Method of nested linear convolutions for estimating the population's health quality

Marina Djakovich, Institute of industrial medicine and human Ecology, Russia
Ivan Finogenko, Institute of Industrial Medicine and Human Ecology, Russia

In mass screening we used a computer-aided system intended on application of the Bayes algorithm for quantitative estimation of risks of main pathological syndromes on the basis of anonymous sociological inquiry. It allows to give quantitative measure of risk of the most widely spread general pathology syndromes (WSGPS). Constructing of integrated criteria of health quality (HQ) is solved by decomposition of the main characteristics of WSGPS with weighting coefficients determined by experts. The HQ is estimated by a vector criterion, transformed into the scalar form by the method of nested linear convolutions. The multiple convolution of the two integrated estimates (multiplicity and frequency of WSGPS)is the generalized criterion of HQ. The technique of gradation of HQ by scaling the values of integrated criteria is grounded. The method proposed allows experts to estimate HQ of the native population on the northern territory of East Siberia.