Low life expectancy is one of the main factors hindering national economic development. Finding a solution to this problem is complicated by enormous differentiation of life expectancy among constituent entities of the Russian Federation. Therefore, assessing the factors increasing life expectancy in heterogeneous regions of the country and developing methodological tools for the application of territorial defragmentation in terms of policy to improve regional health systems are major tasks for public administration. The research aims to find a solution to these problems. On the basis of a detailed analysis of the relevant literature we form a statistical base of indicators influencing life expectancy in RF constituent entities for 10 years; with the help of “hierarchical clustering” we arrange RF constituent entities into eight groups according to the specifics of forming conditions for a long and healthy life; through econometric modeling we assess and identify the impact of individual indicators on life expectancy in different groups of RF constituent entities; on the basis of the modeling results we formulate areas of further research and priorities of the state regional policy in the field of health care. We use general scientific and special methods, including statistical, cartographic, typological, econometric, and cluster methods during the analysis of regional health systems. Statistical data processing and econometric modeling are carried out using statistical packages SPSS Statistics and Gretl. Scientific novelty of the study consists in the clustering of RF constituent entities according to the specifics of forming conditions for increasing life expectancy, which has fundamental importance for improving the effectiveness of territorial management and planning in the field of health care. Practical significance of the work is determined by the tasks of regional policy of Russia and its constituent entities in the sphere of increasing the life expectancy. The results of the study can be useful to the state regional authorities and local authorities for the formation of a set of measures to improve life expectancy
Keywords
strategic planning, life expectancy, clustering, Strategic planning, regional health care system, heterogeneous regions