Impact of healthcare innovation on the population’s well-being in Russia
The article is devoted to the study of innovative activity in healthcare and its impact on the welfare of Russia’s population, depending on the respondents’ region of residence. Inclusion of various components of the population’s well-being is based on the author’s algorithm for calculating the composite index which includes 21 indicators within 5 sub-indices. To test the hypothesis about the presence of a statistically significant relationship between the level of development of innovations in healthcare and the well-being of the population, as well as in order to highlight innovative factors that affect the well-being of the population, the classical econometric tools and machine learning methods are considered. It allows choosing the most accurate model to describe the studied process and identifying the hidden links between the well-being of the regional population in Russia and their innovative activity. The results of evaluating different models made it possible to choose the Random Forest Regression algorithm in favor of compared Linear Regression Model and the Gradient Boosting Regression technique using control on deferred data. The obtained results of the work can be used in monitoring the state and level of innovative development of the healthcare sector at various levels, in the development of regional and municipal projects and programs to improve the healthcare system.