Analysis of the Demand for the Healthcare Services in Moscow Polyclinics Using Big Data Techniques

Nowadays, healthcare field is tightly connected with mathematics and big data technologies, since the transfer of medical data into digital format assumed terabytes of patient’s data. The demand for medical support is seasonal in nature, and in the winter the number of patient appeals to polyclinics significantly increases than in the summer period. The purpose of this research is to perform a comprehensive analysis of the demand for medical services in Moscow polyclinics to determine the essential amount of resources with the use of advanced analytics. The study contains a description of big data technologies in healthcare; executes the beneficial side of its implementation. The research showed that the science community made a great effort in the development of the industry, however, privacy and security issues, standards establishments still require enormous attention and new efforts to be made in the study area. Besides, the paper has a practical implication with an attempt to present the detailed structure of the demand for therapeutic services. The present study is aimed to develop a forecast model to predict the amount of required resources for each polyclinic, considering the seasonality factor. An attempt to analyze these scenarios was made in order to understand the reason for the increased demand, which would influence the forecast model and the general understanding of the situation in city healthcare sector. The key outputs of the research project include the theoretical base analysis, demand structure for the therapeutic services in polyclinics, comprehensive analysis of this demand, methodological framework for the analysis, forecast model and the template of the forecasted values for each Moscow polyclinic. The study makes an attempt to improve the industry performance indicators. Definitely, this approach needs to be improved and it is the subject for further study.