Hori Hadipour, Mohammad Kavoosi-Kalashami, Arsalan Salari, Mohammad Karim Motamed
Hori Hadipour, Mohammad Kavoosi-Kalashami*, Arsalan Salari, Mohammad Karim Motamed
Department of Rural Development, University of Guilan, Iran
The capital input scarcity and their late returns in health system together with other factors such as high cost of constructing new centers, expensive equipment, inadequate expert workforce and consequently slow development of healthcare facilities have always encouraged policy makers and decision-makers of health sector to make optimum use of resources and adopt proper management policies. To ensure the provision of the best and high quality, healthcare services require evaluation of health sector, as efficiency assessment is the first step in performance evaluation. Health education has been one of the most important and inspiring roles of rural healthcare centers and health workers. To evaluate the performance and efficiency of rural healthcare centers in Langarud County is the main objective of this study which can help to improve the efficiency of rural healthcare centers, and also help to make proper plans and strategies to reach those goals and develop such centers. There were 970 active rural healthcare centers in Guilan provinces in 2015, out of which 45 centers were in Langarud County. In this study, we have used CCR model to evaluate their technical efficiency, the results showed that 9 out of 45 rural healthcare centers with the efficiency score of 1, are efficient. Then using AP-CCR model, the units were ranked based on their efficiency. The rural healthcare centers in Garsak, Kuro-rudkhaneh and Malat got the best efficiency scores, respectively.
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Technical efficiency, Decision making units, Inputs, Outputs, Health services
Efficiency is a concept that increases to enhance the quality of life, well-being, comfort and peace of mankind. These goals have always been the focus of attention of those involved in politics and economics. Due to its relation with the allocation and use of inputs, the efficiency has currently been very important.[1] Efficiency means that an organization properly uses its resources to produce the best performance at some point in time, so the efficiency is a measure of the performance in an organizational system. In other words, the efficiency is the use of resources to produce a certain amount of product.[2] Rural healthcare centers (in Iran known as Health Houses) are the most convenient and accessible health centers in rural areas. Each rural healthcare center, considering the geographical conditions, particularly communication facilities and the population, covers one or more villages. The staff trained to provide health service in these healthcare centers are known as health workers. Some tasks performed by rural healthcare centers include: conducting annual census and documentation of vital events such as deaths and births, community participation in health activities, parenatal and child care, health and nutrition education, taking care of students and school health, dental health, monitoring the standards of occupational hygiene, public sanitation, screening, basic treatments and their follow-ups.[3]
Health has always been among the basic human needs.[4] Provision of health services for all people has been one of the goals of development plans in the Islamic Republic of Iran. For instance, article 29 of the Iranian Constitution noted the essential role of public and perfect health as the basic human needs and required the government to mobilize all of its resources, facilities and capacities to provide, maintain and promote the health of the people in the country.[5] The third development plan (2000-2005) stressed that government should take measures to enhance efficiency and develop health services in the country, facilitate public access to health services, develop rural health centers in areas where no investment is made by private sector to provide health services for rural people. The fourth development plan (2005-2009) emphasized on improving health and quality of life and protecting the environment for sustainable development through provision of equitable health services to the public and fair participation in financing the health sector.6 Clearly, to fulfil this goal, it is essential to have proper facilities. As maintaining and improving the public health is among the country's priorities for development, those involved in the health sector are trying to take advantage of the resources at their disposal, and provide the best quality health services to the community.[7]
In recent decades, the high cost of medical services resulting from development of medical technology, and the heavy burden of such costs on most governments, have made policy makers admit that health is not just a social issue, and it should also be viewed from an economic perspective. Therefore, proper distribution of health facilities and their efficient use is of particular importance. Further, it seems inevitable to evaluate and improve the health system, and this would be possible only through further investigation of policies, increased efficiency, limiting the unnecessary costs and responding to needs of the society.[8]
Managers of health sector are always anxious to know if the units under their management are more efficient than other units, and how much efficient their unit is if there is any difference. These questions reflect the application of economic analysis in health units. One of the most important types of economic analysis is the efficiency analysis of the firms, which properly answer these questions and even more about the performance of such units. In fact, performance evaluation viewed as a source of feedback to the managers, can help them set priorities, compare the efficiency of various units, identify the reasons behind low or high efficiency, contribute to make more informed decisions as to continue or stop some activities or programs, and help optimally allocate resources to such units.[9] The performance evaluation of health service providers is now very important, and the use of assessment results, as an indispensable management tool has become popular among all executives at various levels of the health system.[10]
In this paper, we have used a credible and mathematically valid approach to evaluate the performance of rural health centers in Langarud County, which plays an important role in promoting national health in rural areas.
