Introduction: Because of organizations must to have a clear perspective of continuing profitability to be accepted in the capital market, researchers survey efficiency evaluation of the Iranian Public Hospital, so that select qualified hospitals for admission to the capital market by separating efficient and inefficient hospitals
Methods: It is a descriptive, analytical and retrospective study. Data envelopment analysis technique, CCR model and BCC input-axis, were used to measure efficiency. Data includes input and output of public hospital operations, as the inputs include the number of active beds, the number of physician personnel, the number of non-medical personnel and output include the number of hospital admission, the number of outpatient admissions and the bed occupancy rate. The statistical population consisted of 592 public hospitals. According to available data, 558 hospitals were selected. The DEA Solver Pro and SPSS software were used.
Results: In the CCR model, 123 hospitals were efficient (22%), and in BBC model, 183 Hospitals (33%). The average efficiency of hospitals in the CCR model were 0.66 and in the BCC model were 0.75.
Conclusions: According to the data envelopment analysis model (input-axis) inefficient hospital can achieve efficient unit by changing their inputs. But it seems to make sustainable changes, Macro policies and strategies in the health sector should be changed, which can include the autonomy of hospitals, the integration of efficient and inefficient hospitals, Or the formation of hospital cooperation and accept in the capital market.

Introduction:  Hospitals, as one of the main organizations providing health services, have a special sensitivity and importance in the economy and health. Full attention to the efficiency of the hospital as the largest and most costly operational unit of the health system is of particular importance, so the evaluation of hospitals is one of the most important issues for health policy makers.
Methods: Data Envelopment Analysis (DEA) is a method for evaluating the efficiency and productivity of decision units. If a network is composed of interdependent steps to generate outputs. Therefore, in this study, we have evaluated the relative efficiency of hospitals with output weight constraints for those outputs that have non-linear values. Equivalently, in the cover form, the give-and-take principle is used to take into account the output constraints. In this way, an ascending weight sequence is considered for larger output values of nonlinear value. This study is examined in a secret network. In this study, using the network data envelopment analysis approach, a system performance evaluation model has been designed that considers the relationship between weights as a reliable area in the evaluation.
Results: In this article, the efficiency of 10 hospitals is examined with a new approach, of which only the fourth hospital has obtained an efficiency score of 1. An important feature is the change in the type of classification of efficient and inefficient units in the findings. The results showed that the proposed method is more accurate because by considering nonlinear pricing, it reduces the error that results from linear pricing in evaluations.
Conclusion: The resulting efficient and inefficient units are different from the previous classical methods, so different policies for the units must be considered by managers.