The objective of this paper is to benchmark the performance of twelve publicly owned managed care organizations against one another for the period 2009 to 2011. In this paper, we use data envelopment analysis, an operations research technique, to benchmark the performance of twelve publicly managed care organizations. Data envelopment analysis clearly brings out the organizations that are opera...

Very little of WHO's work is done by the Organization alone. Much of it takes the form of coordination and collaboration in which WHO acts in partnership with governments, institutions-both governmental and nongovernmental-and individual scientists and other workers in the field of health. As the following article shows, collaboration with a university hospital department enriches both partners...

Data Envelopment Analysis (DEA) is a nonparametric approach for measuring the relative efficiency of a decision making units consists of multiple inputs and outputs. In all standard DEA models semi positive real valued measures are assumed, while in some real cases inputs and outputs may take complex valued. The question is related to measuring efficiency in such cases. As far as we are aware, ...

Control charts are the most important tools of statistical process control used to discriminate between assignable and common causes of variation and to improve the quality of a process. To design a control chart, three parameters including sample size, sampling interval, and control limits should be determined. The objectives are hourly expected cost, in-control average run length, power of th...

this paper introduces discretionary imprecise data in data envelopment analysis (dea) and discusses the efficiency evaluation of decision making units (dmus) with non-discretionary imprecise data. then, suggests a method for evaluation the efficiency of dmus with non-discretionary imprecise data. when some inputs and outputs are imprecise and non-discretionary, the dea model becomes non-linear ...

Conventional data envelopment analysis (DEA) models assume real-valued inputs and outputs. In many occasions, some inputs and/ or outputs can only take integer values. In some cases, rounding the DEA solution to the nearest whole number can lead to misleading efficiency assessments and performance targets. This paper develops the axiomatic foundation for DEA in the case of integer-valued data, ...