DEA is one of the widely used nonparametric methods of measurement. In this method, the efficient frontier curve is created by a set of points determined by linear programming. To find the points, one can use two assumptions of constant and variable returns to scale. Here the constant return to scale is used. As this model was proposed by “Charnes, Cooper and Rhodes”, it is known as CCR Model, which is formed from the first letters of the name of these three people. It was introduced in 1978, in a paper titled “Measuring the Efficiency of Decision Making Units”.[10] Returns to constant scale mean any multiplier from inputs would produce the same multiplier of the outputs. CRS return model to unit scale is assumed as constant. Therefore, small and large units are compared to each other. In this model, if a single unit changes in the inputs, the outputs will also change (increase or decrease) with a constant proportion. In fact, the slope of the production function in this model is constant.[11]
At relative measurement of the units, Farrell focused on balanced aggregate of units for building a virtual unit, and proposed the following relation as a common measurement tool for evaluating the technical efficiency:[12]
If you seek to evaluate the efficiency of n units each of which has m inputs, and s outputs, the efficiency of the unit j ( j=1,2,…,n ) is calculated in the following way: to calculate the model of constant returns to scale for K production factor and M product that exists for each of the firms:[13]
In the above equation, y represents the outputs of the model, and s represents the number of outputs. X is the inputs, and m is the number of inputs in the model. U and V represent the weight of variables in the weighted mean. In this equation, we seek to obtain the optimal values of U and V; in a way that ratio of the total weight of products to the total weight of production factors and each firm's efficiency is maximized.[14]
The problem with the above relation is that it has infinite optimal solutions. To avoid this problem, the constraint could be added to the model, and change it into a linear programming format. As the method of linear programming for solving duality problem meant fewer constraints than the initial method, it is more appropriate to
In fact, θ shows the optimal input proportions for gaining a definite value of products to the utilized proportion of the products. The numerical value of θ is between zero and one, and the more it is closer to one, the higher would be the levels of efficiency. Index i also represents the orientation of input in solving the duality problem.[15]
In the above models, the rural healthcare centers were divided into two groups: efficient and inefficient. Therefore, this model does not care about the ranking among efficient centers, and efficient healthcare centers are marked by numerical value of one; to solve this problem, we will use Anderson-Peterson model.
Anderson–Peterson method
Anderson–Peterson in 1993 proposed a method for ranking efficient units, which made it possible to evaluate the most efficient units. In this method, the score of efficient centers could be higher than one; therefore, efficient units can be ranked the same as inefficient ones. This method consists of two steps: in the first step, we calculate efficiency the same as before. After identifying efficient centers, the constraints related to the same efficient center will be excluded from the model, so that efficiency could be estimated to be more than one.
Xij is the i input for unit j (i:1,2, 3,…m)
Yrj is the r output for unit j (i: 1, 2, 3,...,s)
Ur is the given weight to r output;
Vi is the given weight to the i input. (4)
In the above equation, the constrain is changed into and it is excluded from the constrains of the problem. As this constrain is excluded, the firm can achieve an efficiency of higher than one.
