OBJECTIVES: Multivariate statistical analysis techniques are helpful to identify associations between multidimensional health system performance indicators. This study is designed to explore the interrelationships between a set of health outcomes and a set of health system performance indicators.

METHODS: A combinative strategy of explanatory factor analysis and canonical correlation coefficient is used to define linear structural relations between study variables. Province-based data gathered from official statistical records of Turkish Statistical Institute for the year 2019. Life expectancy at birth, infant mortality rate and crude death rate were accepted as health outcome indicators.

RESULTS: Explanatory factor analysis indicated two independent variable groups which are: (i) health human resources & capacity and (ii) health services utilization characteristics. Canonical correlation analysis illustrate good performance to define sparse linear combinations of the two groups of variables. There exists strong positive correlations between health outcomes and health human resources & capacity indicators (rc= 0.83; p < 0.001) and health services utilization indicators (rc=0.59; p<0.001), respectively.

CONCLUSIONS: Study findings support the view that there is a linear and strong positive relationship between health outcomes and health human resources & capacity indicators. Further studies will combine big data analytics with multivariate statistical analysis techniques by studying on big health system performance datasets.