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Measuring inequalities in the distribution of health workers: the case of Tanzania.

Munga MA, Maestad O - Hum Resour Health (2009)

Bottom Line: There are significant inequalities in the distribution of health workers per capita.The measure of inequality in the distribution of the health workforce may depend strongly on the underlying measure of health care needs.In cases of a non-uniform distribution of health care needs across geographical areas, other measures of health care needs than population levels may have to be developed in order to ensure a more meaningful measurement of distributional inequalities of the health workforce.

View Article: PubMed Central - HTML - PubMed

Affiliation: National Institute for Medical Research, Dar es Salaam, Tanzania. michaelmunga@yahoo.com

ABSTRACT

Background: The overall human resource shortages and the distributional inequalities in the health workforce in many developing countries are well acknowledged. However, little has been done to measure the degree of inequality systematically. Moreover, few attempts have been made to analyse the implications of using alternative measures of health care needs in the measurement of health workforce distributional inequalities. Most studies have implicitly relied on population levels as the only criterion for measuring health care needs. This paper attempts to achieve two objectives. First, it describes and measures health worker distributional inequalities in Tanzania on a per capita basis; second, it suggests and applies additional health care needs indicators in the measurement of distributional inequalities.

Methods: We plotted Lorenz and concentration curves to illustrate graphically the distribution of the total health workforce and the cadre-specific (skill mix) distributions. Alternative indicators of health care needs were illustrated by concentration curves. Inequalities were measured by calculating Gini and concentration indices.

Results: There are significant inequalities in the distribution of health workers per capita. Overall, the population quintile with the fewest health workers per capita accounts for only 8% of all health workers, while the quintile with the most health workers accounts for 46%. Inequality is perceptible across both urban and rural districts. Skill mix inequalities are also large. Districts with a small share of the health workforce (relative to their population levels have an even smaller share of highly trained medical personnel. A small share of highly trained personnel is compensated by a larger share of clinical officers (a middle-level cadre) but not by a larger share of untrained health workers. Clinical officers are relatively equally distributed. Distributional inequalities tend to be more pronounced when under-five deaths are used as an indicator of health care needs. Conversely, if health care needs are measured by HIV prevalence, the distributional inequalities appear to decline.

Conclusion: The measure of inequality in the distribution of the health workforce may depend strongly on the underlying measure of health care needs. In cases of a non-uniform distribution of health care needs across geographical areas, other measures of health care needs than population levels may have to be developed in order to ensure a more meaningful measurement of distributional inequalities of the health workforce.

No MeSH data available.


Cumulative share of total health workers and U5 deaths across districts.
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Figure 4: Cumulative share of total health workers and U5 deaths across districts.

Mentions: One alternative to population levels as a measure of need is the number of under-five deaths. In Fig. 4, the concentration curve for the cumulative share of under-five deaths is shown together with the Lorenz curve for the cumulative share of all health workers. The concentration curve for under-five deaths lies everywhere above the diagonal, showing that those districts that have few health workers per capita at the same time have a large share of under-five deaths per capita (the concentration index is -0.26 for all districts, -0.29 for urban districts and -0.22 for rural districts, respectively). In other words, the need for health services – measured as the number of under-five deaths – in districts with few health workers is larger than suggested by their respective population levels.


Measuring inequalities in the distribution of health workers: the case of Tanzania.

Munga MA, Maestad O - Hum Resour Health (2009)

Cumulative share of total health workers and U5 deaths across districts.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2655278&req=5

Figure 4: Cumulative share of total health workers and U5 deaths across districts.
Mentions: One alternative to population levels as a measure of need is the number of under-five deaths. In Fig. 4, the concentration curve for the cumulative share of under-five deaths is shown together with the Lorenz curve for the cumulative share of all health workers. The concentration curve for under-five deaths lies everywhere above the diagonal, showing that those districts that have few health workers per capita at the same time have a large share of under-five deaths per capita (the concentration index is -0.26 for all districts, -0.29 for urban districts and -0.22 for rural districts, respectively). In other words, the need for health services – measured as the number of under-five deaths – in districts with few health workers is larger than suggested by their respective population levels.

Bottom Line: There are significant inequalities in the distribution of health workers per capita.The measure of inequality in the distribution of the health workforce may depend strongly on the underlying measure of health care needs.In cases of a non-uniform distribution of health care needs across geographical areas, other measures of health care needs than population levels may have to be developed in order to ensure a more meaningful measurement of distributional inequalities of the health workforce.

View Article: PubMed Central - HTML - PubMed

Affiliation: National Institute for Medical Research, Dar es Salaam, Tanzania. michaelmunga@yahoo.com

ABSTRACT

Background: The overall human resource shortages and the distributional inequalities in the health workforce in many developing countries are well acknowledged. However, little has been done to measure the degree of inequality systematically. Moreover, few attempts have been made to analyse the implications of using alternative measures of health care needs in the measurement of health workforce distributional inequalities. Most studies have implicitly relied on population levels as the only criterion for measuring health care needs. This paper attempts to achieve two objectives. First, it describes and measures health worker distributional inequalities in Tanzania on a per capita basis; second, it suggests and applies additional health care needs indicators in the measurement of distributional inequalities.

Methods: We plotted Lorenz and concentration curves to illustrate graphically the distribution of the total health workforce and the cadre-specific (skill mix) distributions. Alternative indicators of health care needs were illustrated by concentration curves. Inequalities were measured by calculating Gini and concentration indices.

Results: There are significant inequalities in the distribution of health workers per capita. Overall, the population quintile with the fewest health workers per capita accounts for only 8% of all health workers, while the quintile with the most health workers accounts for 46%. Inequality is perceptible across both urban and rural districts. Skill mix inequalities are also large. Districts with a small share of the health workforce (relative to their population levels have an even smaller share of highly trained medical personnel. A small share of highly trained personnel is compensated by a larger share of clinical officers (a middle-level cadre) but not by a larger share of untrained health workers. Clinical officers are relatively equally distributed. Distributional inequalities tend to be more pronounced when under-five deaths are used as an indicator of health care needs. Conversely, if health care needs are measured by HIV prevalence, the distributional inequalities appear to decline.

Conclusion: The measure of inequality in the distribution of the health workforce may depend strongly on the underlying measure of health care needs. In cases of a non-uniform distribution of health care needs across geographical areas, other measures of health care needs than population levels may have to be developed in order to ensure a more meaningful measurement of distributional inequalities of the health workforce.

No MeSH data available.