Vol-7, Special Issue3-April, 2016, pp822-828 http://www.bipublication.com
e cl ti Ar h rc ea es R
Performance assessment of health posts affiliated with Ahvaz University of
medical sciences using data envelopment analysis technique
from 2013 to 2015
Ali Feizi1, Amin Torabipour2* and Abbas Yazdanpanah3 1
Department of health care management,
Marvdasht Branch, Islamic Azad University, Marvdasht, Iran feizi.a55@gmail.com
2
Department of health services management, school of public health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Torabi-a@ajums.ac.ir 3
Assistant professor, Department of health care management, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
Abbas_yaz@yahoo.com
ABSTRACT
Introduction: Data envelopment analysis is the most important and most common way to assess and measure the performance and efficiency of hospital and health centers. The aim of this study is performance analysis of health posts in Ahvaz University of medical sciences.
Methods: This is cross-sectional and linear programming study that was performed from 2013 to 2015. The study population included 600 health posts were affiliated with Ahvaz University of medical sciences Ahvaz University of medical sciences. Based on the visit and the number of services, 39 health posts were selected as samples. Data were analyzed using data envelopment analysis technique. In this method, technical, scale, and managerial efficiency are calculated based on input and output variables. Data were analyzed by Deap.2 software.
Results: The findings showed that average technical, managerial, and scale efficiency of health posts increased during from 2013 to 2015. Average technical efficiency of health posts was 0.92, managerial efficiency was 0.949 and the scale efficiency was 0.968. Herkeleh health post with an average scale efficiency 0.667 and Parchestan goroui with an average technical efficiency and administrative 0.597 had the lowest efficiency.
Conclusion: In this study we concluded that most health posts had good technical and scale efficiency.
Key words: Health post, Performance, Efficiency, Data envelopment analysis
INTRODUCTION
Efficient use of available resources and increase of efficiency toward responsibility to growing needs has become a very important issue in health systems performance (1,2). In the health care system, efficiency evaluation is the first step in evaluating the performance of different sectors of health such as hospitals, health centers, and etc. Therefore, we can use methods of measuring and evaluating the performance of
programming can assess technical, Scale, and managerial efficiency (4). Data envelopment analysis method is a non-parametric method that assesses a frontier production function. This method include all data and observations (1,5). DEA is one of the most common methods of efficiency measurement in the world. Alam Tabriz ( 6), Pourreza(5), Mahani (7), Safi Arian (8), Linna (9), Chang (10) Kirigia(11) used this method to assess efficiency and productivity of health care units. This method is an acceptable method because estimate complex relationship between input and output variables (12). In general, Data envelopment analysis method develops a referral efficient unit for any inefficient units. In this method, efficiency of units is determined after optimizing function factors (4). The results of Data envelopment analysis can help managers that distribute resources properly and reduce additional costs of production process (13). The aim of this study was Performance assessment of health posts affiliated with Ahvaz University of medical sciences using data envelopment analysis technique.
METHOD
This is cross-sectional and linear programming study that was performed from 2013 to 2015. The study population included 600 health posts were affiliated with Ahvaz University of medical sciences Ahvaz University of medical sciences. Based on the number of services, 39 health posts were selected as samples. Data were collected based on determined variables using valid data form. For determining suitable input
and output variables, we used Delhi method based on opinion of 30 experts in health networks. Data were analyzed using data envelopment analysis technique. In this method, technical, scale, and managerial efficiency are calculated based on input and output variables. We selected input-orientation approach and variable returns to scale (VRS) model for data analysis. In input-orientation approach, decision-making units (DMUs) can change their inputs (4, 5, 6). When the efficiency measurement is based on the input-orientation approach (minimizing the production factors), a value of one show perfect efficiency. In this study, we efficiency range was included: poor efficiency (0.5>), moderate efficiency (0.51-0.8), and good efficiency (0.81-1). Finally, Data was analyzed by SPSS.18 and DEAP.2 software.
