Document Type : Original Article

Authors

1 MSc, Industrial Management, Jahad Daneshgahi Institute, Yazd, Iran.

2 Lecture, Industrial Management, Yazd University, Yazd, Iran

3 Assistant Professor, Department of Economics, Management and Accounting, Yazd University, Yazd, Iran.

Abstract

Introduction: Health services currently support physical and mental health of individuals and are a prerequisite for sustainable development in every community. However, such benefits cannot be gained unless balanced distribution of health and treatment facilities and equipments among various geographical regions is ensured. This study assessed the status of development and rankings of Iranian provinces in terms of access to indices of health sector.Methods: This applied, descriptive, cross-sectional study surveyed all Iranian provinces (n = 30) in 2008. In order to collect data, online and printed literate was reviewed and the reports of the Ministry of Health and Medical Education and the Iranian Statistics Center were used as references. The taxonomy technique was employed to determine the degree of development of different provinces. In addition, indices were weighted by Shannon's entropy. Finally, technique for order preference by similarity to ideal solution (TOPSIS) was used to rank the provinces of the country in terms of access to health sector indicators.Results: Taxonomy technique showed 12, 9, and 9 provinces to be developed, semi-developed, and underdeveloped, respectively. Shannon's entropy introduced the ratio of the number of pharmacists to the population as the most important indicator. According to TOPSIS, the provinces of Semnan and Sistan-and-Baluchestan ranked the first and last (30th) in access to health services.Conclusion: In order to reduce imbalance, health policy makers and officials are recommended to consider the developmental rankings of the provinces while allocating resources.Keywords: Provinces; Iran; Health Status Indicators; Techniques; Taxonomy; Shannon's Entropy; Technique for Order Preference by Similarity to Ideal Solution.