The introduction of inputs and outputs
In this paper, the performances of 45 rural healthcare centers operating under supervision of Langarud Health Network have been evaluated. The number of health workers and expenditure of every health care center were taken as inputs, and Family Health patients, outpatients and patients who asked for wound dressing and injection were taken as outputs. Family Health patients include: clients of healthy pregnancy, child care and mothers-care, and outpatients included patients suffering from blood pressure, diabetes, or those who need help with mental health immunization, and other diseases. The inputs and outputs were for the period from 20 March 2015 to 20 March in 2016.
The results of CRS model
Based on the results of the CRS model, out of 45 healthcare centers that were evaluated, 9 healthcare centers of Garask, Kororoud Khaneh, Malat, Lower Leila Kouh, Kafsh Kan Mahaleh, Moridan, Ganjali Sara, Haji Sara and Dive-Shell were efficient (Table 1).
code | Title of rural healthcare centers | outputs | inputs | |||
---|---|---|---|---|---|---|
wound dressing | outpatients | family health clients | costs (million Rials) |
number of health workers | ||
1 | Daryasar | 50 | 707 | 1984 | 107 | 3 |
2 | Lower Salkoyeh | 49 | 2376 | 378 | 118 | 2 |
3 | Dive-Shell | 79 | 2700 | 5689 | 230 | 3 |
4 | Talesh Mahaleh | 238 | 660 | 465 | 90 | 2 |
5 | Lower Leila Kouh | 45 | 1500 | 3806 | 100 | 2 |
6 | Lower Nalekiya Shahr | 20 | 240 | 480 | 35 | 2 |
7 | Tazehabad | 60 | 738 | 924 | 48 | 1 |
8 | Sadat Mahaleh | 20 | 1420 | 1349 | 70 | 1 |
9 | Khalikyasar | 26 | 1807 | 1569 | 128 | 2 |
10 | Lower Popkiyadeh | 40 | 1060 | 472 | 57 | 2 |
11 | Upper Popkiyadeh | 23 | 950 | 1218 | 82 | 2 |
12 | Agha Ali Sara | 24 | 332 | 516 | 43 | 1 |
13 | Pour-Shokuh | 38 | 1145 | 218 | 98 | 2 |
14 | Haji Sara | 48 | 2850 | 1856 | 80 | 2 |
15 | Taleb Sara | 15 | 990 | 1100 | 40 | 1 |
16 | Golab Mahaleh | 32 | 1880 | 1300 | 60 | 2 |
17 | Liseh Roud | 66 | 1680 | 1200 | 63 | 1 |
18 | Moridan | 200 | 3000 | 3500 | 121 | 3 |
19 | Malat | 40 | 2265 | 1500 | 69 | 1 |
20 | Yaghobiyeh | 68 | 1020 | 1574 | 88 | 2 |
21 | Sigaroud | 24 | 1599 | 721 | 55 | 2 |
22 | Bipass Bagh | 60 | 1080 | 980 | 69 | 1 |
23 | Lower Shekar-kesh | 40 | 1118 | 193 | 105 | 2 |
24 | Pileh Mahaleh layl | 50 | 918 | 219 | 57 | 1 |
25 | Lower Parvaresh | 90 | 1156 | 1020 | 65 | 2 |
26 | Tazeh Abad Kurd-Sara Kouh | 35 | 1815 | 820 | 102 | 2 |
27 | Khorma | 40 | 1020 | 600 | 53 | 1 |
28 | Kororoud Khaneh | 300 | 1005 | 450 | 105 | 2 |
29 | Kafsh Kan Mahaleh | 120 | 2350 | 1400 | 67 | 3 |
30 | Sadaat Mahaleh Nalekiya Shahr | 36 | 1652 | 184 | 70 | 2 |
31 | Sadaat Mahaleh Koshalshad | 7 | 1090 | 1400 | 90 | 1 |
32 | Lowkalayeh | 42 | 1982 | 1800 | 105 | 2 |
33 | Miyan Mahaleh Koshal-shad | 10 | 1211 | 240 | 73 | 2 |
34 | Fatideh | 42 | 1860 | 792 | 88 | 2 |
35 | Gol Sephid | 20 | 1369 | 373 | 71 | 2 |
36 | Darya Kenar | 50 | 1335 | 1060 | 89 | 2 |
