Journal of Education and Health Promotion

Abstract BACKGROUND: Given that the need to pay attention to measuring efficiency is considered as
one of the main pillars of improving the level of efficiency in hospitals, so this study was carried
out aimed to determine the mean technical efficiency (The technical efficiency is bound by zero
and one and a score of less than one means that the theatre is inefficient as it could) score in
terms of type and activity of the hospital, input‑oriented and output‑oriented attitude, returns to
scale (In economics, returns to scale and economies of scale are related but different concepts
that describe what happens as the scale of production increases in the long run, when all input
levels including physical capital usage are variable (chosen by the firm). The concept of returns
to scale arises in the context of a firm’s production function. It explains the behavior of the rate
of increase) in hospitals of Iran using data envelopment analysis (DEA) (DEA is a nonparametric
method in operations’ research and economics for the estimation of production frontiers. It is
used to empirically measure productive efficiency of decision‑making units) and stochastic frontier
analysis (SFA) (SFA is a method of economic modeling. It has its starting point in the stochastic
production frontier models simultaneously introduced by Aigner, Lovell and Schmidt[1977] and
Meeusen and Van den Broeck[1977]
MATERIALS AND METHODS: The present study was carried out with a systematic review
of all studies conducted on measuring efficiency of hospitals in Iran from March 21, 2001 to
December 21, 2017 using DEA and SFA. Eleven databases were searched using appropriate
keywords and 470 articles were found and evaluated using a checklist, and finally, 24 articles
were entered into the meta‑analysis process. Meta‑analysis was performed using random effect
model and fixed‑effect model, and study heterogeneity was investigated using Q‑Cochran
test and I
2 index. Furthermore, the main reasons of study heterogeneity were identified due
to meta‑regression.
RESULTS: The average technical efficiency score of hospitals using DEA and SFA method
was obtained equal to 0.885 and 0.809, respectively. Furthermore, with regard to the DEA
method, 0.885, 0.891.0.952 and 0.913 was obtained for input‑oriented and output‑oriented,
general and specialized care hospitals and constant returns respectively. With regard to SFA
method, 0.733, 0.664, 0.641, 0.802, was obtained, and the inputs and outputs affect measuring
the efficiency.
DISCUSSION: In contrast, the DEA method can investigate several input and output simultaneously
and is used as an effective and flexible tool in order to measure the efficiency of the hospital. DEA
can be easily used for calculating efficiency scores based on the proper selection of input and
output indicators. The data envelopment analysis method and different input and output variables
have been used in most studies conducted in Iran, and Stochastic Frontier Analysis has been less
considered. In the present study, the DEA method in governmental educational hospitals showed a
higher efficiency than SFA method in the hospitals under study. But in general, due to lack of optimal
efficiency level in the hospital, it is suggested that policymakers determine the hospital efficiency
indices in order to evaluate their efficiency from different dimensions.  CONCLUSION: The average technical efficiency score of hospitals using DEA and SFA method was obtained equal to 0.885
and 0.809, respectively. Also, the mean technical efficiency score in terms of input-oriented and output-oriented, general and
specialized care hospitals and constant returns to scale using the DEA method was obtained equal to 0.885, 0.891.0.952 and
0.913 and using the SFA method, respectively, it was equal to 0.733, 0.664, 0.641, 0.802, and the inputs and outputs affecting
measuring the efficiency. There is no significant difference between the mean efficiency score between the two methods, but
the data envelopment analysis method is used more. It is suggested that the hospitals efficiency indicators to be determined in
order to more accurately evaluate the hospitals efficiency.

Abstract INTRODUCTION: A sharp increase in expenditure is one of the challenges of the health system
in Iran. Every macroeconomic variable affects health, and if it is disregarded, it will lead to higher
macrobudgets. Physical and mental health as well as the use of health services change according
to the macroeconomic conditions and business cycles (boom and recession). The present study
aimed to determine the effect of macroeconomic indicators on health expenditure.
METHODS: This study was descriptive analytical. The required data related to macroeconomic
indicators and health expenditure in public and private sectors were collected during 1995–2014.
The data were analyzed using the time series models in econometrics, Vector Auto Regression,
and Granger causality technique.
RESULTS: The results of this study indicated that health expenditure has a positive bilateral
relationship with gross domestic production (GDP), gross national production, national income,
and national consumption. On the contrary, expenditure has a negative bilateral relationship with
liquidity rate and inflation rate. In addition, budget deficit has a negative unilateral relationship with
health expenditure while population rate has a positive unilateral relationship with health expenditure.
CONCLUSION: The results of this study indicated the increase of health expenditure in Iran that
GDP is the most critical determining factor of health expenditure. In general, the total expenditure in
the health sector in the world increases when the countries become richer. In line with the increase
of resources, innovative financing methods and efficiency improvement are required for providing
basic health services in low‑income countries.