Health is always
considered as one of the most important issues related to human being. Due to
this importance, governments should primarily provide the best healthcare
services to their citizens. Some indicators can show the quality of healthcare
services in the country. However, one country can have a higher value of one
indicator and can have a lower value of another. Thus, countries can be
categorized in terms of quality of healthcare services. Clustering is a useful
tool for comparing countries and defining the similar countries in terms of
healthcare services. In this study, 28 European Union (EU) countries were
evaluated on 14 health factors and the number of clusters was determined by the
generally accepted rule of thumb. To cluster countries, k-means clustering
method is run in WEKA software for two cluster numbers and four different
initial solution approaches. The resulting clusters were evaluated according to
the Spearman rank correlation coefficient using the order of the GDP per capita
values of the countries in each cluster. It seems using four clusters with
Canopy initial solution approach is the most appropriate way of clustering.
Primary Language | English |
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Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | March 31, 2019 |
Submission Date | April 18, 2018 |
Acceptance Date | January 20, 2019 |
Published in Issue | Year 2019 |