37 | Pir Poshteh | 48 | 1508 | 264 | 56 | 2 |
38 | Lat-leil | 45 | 1207 | 947 | 70 | 2 |
39 | Bolordakan | 85 | 316 | 100 | 55 | 2 |
40 | Sarleil | 30 | 391 | 150 | 50 | 2 |
41 | Lower Siyah Manaseh | 63 | 741 | 173 | 65 | 2 |
42 | Kohlestan | 50 | 540 | 725 | 53/7 | 2 |
43 | Kiya Gahan | 32 | 598 | 1896 | 63 | 2 |
44 | Garask | 210 | 1010 | 300 | 52/5 | 2 |
45 | Ganjali Sara | 20 | 1800 | 1700 | 57 | 1 |
Table 1: Inputs and outputs used to analyze the efficiency of rural health centers in Langarud County.
Reference rural healthcare centers in CRS Model
In order to improve the performance of inefficient rural healthcare centers, they should pursue some models. Based on the results, models used for each inefficient rural healthcare centers are summarized in the Table 2.
Rows | rural healthcare centers | Performance score in CCR | Performance status | Row | rural healthcare centers | Performance score in CCR | Performance condition |
---|---|---|---|---|---|---|---|
1 | Daryasar | 0.533 | Inefficient | 24 | Pileh Mahaleh layl | 0.619 | Inefficient |
2 | Lower Salkoyeh | 0.61 | Inefficient | 25 | Lower Parvaresh | 0.678 | Inefficient |
3 | Dive-Shell | 1 | Efficient | 26 | Tazeh Abad Kurd-Sara Kouh | 0.525 | Inefficient |
4 | Talesh Mahaleh | 0.892 | Inefficient | 27 | Khorma | 0.632 | Inefficient |
5 | Lower Leila Kouh | 1 | Efficient | 28 | Kororoud Khaneh | 1 | Efficient |
6 | Lower Nalekiya Shahr | 0.435 | Inefficient | 29 | Kafsh Kan Mahaleh | 1 | Efficient |
7 | Tazehabad | 0.808 | Inefficient | 30 | Sadaat Mahaleh Nalekiya Shahr | 0.664 | Inefficient |
8 | Sadat Mahaleh | 0.8 | Inefficient | 31 | Sadaat Mahaleh Koshalshad | 0.783 | Inefficient |
9 | Khalikyasar | 0.477 | Inefficient | 32 | Lowkalayeh | 0.611 | Inefficient |
10 | Lower Popkiyadeh | 0.534 | Inefficient | 33 | Miyan Mahaleh Koshal-shad | 0.466 | Inefficient |
11 | Upper Popkiyadeh | 0.46 | Inefficient | 34 | Fatideh | 0.619 | Inefficient |
12 | Agha Ali Sara | 0.399 | Inefficient | 35 | Gol Sephid | 0.541 | Inefficient |
13 | Pour-Shokuh | 0.368 | Inefficient | 36 | Darya Kenar | 0.495 | Inefficient |
14 | Haji Sara | 1 | Efficient | 37 | Pir Poshteh | 0.761 | Inefficient |
15 | Taleb Sara | 0.878 | Inefficient | 38 | Lat-leil | 0.543 | Inefficient |
16 | Golab Mahaleh | 0.896 | Inefficient | 39 | Bolordakan | 0.397 | Inefficient |
17 | Liseh Roud | 0.993 | Inefficient | 40 | Sarleil | 0.258 | Inefficient |
18 | Moridan | 1 | Efficient | 41 | Lower Siyah Manaseh | 0.418 | Inefficient |
19th | Malat | 1 | Efficient | 42 | Kohlestan | 0.502 | Inefficient |
20 | Yaghobiyeh | 0.588 | Inefficient | 43 | Kiya Gahan | 0.819 | Inefficient |
21 | Sigaroud | 0.816 | Inefficient | 44 | Garask | 1 | Efficient |
22 | Bipass Bagh | 0.826 | Inefficient | 45 | Ganjali Sara | 1 | Efficient |
23 | Lower Shekar-kesh | 0.343 | Inefficient |
Table 2: Average of precision and recall facing the number of retrieved outputs.
