Cost Effectiveness and Resource Allocation (Mar 2006)
Technical efficiency of district hospitals: Evidence from Namibia using Data Envelopment Analysis
Abstract
Abstract Background In most countries of the sub-Saharan Africa, health care needs have been increasing due to emerging and re-emerging health problems. However, the supply of health care resources to address the problems has been continuously declining, thus jeopardizing the progress towards achieving the health-related Millennium Development Goals. Namibia is no exception to this. It is therefore necessary to quantify the level of technical inefficiency in the countries so as to alert policy makers of the potential resource gains to the health system if the hospitals that absorb a lion's share of the available resources are technically efficient. Method All public sector hospitals (N = 30) were included in the study. Hospital capacity utilization ratios and the data envelopment analysis (DEA) technique were used to assess technical efficiency. The DEA model used three inputs and two outputs. Data for four financial years (1997/98 to 2000/2001) was used for the analysis. To test for the robustness of the DEA technical efficiency scores the Jackknife analysis was used. Results The findings suggest the presence of substantial degree of pure technical and scale inefficiency. The average technical efficiency level during the given period was less than 75%. Less than half of the hospitals included in the study were located on the technically efficient frontier. Increasing returns to scale is observed to be the predominant form of scale inefficiency. Conclusion It is concluded that the existing level of pure technical and scale inefficiency of the district hospitals is considerably high and may negatively affect the government's initiatives to improve access to quality health care and scaling up of interventions that are necessary to achieve the health-related Millennium Development Goals. It is recommended that the inefficient hospitals learn from their efficient peers identified by the DEA model so as to improve the overall performance of the health system.