FINDINGS
The findings of the study showed that average of technical, managerial, and Scale efficiency of health posts had an increasing trend. Averagely, technical, managerial, and Scale efficiency was good. Average of technical efficiency was 0.92, managerial efficiency was 0.949 and the Scale efficiency was 0.968. Therefore, scale efficiency had higher score than other type of efficiency indicators. The results also showed that out of 39 health posts, 16 health posts (%41) have perfect efficiency (efficiency=1). Between the health posts, Parchestan Goroui health post with an average technical and managerial 0.579 and Herkele health posts with an average of scale efficiency 0.667 had the lowest efficiency (Table 1).
Table 1. Comparison of technical, managerial, and scale efficiency of studied health posts
Health posts
Technical efficiency Managerial Efficiency
Scale efficiency
92 93
94 Average 92
93 94
Avera ge 92
93 94
Average
Sufan 1
1 1
1 1
1 1
1 1
1 1
1
New dailam 0.896
0.992 0.720
0.869 0.987
1 0.771 0.919
0.908 0.992
0.934 0.945
Mehdi abad 0.929
1 0.829
0.919 1
1 1
1 0.929 1
0.829 0.919
Kangonjeshki 1
0.812 0.822
0.878 1
0.836 0.824
0.887 1
0.972 0.997
0.990
Benshavar 1
1 1
1 1
1 1
1 1
1 1
1
Dalan 0.726
0.781 1
0.836 0.883
0.785 1
0.889 0.823
0.996 1
0.940
Ableh sofla 0.823
0.809 0.843
0.825 0.823
0.809 0.843
0.825 1
1 1
1
Dare zang 1
1 1
1 1
1 1
1 1
1 1
1
Parchestan gorouie 0.547
0.572 0.619
0.579 0.547
0.572 0.619
0.579 1
1 1
1
Kout soltan 0.723
1 0.861
0.861 0.891
1 1
0.964 0.811
Sadin 0.818 0.873 0.904 0.865 0.821 0.881 1 0.901 0.997 0.991 0.904 0.964 Eslam ababd 0.645 0.763 0.891 0.736 0.743 0.773 1 0.832 0.867 0.988 0.891 0.915 Emamzade Abdollah 0.643 0.915 0.931 0.830 0.643 0.915 0.931 0.830 1 1 1 1 Gabir2 1 1 1 1 1 1 1 1 1 1 1 1 Magtou 1 1 0.969 0.990 1 1 1 1 1 1 0.969 0.909 Morzam 1 1 1 1 1 1 1 1 1 1 1 1 Mlah 1 1 1 1 1 1 1 1 1 1 1 1 Fotour 1 1 1 1 1 1 1 1 1 1 1 1 Rostam ababd 1 1 1 1 1 1 1 1 1 1 1 1 Bneh fakhar 1 1 1 1 1 1 1 1 1 1 1 1 Sagour saleh 0.902 0.955 0.976 0.944 1 0.990 1 0.997 0.902 0.964 0.976 0.947 Omaldabs 1 1 1 1 1 1 1 1 1 1 1 1 Koie talghani 1 1 1 1 1 1 1 1 1 1 1 1 Karimabad 1 1 1 1 1 1 1 1 1 1 1 1 abnargesi 1 1 1 1 1 1 1 1 1 1 1 1 Cham enaie 0.866 0/855 1 0.907 0.866 0.855 1 0.907 1 1 1 1 Sen 0.925 1 0.840 0.922 1 1 0.920 0.973 0.925 1 0.913 0.946 Avafi 1 1 1 1 1 1 1 1 1 1 1 1 Chenar mangare 1 0.949 0.941 0.963 1 0.961 0.941 0.967 1 0.987 1 0.996 Ali abad 0.954 0.828 1 0.927 1 0.828 1 0.943 0.954 1 1 0.985 Maghtou alia 1 1 1 1 1 1 1 1 1 1 1 1 Alavanefai 1 1 1 1 1 1 1 1 1 1 1 1 Kout seied saleh 0.909 0.922 0.803 0.878 1 1 1 1 0.909 0.922 0.803 0.878 amire 1 1 1 1 1 1 1 1 1 0.894 1 0.964 Ghale changaei 0.959 0.822 0.812 0.864 0.985 0.824 0.862 0.890 0.974 0.998 0.942 0.971 Harkele 0 1 0.956 0.652 1 1 0.956 0.988 0 1 1 0.667 Paab shelal 0.799 0.718 0.719 0.745 0.825 0.773 0.748 0.782 0.968 0.929 0.960 0.952 Sar ahouney 0.867 1 1 0.956 0.901 1 1 0.967 0.962 1 1 0.987 Eslamabad 0.894 0.898 1 0.931 0.954 0.942 1 0.894 0.938 0.953 1 0.964 Mean 0.893 0.960 0.934 0.920 0.945 0.941 0.960 0.949 0.945 0.992 0.974 0.968
According to table 2, the most health posts had generally good performance (0.81-1). Also, the results showed that scale efficiency of most of health posts was higher than managerial and technical efficiency.
