Abstract
In general, the importance of cluster analysis is that one can evaluate elements by clustering multiple homogeneous data; the main objective of this analysis is to collect the elements of a single, homogeneous group into different divisions, depending on many variables. This method of analysis is used to reduce data, generate hypotheses and test them, as well as predict and match models. The research aims to evaluate the fuzzy cluster analysis, which is a special case of cluster analysis, as well as to compare the two methods—classical and fuzzy cluster analysis. The research topic has been allocated to the government and private hospitals. The sampling for this research was comprised of 288 patients being treated in 10 hospitals. As the similarity between hospitals of the study sample was measured according to the standards of quality of health services under fuzzy conditions (a case of uncertainty of the opinions of patients who were in the evaluation of health services provided to them, which was represented by a set of criteria and was measured in the form of a Likert five-point scale). Moreover, those criteria were organized into a questionnaire containing 31 items. The research found a number of conclusions, the most important is that both methods of hierarchical cluster analysis and fuzzy cluster analysis, classify the hospitals of the research sample into two clusters, each cluster comprises a group of hospitals that depend on applying health quality service standards. The second important conclusion is that the fuzzy cluster analysis is more suitable for the classification of the research sample compared to hierarchical cluster analysis.
Highlights
The health sector is one of the most important sectors in any country because it is closely linked to the health and life of human beings, Modern societies are paying great attention to the quality of health services to improve it in all health institutions
There have been several studies concerning the quality of health services in hospitals, but our paper differs from these studies in the use of two methods of cluster analysis
The hospitals in the research sample were divided into two clusters as shown in Table 4: As it appeared that the hospitals (Al Talimi, Al Basrah, Al Fayhaa, Al Mosawi, Al Zuber)had the highest membership degree in the first cluster while the (Al Mawanaa, Al Shifaa, Private Child, Abn Al-Betar, Al Mowasat) had the highest degree of membership in the second cluster
Summary
The health sector is one of the most important sectors in any country because it is closely linked to the health and life of human beings, Modern societies are paying great attention to the quality of health services to improve it in all health institutions. The fuzzy cluster method is based on giving views a degree of membership between zero and one in one or more clusters This is mathematically represented as follows: μik ∈ [0,1], 1 ≤ i ≤ c , 1 ≤ k ≤ p c. There is a set of coefficients used to select the number of suitable clusters for the classification of observations using the cluster analysis method, including the following. It is mathematically defined as: TFhce(Uv)aCl=uuetcol∑efciv=e1Dcl∑−upk1n=n1μ'spi2kpartitio...n(c6o)efficient, Fc(U), is, 0 < Fc(U) < 1 If Fc(U) = 1;This indicates that there is no fuzziness in the data, while if Fc(U) = 0, it means a complete fuzziness is in the data
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