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Payesh 2024, 23(1): 7-17 |
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Ashtarinezhad E, Ahmadi K, Mojiri A. Clustering and ranking Iranian provinces based on some health indicators. Payesh 2024; 23 (1) :7-17
URL: http://payeshjournal.ir/article-1-2178-en.html
URL: http://payeshjournal.ir/article-1-2178-en.html
1- Chief Executive of ME Statistical Software Design Institute, Mashhad, Razavi Khorasan, Iran
2- Department of Computer Science, Faculty of Mathematical Sciences, Shahrekord University, Chaharmahal and Bakhtiari, Iran
3- Department of Statistics, Faculty of Science, University of Zabol, Sistan and Baluchestan, Iran
2- Department of Computer Science, Faculty of Mathematical Sciences, Shahrekord University, Chaharmahal and Bakhtiari, Iran
3- Department of Statistics, Faculty of Science, University of Zabol, Sistan and Baluchestan, Iran
Abstract: (825 Views)
Objective(s): The use of statistical methods to reach the clustering and ranking of health in the society can give a proper view of the state of health in Iranian provinces. The aim of the current research was to cluster and rank Iranian provinces based on some health indicators.
Methods: This was a descriptive study. Clustering and ranking Iranian provinces were carried out according to several items such as the number of employees working in faculties of medical sciences, doctors, paramedics, hospitals, active beds, primary health care providers, laboratories, rehabilitation centers, nuclear medicine centers, clinics and emergency centers. The data were collected from the statistical yearbooks of the provinces. Clustering analysis and data visualizations were performed in R software and ranks were obtained using Topsis software.
Results: The results showed that the provinces of Ilam, Yazd, Semnan, South Khorasan, Zanjan, Ardabil, Fars, Kohgiluyeh and Boyer Ahmad, and Chaharmahal and Bakhtiari had the highest health scores and belonged to the third cluster. Their ranks were 1 to 9 respectively. In the first cluster the following provinces were observed: Qom, Tehran, Alborz, and Hamedan with scores of 0.552, 0.540, 0.460, and 0.36 respectively indicating that these provinces had the lowest health scores and their ranks were 28 to 31. The other provinces appeared on the second cluster and ranked 10 to 27 with almost equal scores.
Conclusion: In order to achieve health equity, the indicators should be improved in provinces belonged to the first cluster to in order to achieve the standard per capita.
Methods: This was a descriptive study. Clustering and ranking Iranian provinces were carried out according to several items such as the number of employees working in faculties of medical sciences, doctors, paramedics, hospitals, active beds, primary health care providers, laboratories, rehabilitation centers, nuclear medicine centers, clinics and emergency centers. The data were collected from the statistical yearbooks of the provinces. Clustering analysis and data visualizations were performed in R software and ranks were obtained using Topsis software.
Results: The results showed that the provinces of Ilam, Yazd, Semnan, South Khorasan, Zanjan, Ardabil, Fars, Kohgiluyeh and Boyer Ahmad, and Chaharmahal and Bakhtiari had the highest health scores and belonged to the third cluster. Their ranks were 1 to 9 respectively. In the first cluster the following provinces were observed: Qom, Tehran, Alborz, and Hamedan with scores of 0.552, 0.540, 0.460, and 0.36 respectively indicating that these provinces had the lowest health scores and their ranks were 28 to 31. The other provinces appeared on the second cluster and ranked 10 to 27 with almost equal scores.
Conclusion: In order to achieve health equity, the indicators should be improved in provinces belonged to the first cluster to in order to achieve the standard per capita.
type of study: Descriptive |
Subject:
Helath Services Management
Received: 2023/06/17 | Accepted: 2023/10/30 | ePublished ahead of print: 2023/11/22 | Published: 2023/12/27
Received: 2023/06/17 | Accepted: 2023/10/30 | ePublished ahead of print: 2023/11/22 | Published: 2023/12/27
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