THE CORRELATION BETWEEN 2 HUMAN RESOURCE INDICATORS, THEIR RATIO AND ESTIMATED LIFE EXPECTANCY IN 49 EUROPEAN AND CENTRAL ASIAN COUNTRIES

The purpose of this paper is check if there is a linear correlation between 2 human resource indicators, their ratio and estimated life expectancy. The paper studies if there is any linear correlation between physicians / 100000 population, pharmacists / 100000 population, the ratio physicians / 100000 population / pharmacists / 100000 population and estimated life expectancy. WHO data from 2013 was used for the following European and Central Asian countries: Albania, Armenia, Austria, Azerbaijan, Belarus, Belgium, Bosnia & Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, France, Finland, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Luxembourg, FYR Macedonia, Malta, Moldova, Netherlands, Norway, Poland, Portugal, Romania, Russia, Serbia, Slovenia, Spain, Sweden, Switzerland, Tajikistan, Turkey, Turkmenistan, Ukraine, United Kingdom and Uzbekistan. Pearson linear correlation coefficient was calculated for all paired indicators and subsequent scatter diagrams were drawn. The r correlation coefficient was compared with critical values of ά = 0.05 and ά = 0.01. It was found that there is a strong linear correlation ά = 0.05 < r < ά = 0.01 between estimated life expectancy and physicians / 100000 population, between estimated life expectancy and pharmacists / 100000 population, as well estimated life expectancy and the ratio physicians / 100000 population / pharmacists / 100000 population. In addition r2 was calculated in order to understand the proportion to which the variation of estimated life expectancy is explained by linear association between the respective human resource indicator and estimated life expectancy. The research shows which of those human resource indicators have a linear correlation whith estimated life expectancy and to what degree. It yields interesting inferences about health care delivery patterns, and can provide policymakers a hint to increase resource allocation efficiency, and improve access to care