Integrated assessment model of medical organization management efficiency based on mathematical approach

The article considers the problem of forming an integral indicator for evaluating the effectiveness of management in terms of ranking factors by their informativeness based on mathematical methods of pattern recognition. Since in the modern realities of the crisis, pandemic and other socio-political challenges, medical issues are becoming more and more relevant, it is proposed to take a more qualitative approach to assessing the effectiveness of management in this area. Assumptions are made about an integrated approach to the development of such an assessment that would cover the entire pool of necessary indicators. However, there are difficulties on this path, because in this case there will be many factors; with such a volume of data, calculations are difficult even with the available computing power. It is assumed that some of the parameters can be discarded, but the question arises: which are really less important, and which are simply necessary. To do this, it is proposed to use an algorithm to identify the most informative factors, as well as to use an integral evaluation indicator. The whole procedure for constructing an integral indicator for evaluating the effectiveness of management is divided into several parts. The most important part is the choice of informative factors. It is proposed to consider factors as some vector, with a priori weights found in a certain way. From a mathematical point of view, informativeness is proposed to be understood as the average distance between certain quantities. Then, with the help of the majority committee, the problem of pattern recognition is directly solved. At the same time, a question arises regarding the construction of the majority committee itself, and the main drawback of this approach is also indicated. The Seniority Committee is not considered in this case because of its inefficiency. To eliminate all the vulnerabilities, it is proposed to solve the problem of constructing a separating majority committee for sets by modifying the N. Nilson linear correction algorithm, which is the novelty of this method. This modification makes it possible to build the necessary dividing majority committee for the set, which subsequently leads to the choice of informative factors. The algorithm for selecting the most informative indicators is carried out for each enlarged group of factors. After its implementation, we get a certain number of indicators, much smaller than they were at the beginning, while the question of assigning weight to each factor remains open. To solve this problem, the authors propose the use of expert assessments. Thus, within each enlarged group of indicators, we get the sum of indicators with weighting coefficients, from which an integral indicator of the effectiveness of the management of a medical organization is already obtained.