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Open in a separate window Discussion We measured total hospital productivity using malemquist index.
Malemquist index is a useful technique to assess hospital productivity The results showed that the productivity of hospitals over the years has increased and had an ascending trend. However, the average of total productivity was 1. Different values for total factors productivity have been reported in different researches in Iran and other countries.
One way to increase technical efficiency is decrease of length of stay and increase of hospital size. Masayuki 21 showed that the larger hospitals have the higher productivity. Of course, length of stay effects should be controlled simultaneously.
It should be noted Productivity change is affected scale efficiency changes, technological performance and managerial performance 13 Evaluation of the causes of these effects can be helpful in improvement of the total productivity.
The lack of technological innovation in hospitals led to a decrease in TFP change. Technological improvements play an important role in increasing the productivity of larger hospitals Findings of our study showed that despite improvement in productivity trend of hospitals, the average of productivity of hospitals not improved; this result can be used as a warning in order to make better use of existing resources.
In hospitals that the main cause of low productivity is changes in technology efficiency, it seems that lack of enough familiarity of managers with the advanced hospital technologies, lack of equipment and inappropriate use of technology in diagnosis, care and treatment, are the main causes Limitations of current study were first, databases are not well developed in hospitals.
Second, medical record system is manual and third, DEA software has technical limitations. Conclusions In the F and K hospitals the main cause of the low productivity is changes in technical efficiency therefore mangers must use inputs doctors, nurses and beds efficiently and increase the outputs.
In hospitals E that the main cause of low productivity is negative changes of scale efficiency therefore managers must improve the scale efficiency. Finally, according to results of this study, decrease of technological efficiency had the highest negative impact on average of total productivity of hospitals.
Therefore, hospital Managers and policy makers can use economic of scale methods including: Acknowledgments The authors would like to appreciate the Research and Technology Deputy of Ahvaz Jundishapur University of Medical Sciences and School of Rehabilitation Sciences for their financial and administrative support to undertake this project.
The authors declare that there is no conflict of interests. Am J Applied Sci, 9 3: Efficiency measurement in developing countries: Application of data envelopment analysis for Iranian hospitals.
Health Services Manage Res, Frontier-based techniques in measuring hospital efficiency in Iran: A conceptual framework for selecting the most appropriate variables for measuring hospital efficiency with a focus on Iranian public hospitals.
Health Serv Manage Res, Measuring hospital efficiency with data envelopment analysis: Substitutable Inputs and Outputs.
J Med Sys, Journal of Health Administration, 12 Advantages of Data Envelopment Analysis 1. It has the capability of handling multiple inputs and outputs 2. Inputs and outputs can have different units of measure.
3. It is a non parametric method which does not need a functional form for computing efficiency 4. It can calculate the sources and the extent of inefficiency in inputs and outputs 5.
data envelopment analysis phd thesis DATA ENVELOPMENT ANALYSIS FOR MEASURING THE EFFICIENCY OF HEAD TRAUMA CARE IN ENGLAND AND WALES by Afaf Nafea Alrashidi This thesis is submitted in partial fulfilment III Data Envelopment Analysis and Performance Measurement Proceedings of the 11th International Conference of DEA, June , Samsun, Turkey EDITED .
Master’s degree thesis LOG Logistics Application of Data Envelopment Analysis and Malmquist Productivity Index in the Norwegian. Introduction to Data Envelopment Analysis Data Envelopment Analysis is a Performance Measurement technique which is used for comparing the performances of similar units of an organization.
The units for which we are doing the performance analysis are called Decision Making Units (DMU). Doctoral Thesis University of Trento CIFREM Interdepartmental Centre for Research Training in Economics and Management Doctoral School in Economics and Management.
This is a tutorial on Data Envelopment Analysis (*) 1 – Abstract Data envelopment analysis (DEA) is a linear programming based technique for measuring the relative performance of organisational units where the presence of multiple inputs and outputs makes comparisons difficult.