Ranking of efficient rural healthcare centers in CRS model
In order to rank rural healthcare centers in CCR model, the index of number of recurrences as a reference was taken into account. Accordingly, the ranking of efficient rural healthcare centers is summarized in the Table 3.
Rows | Rural healthcare centers | Benchmark 1 | Benchmark 2 | Benchmark 3 | Benchmark 4 |
---|---|---|---|---|---|
1 | Daryasar | Moridan | Lower Leila Kouh | ||
2 | Lower Salkoyeh | Garask | Kafsh Kan Mahaleh | Malat | |
3 | Talesh Mahaleh | Moridan | Garask | Kororoud Khaneh | |
4 | Lower Nalekiya Shahr | Lower Leila Kouh | Moridan | ||
5 | Tazehabad | Malat | Lower Leila Kouh | Moridan | Kororoud Khaneh |
6 | Sadat Mahaleh | Dive-Shell | Ganjali Sara | Malat | |
7 | Khalikyasar | Malat | Ganjali Sara | Dive-Shell | |
8 | Lower Popkiyadeh | Kafsh Kan Mahaleh | Malat | Hajji Sara | |
9 | Upper Popkiyadeh | Lower Leila Kouh | Moridan | Ganjali Serra | |
10 | Agha Ali Sara | Kororoud Khaneh | Moridan | Lower Leila Kouh | |
11 | Pour-Shokuh | Garask | Kafsh Kan Mahaleh | Mortar | |
12 | Taleb Sara | Lower Leila Kouh | Moridan | Ganjali Serra | |
13 | Golab Mahaleh | Kafsh Kan Mahaleh | Ganjali Sara | Hajji Sara | |
14 | Liseh Roud | Lower Leila Kouh | Moridan | Mortar | Kororoud Khaneh |
15 | Yaghobiyeh | Kvrvrvdkhanh | Moridan | Lower Leila Kouh | |
16 | Sigaroud | Hajji Sara | |||
17 | Bipass Bagh | Malat | Kororoud Khaneh | Divshal | |
18 | Lower Shekar-kesh | Garask | Kafsh Kan Mahaleh | Malat | |
19 | Pileh Mahaleh layl | Kororoud Khaneh | Garask | Malat | |
20 | Lower Parvaresh | Moridan | Malat | Garask | Kafsh Kan Mahaleh |
21 | Tazeh Abad Kurd-Sara Kouh | Malat | Hajji Sara | Kafsh Kan Mahaleh | |
22 | Khorma | Garask | Kafsh Kan Mahaleh | Malat | |
23 | Sadaat Mahaleh Nalekiya Shahr | Kafsh Kan Mahaleh | Hajji Sara | ||
24 | Sadaat Mahaleh Koshalshad | Sara Ganjali | Divshal | ||
25 | Lowkalayeh | Ganjali Sara | Moridan | Kafsh Kan Mahaleh | Malat |
26 | Miyan Mahaleh Koshal-shad | Hajji Sara | |||
27 | Fatideh | Kafsh Kan Mahaleh | Hajji Sara | Malat | |
28 | Gol Sephid | Hajji Sara | |||
29 | Darya Kenar | Malat | Moridan | Kafsh Kan Mahaleh | Garask |
30 | Pir Poshteh | Kafsh Kan Mahaleh | Hajji Sara | ||
31 | Lat-leil | Moridan | Kafsh Kan Mahaleh | Sara Ganjali | Malat |
32 | Bolordakan | Garask | Kororoud Khaneh | ||
33 | Sarleil | Mortar | Garask | Kafsh Kan Mahaleh | |
34 | Lower Siyah Manaseh | Garask | Kafsh Kan Mahaleh | Malat | |
35 | Kohlestan | Moridan | Garask | ||
36 | Kiya Gahan | Lower Leila Kouh | Moridan |
Table 3: Benchmarking for inefficient rural healthcare centers in CRS method.