Table 2. Comparison of technical, managerial, and scale efficiency status of studied health posts, during 2013-2015. Efficiency Good (0.81-1) Moderate (0.51-0.8) Weak (0.5>) 92 93 94 92 93 94 92 93 94 Technical 32)%82( 36)%92( 36)%92( 6)%15( 3)%7( 3)%7( 1)%2( - - Scale 38)%98( 39)%100( 39)%100( - - - 1)%2( - - Management 36)92%( 36)%92( 36)%92( 3)%7( 3)%7( 3)%7( - - -
The results of table 3 shows status of inefficient health posts toward referral health posts in order to determine the best referral unit. Health posts with perfect efficiency are referral units. The results showed that Soufan, Avafi, and Abnargesi health posts were referral units with higher weighted score.
Table3. identification of referral centers were inefficient units and their weight
Health posts 2013 2014 2015 Health posts reference Reference to the highest weight Weight Health posts reference Reference to the highest weight Weight Health posts reference Reference to the highest weight Weight Sufan 1 1 1 1 1 1 1 1 1 New dailam 1 20 28
1 0.684
1 1
abad Kangonjes hki 4 1 1
28 22 25 20 14 1 20
0.370 5 39 25 23
18 14 25 0.387 Benshavar 5 1 1 5 1 1 5 1 1 Dalan 1 21 32
28 28
0.654 32 27 28
27 0.542 6 1 1 Ableh sofla 18 1 28
25 8 28
0.595 1 25 28 18
22 25
0.618 5 18 25
25 0.685 Dare zang 8 1 1 8 1 1 8 1 1 Parchestan gorouie 25 8 18
8 0.493
8 1 24 18 1
0.436 5 25 18
18 0.671
Kout soltan 28 19 32
23 3 19 0.388 10 1 1 10 1 1 sadin 28 31 24
24 0.456
36 28 27 27 0.467 11 1 1 Eslam ababd 28 19 32
18 19
0.587 28 27 16
32 28 0.455 12 1 1 Emamzade abdollah 1 25 8 18
4 8
0.356 23 1 25
14 14
0.600 14 25 18 5
39 25 0.370 Gabir2 14 1 1 14 1 1 14 1 1 magtou 15 1 1 15 1 1 15 1 1 Morzam 16 1 1 16 1 1 16 1 1 Mlah 17 1 1 17 1 1 17 1 1 Fotour 18 1 1 18 1 1 18 1 1 Rostam ababd 19 1 1 19 1 1 19 1 1 Bneh fakhar 20 1 1 20 1 1 20 1 1 Sagour saleh 21 1 1
32 20 23 28 14 14 0.574 21 1 1 Omaldabs 22 1 1 22 1 1 22 1 1 Koie talghani 23 1 1 23 1 1 23 1 1 Karimabad 24 1 1 24 1 1 24 1 1 Abnargesi 25 1 1 25 1 1 25 1 1 Cham enaie 25 1 28 8
24 1
0.377 1 24 25 22
25 0.595 26 1 1 Sen 27 1 1 27 1 1 34 18 21 10 34 0.587 Avafi 28 1 1 28 1 1 8 18
8 0.768 Chenar mangare 29 1 1
1 20 22 23 14 25 25
0.809 5 25 18 19
25 0.834 Ali abad 30 1 1
1 25 19 20 1 0.433 30 1 1 Maghtou alia 31 1 1 31 1 1 31 1 1 alavanefai 32 1 1 32 1 1 32 1 1 Kout seied saleh 33 1 1 33 1 1 33 1 1 amire 34 1 1 34 1 1 34 1 1 Ghale changaei 1 25 27 28
27 0.683
20 22 25 28 25
0.637 18 34 8 26
26 0.533 harkele 36 1 1 36 1 1 25 14 18
25 0.656
Paab shelal 25 4 18 31
36 25
0.543 1 25 22
25 0.547
34 25 8 1 18 25
0.497
Sar ahouney
36 4 28 22 14 28 0.489 38 1 1 38 1 1 Eslamabad
23 4 4
0.907 23 3 5
23 0.574 39 1 1 DISCUSSION:
In this study, performance assessment of health posts affiliated with Ahvaz university of medical sciences was performed using the Data envelopment analysis technique. Data envelopment analysis is one of the most common methods of Performance assessment
