Measuring inequality in physician distributions using spatially adjusted Gini coefficients

Gender difference of geographic distribution of physicians in Japan: three-point analysis of 1994, 2004 and 2014

BACKGROUND

Japan's medical education system produces 9,000 graduates annually. Despite the government's implementation of several strategies, including increasing the number of doctors trained, the country still struggles with a shortage of physicians in rural areas. This study examined this issue, focusing on gender and considering years of physician experience, demographic and geographic factors.

METHODS

We analyzed the Physician Census from 1994, 2004, and 2014, examining data on physicians' gender and the number of years since licensure. To correct the impact of municipal mergers, the analysis was aligned with the number of municipalities in 2014 (1741). We examined data from each physician (gender and years of medical experience) and analyzed the demographic and geographic distribution trend using Spearman correlation coefficients. We then used the Gini coefficient to evaluate the distribution change of physicians based on gender and years of experience.

RESULTS

The number of physicians increased 1.29-fold over the 20-year observation period (1.23-fold for male physicians and 2.17-fold for female physicians), and the percentage of female physicians increased from 13.4% to 20.4%. We found that 87.7% of physicians were concentrated in the top 1/3 municipalities in terms of population. The number of female physicians was higher at 91.8% compared to 86.8% for male physicians. The Gini coefficients were lower for veteran physicians of both sexes than for younger physicians. The Gini coefficient for all physicians was 0.315-0.298-0.298 (male physicians: 0.311-0.289-0.283, female physicians: 0.394-0.385-0.395) The Gini coefficients for female compared to male physicians were higher in all age groups, showing that The distribution of female physicians is skewed toward urban areas.

CONCLUSION

Female physicians are less distributed in rural areas than male physicians. In addition, despite the fact that the number of female physicians has increased more than male physicians over the past 20 years, the geographic ubiquity of female physicians has not improved. Since the trend of increasing the number of female physicians is expected to continue in the future, it is necessary to take some measures, such as providing a work-life balance suitable for female physicians.

Inequalities in healthcare resources and outcomes threatening sustainable health development in Ethiopia: panel data analysis

OBJECTIVE

To measure inequalities in the distributions of selected healthcare resources and outcomes in Ethiopia from 2000 to 2015.

DESIGN

A panel data analysis was performed to measure inequalities in distribution of healthcare workforce, infrastructure, outcomes and finance, using secondary data.

SETTING

The study was conducted across 11 regions in Ethiopia.

PARTICIPANTS

Regional population and selected healthcare workforce.

OUTCOMES MEASURED

Aggregate Theil and Gini indices, changes in inequalities and elasticity of healthcare resources.

RESULTS

Despite marked inequality reductions over a 16 year period, the Theil and Gini indices for the healthcare resources distributions remained high. Among the healthcare workforce distributions, the Gini index (GI) was lowest for nurses plus midwives (GI=0.428, 95% CI 0.393 to 0.463) and highest for specialist doctors (SPDs) (GI=0.704, 95% CI 0.652 to 0.756). Inter-region inequality was the highest for SPDs (95.0%) and the lowest for health officers (53.8%). The GIs for hospital beds, hospitals and health centres (HCs) were 0.592(95% CI 0.563 to 0.621), 0.460(95% CI 0.404 to 0.517) and 0.409(95% CI 0.380 to 0.439), respectively. The interaction term was highest for HC distributions (47.7%). Outpatient department visit per capita (GI=0.349, 95% CI 0.321 to 0.377) and fully immunised children (GI=0.307, 95% CI 0.269 to 0.345) showed inequalities; inequality in the under 5 years of age mortality rate increased overtime (P=0.048). Overall, GI for government health expenditure (GHE) was 0.596(95% CI 0.544 to 0.648), and the estimated relative GHE share of the healthcare workforce and infrastructure distributions were 46.5% and 53.5%, respectively. The marginal changes in the healthcare resources distributions were towards the advantaged populations.

CONCLUSION

This study revealed high inequalities in healthcare resources in favour of the advantaged populations which can hinder equal access to healthcare and the achievements of healthcare outcomes. The government should strengthen monitoring mechanisms to address inequalities based on the national healthcare standards.