Planning and organizing the functioning of health care institutions is a priority area of activity of their founders. The purpose of such management activities is to ensure the timeliness, quality and completeness of medical services provided to the clients of the institution. At the same time, an important step is to predict the needs for medical services in future periods of time. Forecasting should be carried out taking into account the socio-demographic, medical and behavioral characteristics of persons -potential consumers of medical services and the characteristics of the population structure of the territory in which the medical institution operates. Thus, the object of research is the processes that arise during the analysis of operational and retrospective statistical, medical and social, expert and other data to determine the forecast values of the levels of demand for certain medical services. The results of the analysis should become the basis for making management decisions on planning and organizing the activities of health care institutions in future periods.In the course of the research, a systematic approach, methods of mathematical modeling and other general scientific methods were used.The research result is a developed method for forecasting the demand for medical services in future periods of time. The method consists in the implementation of four sequential stages of the analysis of the initial data. In this case, it becomes necessary to solve the problems of clustering, classification, identification and forecasting. The accu racy of the predicted values depends on the choice of methods and algorithms for solving the problems posed and on the completeness of the initial data. As a result of applying the method, it is possible to obtain:-аdivision of persons -potential consumers of medical services into groups in accordance with their sociodemographic portraits, medical data and behavioral characteristics;-relationship between the number of educated groups and the demand for various medical services; -predicted values of the number of groups, as well as the demand for medical services.The results can serve as a basis for making managerial decisions on organizing the activities of medical institutions in future periods of time.
The study is devoted to the development of information technology for forecasting based on time series. It has been found that it is important to develop new models and forecasting methods to improve the quality of the forecast. Information technology is based on the evolutionary method of synthesis of the forecast scheme grounded on basic forecast models. The selected method allows you to consider any number of predictive models that may belong to different classes. For a given time series, the weight coefficients with which the models are included in the resulting forecast scheme are calculated by finding the solution to the optimization problem. The method of constructing the objective function for the optimization problem in the form of a linear combination of forecasting results by basic forecasting models is shown. It is proposed to find the solution to the optimization problem using a genetic algorithm. The result of the method is the forecast scheme, which is a linear combination of basic forecast models. To assess the quality of the forecast, it is suggested to use forecasting errors or forecast volatility calculated as the standard deviation. Forecast quality criteria are selected depending on the context of the task. The use of forecast volatility as a quality criterion, with repeated use of technology, will reduce the deviation of forecast values from real data. The structural scheme of information technology is developed. Structurally, information technology consists of two blocks: data processing and interpretation of the obtained values. The result of the application of the developed information technology is the production rules for determining the predicted value of the studied quantity. Experimental verification of the obtained results was performed. The problem of forecasting the number of religious organizations in Ukraine based on statistical data from 1997 to 2000 has been solved. The autoregression method and the linear regression model were chosen as the basic forecast models. Based on the results of using the developed information technology, the weights of the basic models were calculated. It is demonstrated that the obtained forecast scheme allowed to improve the average absolute percentage error and forecast volatility in comparison with the selected models. Keywords: information technology; time series; forecasting; evolutionary technologies; forecast volatility; synthesis of the forecast scheme.
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