in the field of healthcare networks, Limited studies have been done (9,11,17). The findings of the study showed The average Efficiency Technical, managerial and Scale Health posts 92 to 94 has increased during the study. On average, Efficiency Technical, good management and Scale Health posts (more than 1) assessment was. Average Efficiency Technical Health posts 0.92, Management Efficiency 0.949 And the Scale efficiency 0.968.So Scale efficiency are rated higher than managerial and technical efficiency and. Average score shows efficiency Technical The Health posts about study Efficiency is necessary to reach the main border That someday your input to about 8 percent. In this Average Efficiency Health centers 0.057 were reported (22). Another study in Kenya showed that 18 percent of health centers A Technical inefficiency And %47 were non-Scale efficiency (23). The results showed that Health posts in the study of Efficiency Technical, Management and mostly in good Scale (1 -0.81), respectively. In this regard Farahabadi et al. During the study showed health care centers the average Efficiency Technical, Management, Scale In the studied hospitals, respectively, 0.087, 0.091, and 0.095 respectively which corresponded with the results. Also, this study showed that in 2013, 43.5 percent, 2014 and 2015 53.8 percent of health posts had efficient perfectly. And other Health posts Efficiency was a relative. The study showed brave et al. That the Health posts the study only 7.27 of Health posts were efficient assessment And the rest has had some degree of non-Efficiency (24). In this regard, the study also showed that Kazyly in Ghana Only %35 of the studied hospitals were efficient And 65 percent were deficient assessment. In between shopping centers have inefficient Efficiency% 24 were less than 50 percent (22).The results of this study with the results of the present study is slightly different. These differences may be due to several factors Such as type of service, How is resource allocation and calculation errors. To Increase Efficiency Technical health centers Can be input surplus Scale according to the optimal level of
efficiency to be increased or decreased (4). It also constant with increasing output and input or stabilizing output and reduce inputs Efficiency can be increased health centers (25). In this study, some such centers Sofan, ab Nargesi and Avafi reference as Health posts with the highest frequency were determined. Use of data envelopment analysis Centers can be inefficient, Reference Center determined. Reference centers a model for Performance improvement centers (4, 25). Studies on the health assessment Efficiency and Performance Unit and Money Can determine the proper input and output sources Efficiency kinds of Technical, , Management and Scale of In the ranking of health care systems administrators to help.
CONCLUSION:
In this study, we conclude The most studied Health posts The Efficiency Technical, Scale management and were in good condition As well as the Efficiency Technical Scale efficiency And top management's assessment. The results showed that Health posts sofan, avafi and abnargesi with the highest weight As the unit of reference Health posts were set for benchmarking other.
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