Identifying Influential Variables on Health Expenditure of the Organisation for Economic Co-Operation and Development (OECD) Countries.

Background: Health expenditures of countries have an increasing trend in general and identifying variables affecting health expenditure is an important step toward budget planning for financial sustainability. This study aimed to examine the health expenditure of the Organisation for Economic Co-operation and Development (OECD) countries and identify influential variables.

Methods: The data for the years 2000-2018 of OECD countries' current health expenditure (% of GDP) and economic, demographic, and health variables, considered to affect the health expenditure, to include in the analysis were extracted using the World Bank database (World Bank 2021). Data analys using Chi-Squared Automatic Interaction Detection (CHAID) decision tree technique. Fifteen variables in economic, demographic, and health categories are selected to build the CHAID decision tree.

Results: As a result of CHAID analysis, five variables are identified as influential on current health expenditure, which are gross domestic product per capita, life expectancy at birth, death rate, out-of-pocket expenditure, and fertility rate. Thirty-seven OECD countries are classified into eleven groups by the decision rules in terms of the current health expenditure. The high value of the correlation coefficient between the predicted values and the actual values of health expenditure of countries indicates good prediction performance. Moreover, the regression models built using the identified influential variables as explanatory variables give good forecast accuracy.

Conclusion: As an effective tool, the CHAID decision tree technique provides a rule-based model in the form of a tree with nodes and branches, illustrating the splitting process graphically with identified variables and their cut-off points for classification and prediction.