Clustering and ranking Iranian provinces based on some health indicators

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...

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Main Authors: Emad Ashtarinezhad, Kambiz Ahmadi, Azadeh Mojiri
Format: Article
Language:fas
Published: Iranian Institute for Health Sciences Research 2024-02-01
Series:Payesh
Subjects:
Online Access:http://payeshjournal.ir/article-1-2178-en.pdf
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author Emad Ashtarinezhad
Kambiz Ahmadi
Azadeh Mojiri
author_facet Emad Ashtarinezhad
Kambiz Ahmadi
Azadeh Mojiri
author_sort Emad Ashtarinezhad
collection DOAJ
description 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.
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spelling doaj.art-4ace68e546444f20a3d5711f0db7a2aa2024-01-09T05:27:02ZfasIranian Institute for Health Sciences ResearchPayesh1680-76262008-45362024-02-01231717Clustering and ranking Iranian provinces based on some health indicatorsEmad Ashtarinezhad0Kambiz Ahmadi1Azadeh Mojiri2 Chief Executive of ME Statistical Software Design Institute, Mashhad, Razavi Khorasan, Iran Department of Computer Science, Faculty of Mathematical Sciences, Shahrekord University, Chaharmahal and Bakhtiari, Iran Department of Statistics, Faculty of Science, University of Zabol, Sistan and Baluchestan, Iran 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.http://payeshjournal.ir/article-1-2178-en.pdftopsisclusteringrankinghealth indicators
spellingShingle Emad Ashtarinezhad
Kambiz Ahmadi
Azadeh Mojiri
Clustering and ranking Iranian provinces based on some health indicators
Payesh
topsis
clustering
ranking
health indicators
title Clustering and ranking Iranian provinces based on some health indicators
title_full Clustering and ranking Iranian provinces based on some health indicators
title_fullStr Clustering and ranking Iranian provinces based on some health indicators
title_full_unstemmed Clustering and ranking Iranian provinces based on some health indicators
title_short Clustering and ranking Iranian provinces based on some health indicators
title_sort clustering and ranking iranian provinces based on some health indicators
topic topsis
clustering
ranking
health indicators
url http://payeshjournal.ir/article-1-2178-en.pdf
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AT kambizahmadi clusteringandrankingiranianprovincesbasedonsomehealthindicators
AT azadehmojiri clusteringandrankingiranianprovincesbasedonsomehealthindicators