Abstract

Health sector reforms are always linked to financial restraints. The relative low spending on healthcare by the majority of developing countries makes it even more crucial to plan the deployment of health services optimally. Many countries in the world have taken recourse to analyzing efficiency of the decision making units (DMU) in terms of inputs and outputs. A study from Ghana using this approach found 65% of the sampled health centres (HC) to be deficient in terms of services delivered in maternal and child health domains based on inputs such as number of staff, number of beds and the financial outlay. 1 The method used was Data Envelopment Analysis (DEA) which gave a relative measure of efficiency. DEA estimates how well a DMU is functioning compared to its peers. It is constructed non-parametrically using linear programming techniques and can analyze several outputs simultaneously. The technical efficiency (TE) of a DMU refers to the ability to minimize the use of inputs in reaching the given outputs or the ability to obtain the maximum output from a given set of inputs. A constant return to scale (CRS) model is applicable when all the DMUs are functioning at an optimal scale. On the other hand, a variable return to scale (VRS) model can be employed as an extension to CRS model so as not to be affected by the scale efficiency. 2 The model used in the paper from Ghana was input-oriented and instead of going for a constant return to scale (CRS) model, the study used a variable return to scale (VRS) model. The scale efficiency was derived by finding the ratio of CRS efficiency score to VRS efficiency score. Pure technical efficiency and scale efficiency was proposed as an aid to find the potential of increasing the total outputs for the existing capacity/size of the DMU. The study concluded that the centres (DMU/HC) were using more inputs than needed to produce the current outputs. Hence a cost minimization objective was put forth which aimed at input savings. In the year 2000, a DEA approach was applied to 20 hospitals in Oman. 3 Four outputs representing out-patient visits, in-patient

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