The results of the AP-CCR model
Anderson-Peterson model was used for ranking rural healthcare centers. Accordingly, rural healthcare center in Garask with the highest efficiency score was in the first place.
According to the study results, 9 out of 45 rural healthcare centers in Langarud are efficient and the remaining ones are inefficient.
Among the efficient rural healthcare centers, the one in Garask ranked first, and the rural healthcare centers in Kororoud Khaneh, Malat, Lower Leila Kuh, Kafsh Kan Mahaleh, Moridan, Ganjali Sara, Hajji Sara, and Dive-shell were respectively ranked second to ninth. These findings are in consistent with Shoja et al. which evaluated the performance of rural healthcare centers in Firoozkooh. Based on the study results, 5 out of 18 rural healthcare centers in Firoozkooh were efficient and the remaining ones were inefficient. In ranking the rural healthcare centers, the one in Arjomand achieved the highest efficiency.
In this study which was conducted on Langarud County, the average efficiency of 36 rural healthcare centers was 61%, this suggests that potential average reduction of 39% has no effect on outputs.
The feasibility of DEA in this study showed that 80% of rural healthcare centers were inefficient and 20% were efficient, this is comparable to Marschall et al. study,16 in which 30% of the rural healthcare centers in Burkina Faso were inefficient. Also, the study, in which 45 rural healthcare centers were evaluated using DEA, is in consistent with Caballer-Tarazona et al., on 22 hospitals in Valencia Association, in which 6 hospitals were effective and 16 were ineffective.
Hughes et al., evaluating 70 NSW hospitals, Lina evaluating 43 public hospitals in Finland, Webster et al., evaluating 301 private hospitals in Australia, and Sear and Chirikos evaluating 186 hospitals in Florida have all emphasized using DEA for evaluating the efficiency of hospitals. Meanwhile, Gannon evaluating 60 hospitals in Ireland[17] and Mortimer and Peacock on 38 public hospitals in Australia all used DEA to evaluate the relative efficiency of the hospitals.
The results provide authorities with a clear view of the capabilities of rural healthcare centres and managers of health sector, in a way that managers can use the results to evaluate the performance of rural healthcare centres, and make proper decision to overcome the weaknesses. Therefore, we can identify the strengths and weaknesses through examining the results and rankings in this article, and accordingly, one can assess the realization of strategic goals of health sector, and define the future strategy for each unit.
Interpreting the efficiency score of rural healthcare centres, we found that some units have a performance score higher than others, and tend to be efficient. But some other units are known as the most inefficient units and require more time and endeavour to improve their efficiency.
In some units, some special administrative policies are adopted such as reducing the costs of consumables and reconsidering the allocation of funds for some units, in a way that the output is commensurate with its costs. In some other units, layoffs could be useful where there are a few clients, and one person can properly perform the tasks and be responsive to clients and provide the services. This way, the surplus workforce would be employed for units which do not have enough staff. The study also revealed that in some units, the total number of clients to the population is falsely too high or too low, which could be caused by various factors such as cultural view of the rural people towards going to rural healthcare centres, etc. If such factors are identified, they could be used to promote the efficiency of such centres. Besides, some inefficient centres can model the centres introduced in the table as referral model, and reduce the cost of inputs, or increase their total outputs for example through the number of patients, etc., to achieve higher efficiency.