Effects of maternal mortality on gross domestic product (GDP) in the WHO African region.

WHO African region has got the highest maternal mortality rate compared to the other five regions. Maternal mortality is hypothesized to have significantly negative effect on the gross domestic product (GDP). The objective of the current study was to estimate the loss in GDP attributable to maternal mortality in the WHO African Region. The burden of maternal mortality on GDP was estimated using a double-log econometric model. The analysis is based on cross-sectional data for 45 of the 46 Member States in the WHO African Region. Data were obtained from UNDP and the World Bank publications. All the explanatory variables included in the double-log model were found to have statistically significant effect on per capita gross domestic product (GDP) at 5 % level in a t-distribution test. The coefficients for land (D), capital (K), educational enrollment (EN) and exports (X) had a positive sign; while labor (L), imports (M) and maternal mortality rate (MMR) were found to impact negatively on GDP. Maternal mortality of a single person was found to reduce per capita GDP by US $ 0.36 per year. The study has demonstrated that maternal mortality has a statistically significant negative effect on GDP. Thus, as policy-makers strive to increase GDP through land reform programs, capital investments, export promotion and increase in educational enrollment, they should always remember that investment in maternal mortality-reducing interventions promises significant economic returns.

Technical efficiency of public district hospitals and health centres in Ghana: a pilot study.

BACKGROUND: The Government of Ghana has been implementing various health sector reforms (e.g. user fees in public health facilities, decentralization, sector-wide approaches to donor coordination) in a bid to improve efficiency in health care. However, to date, except for the pilot study reported in this paper, no attempt has been made to make an estimate of the efficiency of hospitals and/or health centres in Ghana. The objectives of this study, based on data collected in 2000, were: (i) to estimate the relative technical efficiency (TE) and scale efficiency (SE) of a sample of public hospitals and health centres in Ghana; and (ii) to demonstrate policy implications for health sector policy-makers. METHODS: The Data Envelopment Analysis (DEA) approach was used to estimate the efficiency of 17 district hospitals and 17 health centres. This was an exploratory study. RESULTS: Eight (47%) hospitals were technically inefficient, with an average TE score of 61% and a standard deviation (STD) of 12%. Ten (59%) hospitals were scale inefficient, manifesting an average SE of 81% (STD = 25%). Out of the 17 health centres, 3 (18%) were technically inefficient, with a mean TE score of 49% (STD = 27%). Eight health centres (47%) were scale inefficient, with an average SE score of 84% (STD = 16%). CONCLUSION: This pilot study demonstrated to policy-makers the versatility of DEA in measuring inefficiencies among individual facilities and inputs. There is a need for the Planning and Budgeting Unit of the Ghana Health Services to continually monitor the productivity growth, allocative efficiency and technical efficiency of all its health facilities (hospitals and health centres) in the course of the implementation of health sector reforms.