Addressing Geographical Disparities in the Allocation of Hospital Human Resources: An Examination of Health Inequalities in Iran Publisher Pubmed



Mostafavi H ; Mohamadi E ; Takian A ; Bakhtiari A ; Jafarzadeh J ; Olyaeemanesh A
Source: Human Resources for Health Published:2026

Abstract

Background: Human resources are fundamental to improving both service quality and patient outcomes. Given the critical role of accurate data on workforce distribution as a key hospital resource in planning and policymaking, this study aims to assess inequalities in the distribution of hospital human resources and their association with hospital mortality rates across the provinces of Iran. Data and methods: This cross-sectional quantitative study covered 31 provinces across Iran, analyzing data from 383 districts, which represent a comprehensive national-level examination of human resource distribution in the healthcare sector. The Gini coefficient was calculated at both national and sub-national levels. Additionally, stratified analyses were conducted by region to determine whether inequalities were more pronounced in specific geographic areas. Results: The analysis of hospital human resources revealed mean physician and nurse densities of 0.34 and 1.28 per bed, respectively, with relative ratios (RR) of 0.67 and 0.80. The Gini coefficients indicated moderate inequality for physicians (0.19) and low inequality for nurses (0.10), while other staff showed intermediate values (mean 0.44, Gini 0.15). Variability across provinces was reflected in standard deviations, with the highest inequality observed in physician distribution (max Gini 0.59). These findings highlight uneven distribution patterns of hospital workforce components. Conclusions: The Gini coefficients indicate notable disparities, particularly among physicians, where some provinces experience far worse staffing levels compared to others. Targeted interventions, including incentivizing healthcare professionals to work in underserved areas and improving resource allocation models, are essential to enhance the fairness and efficiency of Iran’s healthcare system. © The Author(s) 2026.