combination of both, respectively. For each isointegral type, 192 discrete measurements, and hence 192 features, were obtained; these correspond with the 192 leads recorded. Subsequent to this a signal-to-noise ratio-based feature ranking methodology was applied to select subsets of the best three, six and ten measurements (features) from the 192 available for each isointegral. These subsets of features were then applied to four different classifiers Naïve Bayes (NB), support vector machine (SVM), multi-layer perceptron (MLP) and random forest (RF) and in each application ten-fold cross validation was employed. It was found that when using the subsets of features obtained from the STT or QRST isointegrals, classification results in excess of 80% were attainable. This was in contrast to the results obtained using the QRS isointegral features where poorer performance (between 62.9% and 74.1%) was observed. The results from this study have illustrated that, for the studied dataset, the mean distribution of potentials during ventricular depolarization, and during ventricular repolarization and depolarization combined possessed greater diagnostic information. Overall it was concluded that this approach to BSPM analysis does provide a useful means for illustrating the usefulness of various features in diagnostic classification.

Key words: electrocardiogram, body surface potential map, myocardial infarction, feature selection

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Ranked model in the form of linear transformation of multivariate feature vectors on a line can reflect a causal order between liver diseases. A priori medical knowledge about order between liver diseases and clinical data sets has been used in the definition of the convex and piecewise linear (CPL) criterion function. The linear ranked transformations have been designed here through minimization of such CPL criterion functions.

Keywords: sequential patterns, ranked linear transformations, convex and piecewise linear (CPL) criterion functions, linear separability of data sets, sequence of liver diseases

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 Polski