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Payesh
Article . 2024
Data sources: DOAJ
Payesh (Health Monitor) Journal
Article . 2024 . Peer-reviewed
Data sources: Crossref
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Clustering and ranking Iranian provinces based on some health indicators

Authors: Emad Ashtarinezhad; Kambiz Ahmadi; Azadeh Mojiri;

Clustering and ranking Iranian provinces based on some health indicators

Abstract

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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Keywords

Medicine (General), health indicators, R, topsis, R5-920, ranking, Medicine, clustering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Top 10%
Average
gold