Using data envelopment analysis to measure the extent of technical efficiency of public health centres in Ghana

<p>Abstract</p> <p>Background</p> <p>Data Envelopment Analysis (DEA) has been used to analyze the efficiency of the health sector in the developed world for sometime now. However, in developing economies and particularly in Africa only a few studies have applied DEA in measuring the efficiency of their health care systems.</p> <p>Methods</p> <p>This study uses the DEA method, to calculate the technical efficiency of 89 randomly sampled health centers in Ghana. The aim was to determine the degree of efficiency of health centers and recommend performance targets for the inefficient facilities.</p> <p>Results</p> <p>The findings showed that 65% of health centers were technically inefficient and so were using resources that they did not actually need.</p> <p>Conclusion</p> <p>The results broadly point to grave inefficiency in the health care delivery system of public health centers and that significant amounts of resources could be saved if measures were put in place to curb the waste.</p

Technical efficiency of peripheral health units in Pujehun district of Sierra Leone: a DEA application

BACKGROUND: The Data Envelopment Analysis (DEA) method has been fruitfully used in many countries in Asia, Europe and North America to shed light on the efficiency of health facilities and programmes. There is, however, a dearth of such studies in countries in sub-Saharan Africa. Since hospitals and health centres are important instruments in the efforts to scale up pro-poor cost-effective interventions aimed at achieving the United Nations Millennium Development Goals, decision-makers need to ensure that these health facilities provide efficient services. The objective of this study was to measure the technical efficiency (TE) and scale efficiency (SE) of a sample of public peripheral health units (PHUs) in Sierra Leone. METHODS: This study applied the Data Envelopment Analysis approach to investigate the TE and SE among a sample of 37 PHUs in Sierra Leone. RESULTS: Twenty-two (59%) of the 37 health units analysed were found to be technically inefficient, with an average score of 63% (standard deviation = 18%). On the other hand, 24 (65%) health units were found to be scale inefficient, with an average scale efficiency score of 72% (standard deviation = 17%). CONCLUSION: It is concluded that with the existing high levels of pure technical and scale inefficiency, scaling up of interventions to achieve both global and regional targets such as the MDG and Abuja health targets becomes far-fetched. In a country with per capita expenditure on health of about US$7, and with only 30% of its population having access to health services, it is demonstrated that efficiency savings can significantly augment the government's initiatives to cater for the unmet health care needs of the population. Therefore, we strongly recommend that Sierra Leone and all other countries in the Region should institutionalise health facility efficiency monitoring at the Ministry of Health headquarter (MoH/HQ) and at each health district headquarter

Relationship between household wealth inequality and chronic childhood under-nutrition in Bangladesh

BACKGROUND: Household food insecurity and under-nutrition remain critically important in developing countries struggling to emerge from the scourge of poverty, where historically, improvements in economic conditions have benefited only certain privileged groups, causing growing inequality in health and healthcare among the population. METHODS: Utilizing information from 5,977 children aged 0-59 months included in the 2004 Bangladesh Demographic and Health Survey , this study examined the relationship between household wealth inequality and chronic childhood under-nutrition. A child is defined as being chronically undernourished or whose growth rate is adversely stunted, if his or her z-score of height-for-age is more than two standard deviations below the median of international reference. Household wealth status is measured by an established index based on household ownership of durable assets. This study utilized multivariate logistic regressions to estimate the effect of household wealth status on adverse childhood growth rate. RESULTS: The results indicate that children in the poorest 20% of households are more than three time as likely to suffer from adverse growth rate stunting as children from the wealthiest 20% of households (OR=3.6; 95% CI: 3.0, 4.3). The effect of household wealth status remain significantly large when the analysis was adjusted for a child's multiple birth status, age, gender, antenatal care, delivery assistance, birth order, and duration that the child was breastfed; mother's age at childbirth, nutritional status, education; household access to safe drinking water, arsenic in drinking water, access to a hygienic toilet facility, cooking fuel cleanliness, residence, and geographic location (OR=2.4; 95% CI: 1.8, 3.2). CONCLUSION: This study concludes that household wealth inequality is strongly associated with childhood adverse growth rate stunting. Reducing poverty and making services more available and accessible to the poor are essential to improving overall childhood health and nutritional status in Bangladesh

Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

Islam MM, Alam M, Tariquzaman M, et al. Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model. BMC Public Health. 2013;13(1): 11.BACKGROUND: Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. METHODS: The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. RESULTS: The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother's education, father's education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. CONCLUSIONS: Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh