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Global Journal of Health Science logoLink to Global Journal of Health Science
. 2014 Jun 24;6(6):28–36. doi: 10.5539/gjhs.v6n6p28

Assessment the Trend of Inequality in the Distribution of Intensive Care Beds in Iran: Using GINI Index

Mohammad Meskarpour-Amiri 1,2, Parisa Mehdizadeh 3, Mohsen Barouni 4, Nooredin Dopeykar 5,, Maryam Ramezanian 6
PMCID: PMC4825512  PMID: 25363104

Abstract

Background and Aim:

While most of the published researches have reported the amount of inequity in geographical distribution of important health resources, only a small number of studies have focused on the trend of inequality in the distribution of these resources.

The purpose of this study was to determine the trend of inequality in the distribution of intensive care beds in Iran during 2010 to 2012 by using the Gini coefficient.

Methods:

This is a cross-sectional research conducted in 2013. The changes over three years (2010 to 2012) were calculated by Gini coefficient to investigate the trend of inequality in geographical distribution of intensive care beds (CCU, ICU and NICU).

Results:

The Gini coefficient for CCU beds was calculated as 0.02, 0.04 and 0.06 in 2010, 2011 and 2012, respectively. The Gini coefficient for ICU beds was calculated as 0.03, 0.05 and 0.05 in 2010, 2011 and 2012, respectively. Also, the Gini coefficient for NICU bed was calculated as 0.02, 0.03 and 0.04 in 2010, 2011 and 2012, respectively.

Conclusion:

Regarding to Gini coefficient, the trend of inequality was increased in the distribution of intensive care beds in Iran. Particularly, the inequalities in distribution of CCU beds were significantly increased during past years. In fact, if this trend of inequality continues, the distribution of intensive care beds will be extremely unequal in the next five years in Iran.

Keywords: inequality, Intensive Care Beds, GINI Index, ICU, CCU, NICU

1. Background

In general, one of the most important goals of a health system is to provide public accessibility and equality in receiving health and treatment services (Kiadaliri, Najafi, & Haghparast-Bidgoli, 2011; Balarajan, Selvaraj, & Subramanian, 2011). Since accessibility to health is one of the basic rights of individuals in the society; nowadays accessibility of individuals in a society to health services counts as one measure of development (Kottke & Isham, 2010; Mackenbach et al., 2008). Furthermore, limited accessibility to health services and the inequality in availability of the services furnished by health and treatment systems deprives these people of acceptable and effective treatment (Kottke & Isham, 2010; Reddy, 2004; Tofighi, Meskarpour, & Ameryoun, 2011).

Inequality in health services in different countries has taken the form of a global challenge (Mackenbach et al., 2008; Tang et al., 2008) affected by various factors, including individual, social and geographical variables (Mackenbach et al., 2003; Marmot, 2001). These factors are stronger in developing countries (Balarajan et al., 2011) so much so that the geographical distribution of health in developing countries has turned into a fundamental issue. Therefore, the measurement of fair distribution of health services on top of previous measures has been emphasized by World Health Organization (World Health Organization, 2000).

Identifying the number and types of intensive care beds and their distribution may prove as an indirect measurement of the accessibility to inpatient intensive care services (Horev, Pesis-Katz, & Mukamel, 2004; Pedersen & Lilleeng, 2000). Despite the fact that in many cases the proportion of beds to population may be used as a measure of the distribution of health services, a high proportion does not necessarily imply an equal accessibility of the population to such facilities and services. Therefore, examining the distribution of a service in a given geographical location could be a supplementary criterion to the existing measures of central tendencies (Horev et al., 2004).

Iran, like other developing countries, is faced with the lack of intensive care resources (Ameryoun, Meskarpour-Amiri, Lorgard Dezfuli-Nejad, Khoddami-Vishteh, & Tofighi, 2011; Tofighi, Meskarpour Amiri, Ameriuon, & Naseri, 2011). Although the number of intensive care beds has grown substantially in recent years, it does not still seem enough. Previous studies (Ameryoun et al., 2011) showed that the number of per population intensive care beds in Iran is lower than those in many developing countries. Shortage of per population intensive care beds in Iran causes problems such as patient transference between provinces (Ameryoun et al., 2011), long waiting line of receiving intensive care unit services (Abedi, Seiyamiyan, & Rostami, 2012) increase mortality and cost of treatment (Ameryoun et al., 2011; Tofighi et al., 2011), reducing the patient satisfaction (Abdi, Delgoshaei, Ravaghi, Abbasi, & Heyrani, 2013) and quality of care (Falahinia, Zareian, Oshvandi, Farhanchi, & Moghimbigi, 2013) in intensive care units. One solution to these problems is to increase the number of intensive care beds in short term, but according to the limited resources this doesn’t seem rational and feasible. Another solution is to distribute the available intensive care beds more efficiently and equitably. In terms of intensive care beds shortage, the uneven distribution of the bed can greatly threaten the access to care. In other words, inequality in the distribution of intensive care beds could increase the problems caused by the shortage of this beds. Thus, the distribution of intensive care beds in developing countries like Iran seems to be more important.

In Iran, establishment of public hospitals by government and especially set up of intensive care units in public hospitals are greatly influenced by two main factors, the number of population and the bargaining power of local politicians. Therefore, the needs of population and regional epidemiology of diseases have received lower attention in health resource allocation. Additionally, the activities of the private sector in health care were always based on the principle of profit; however the government`s incentives were not useful to encourage private sector to develop in less developed areas (Ameryoun et al., 2011; Tofighi et al., 2011).

While many studies have focused on measuring the amount of inequality in the distribution of health resources in both developed and developing countries, there still is a question here: whether the distribution of health care resources goes toward equality or inequality? In fact, most of the published researches have emphasized on the inequality in geographical distribution of important medical resource such as hospital beds (Ameryoun et al., 2011; Mackenbach et al., 2008; Nishiura et al., 2004), Medical staffs (Fülöp, Kopetsch, Hofstätter, & Schöpe, 2008; Kreng & Yang, 2011; Theodorakis & Mantzavinis, 2005) and medical equipment (Chun-xia, Lang, Yu-ming, & Zhao-hui, 2007; He Yu, & Chen, 2013), however only a small number of studies have focused on the trend of inequality in the distribution of these resources.

Inequality in receiving health services is measured by different scales (Williams & Doessel, 2006), one of which is the Gini coefficient which is based on the Lorenz curve. This coefficient compares the cumulative frequency of the distribution of a given variable with the normal distribution of that variable (which shows equality) (Berndt, Fisher, & Rajendrababu, 2003; Williams & Doessel, 2006).

Over the past few years, dramatic growth has been occurred in the number of intensive care beds in Iran. Only from 2010 to 2011, the number of intensive care beds has increased by 12.6%. Due to the increase in intensive care beds in Iran, the attention of policy makers and researchers have been on this question that whether the trend in distribution of intensive care beds is towards equality or inequality? The purpose of this study was to determine the trend of inequality in the distribution of intensive care beds in Iran during 2010 to 2012, using the Gini coefficient.

2. Materials and Methods

This study was a cross-sectional research that performed in 2013. Changes in the Gini coefficient over three years (2010 to 2012) were used to study the trend of inequality in geographical distribution of intensive care beds (CCU, ICU and NICU). The population data of Iranian provinces from 2010 to 2012 were obtained from the Statistics Center of Iran. The number of intensive care beds (ICU, Post ICU and NICU beds) in each province from 2010 to 2012 was based on the latest reported information of the Ministry of Health and Medical Education of Iran. According to the prior studies (Ameryoun et al., 2011; He et al., 2013), the Gini coefficient is calculated by the following formula:

graphic file with name GJHS-6-28-g001.jpg

Where X was the cumulative percentage of the population and Y was the cumulative percentage of each type of intensive care beds. The Gini coefficient ranges between 0 and 1, where theoretically, zero corresponds to a perfect equality and 1 corresponds to a perfect inequality. Based on the previous studies (Ameryoun et al., 2011; He et al., 2013), Gini coefficient which is smaller than 0.2 is considered as low inequality level; between 0.2 and 0.3 is considered as moderate inequality; between 0.3 and 0.4 is considered as high inequality; higher than 0.4 is considered as extreme inequality.

The demographic data as well as the number of CCU, ICU and NICU beds were entered into MS Excel spreadsheet. The number of each type of CCU and Post CCU bed per 100.000 people, and the cumulative percentages of each type of bed were calculated. Finally, the Gini coefficients for each type of bed were calculated by using the above formula.

3. Results

In 2010, 2011 and 2012, Iran had a total population of 73.650.566, 74.733.231 and 75.149.669 with total numbers of 3160, 3430 and 3665 CCU beds, the total number of 3384, 3576 and 3698 ICU beds and the total number of 1189, 1295 and 1349 NICU beds, respectively. Tehran, the capital of Iran, had the largest amount of CCU, ICU and NICU beds and population during 2010-2012. The total numbers of CCU, ICU and NICU beds from 2010 to 2012 are shown in Table 1.

Table 1.

Total number of CCU, ICU and NICU beds from 2010 to 2012 by province

Province 2010 2011 2012



Population CCU ICU NICU Population CCU ICU NICU Population CCU ICU NICU
East Azerbaijan 3667968 125 157 83 3691270 143 162 86 3724620 159 176 88
West Azerbaijan 2979604 105 146 52 3016301 110 147 56 3080576 110 147 57
Ardebil 1238778 40 79 18 1242956 42 81 18 1248488 44 83 18
Isfahan 4741615 224 222 75 4804458 235 232 76 4879312 238 232 76
Ilam 561001 16 18 8 566332 17 19 9 557599 18 19 10
Bushehr 928930 45 35 17 943535 46 37 17 1032949 46 41 17
Tehran 14448184 717 790 247 12505705 763 780 256 12183391 871 801 273
Karaj NE NE NE NE 2289412 66 45 10 2412513 66 48 10
Chaharmahal&Bakhtyari 883856 30 34 20 892909 32 34 20 895263 34 34 21
South Khorasan 666493 26 23 14 676794 27 26 17 662534 27 38 19
RazaviKhorasan 5852010 149 208 119 5940766 153 231 129 5994402 155 237 131
North Khorasan 831684 25 25 20 838781 25 25 20 867727 25 25 20
Khuzestan 4420874 154 164 29 4471488 165 168 30 4531720 179 179 38
Zanjan 978310 25 52 19 983369 29 67 20 1015734 34 67 22
Semnan 615601 37 53 14 624482 37 53 14 631218 37 53 14
Sistan&Baluchestan 2650767 103 111 57 2733205 119 123 67 2534327 119 123 67
Fars 4479087 280 241 55 4528514 284 248 64 4596658 287 252 66
Qazvin 1194771 23 29 10 1212464 26 32 10 1201565 28 32 10
Qom 1107145 40 74 20 1127713 40 74 24 1151672 40 74 24
Kordestan 1460180 62 34 14 1467585 70 47 19 1493645 70 47 19
Kerman 2872902 122 87 52 2947346 126 108 57 2938988 138 117 61
Kermanshah 1898464 70 116 45 1905793 73 119 45 1945227 70 119 45
Kohkiluyeh & Buyer Ahmad 660216 15 16 6 669140 15 16 15 658629 15 16 15
Golestan 1669019 78 65 17 1687086 92 65 20 1777014 92 69 24
Gilan 2440405 82 61 13 2453469 95 70 13 2480874 109 74 13
Lorestan 1747159 93 82 29 1758226 113 84 40 1754243 117 84 43
Mazandaran 3007570 166 221 69 3037336 178 230 69 3073943 222 234 69
Markazi 1381645 66 50 26 1392435 66 53 26 1413959 66 53 26
Hormozgan 1519700 66 34 8 1558878 67 37 11 1578183 68 40 14
Hamedan 1699815 49 82 17 1699588 49 85 21 1758268 54 99 23
Yazd 1046816 127 75 16 1065893 127 78 16 1074428 127 85 16
Total 73650566 3160 3384 1189 73733231 3430 3576 1295 75149669 3665 3698 1349

NE: Not exist (after the Parliamentary approval, Karaj was introduced as 31st province of Iran from 2011).

There were 4.29, 4.59 and 4.87 CCU beds for each 100.000 people across the nation in 2010, 2011 and 2012 respectively. There were 4.59, 478 and 4.92ICU beds for each 100.000 people across the nation in 2010, 2011 and 2012 respectively. Also, there were 1.61, 1.73 and 1.79 NICU beds for each 100.000 people in 2010, 2011 and 2012 respectively. Table 2 shows the number of CCU, ICU and NICU beds per 100.000 populations from 2010 to 2012.

Table 2.

Number of CCU, ICU and NICU beds per 100.000 population from 2010 to 2012

Province 2010 2011 2012



CCU ICU NICU CCU ICU NICU CCU ICU NICU
East Azerbaijan 3.408 4.28 2.263 3.874 4.389 2.33 4.269 4.725 2.363
West Azerbaijan 3.524 4.9 1.745 3.647 4.874 1.857 3.571 4.772 1.85
Ardebil 3.229 6.377 1.453 3.379 6.517 1.448 3.524 6.648 1.442
Isfahan 4.724 4.682 1.582 4.891 4.829 1.582 4.878 4.755 1.558
Ilam 2.852 3.209 1.426 3.002 3.335 1.589 3.228 3.407 1.793
Bushehr 4.844 3.768 1.83 4.875 3.921 1.802 4.453 3.969 1.646
Tehran 4.963 5.468 1.71 6.101 6.237 2.047 7.149 6.575 2.226
Karaj NE NE NE 2.883 1.966 0.437 2.736 1.99 0.415
Chaharmahal&Bakhtyari 3.394 3.847 2.263 3.584 3.808 2.24 3.798 3.798 2.346
South Khorasan 3.901 3.451 2.101 3.989 3.842 2.512 4.075 5.736 2.868
RazaviKhorasan 2.546 3.554 2.033 2.575 3.888 2.171 2.586 3.954 2.185
North Khorasan 3.006 3.006 2.405 2.981 2.981 2.384 2.881 2.881 2.305
Khuzestan 3.483 3.71 0.656 3.69 3.757 0.671 3.95 3.95 0.839
Zanjan 2.555 5.315 1.942 2.949 6.813 2.043 3.347 6.596 2.166
Semnan 6.01 8.609 2.274 5.925 8.487 2.242 5.862 8.396 2.218
Sistan&Baluchestan 3.886 4.187 2.15 4.354 4.5 2.451 4.696 4.853 2.644
Fars 6.251 5.381 1.228 6.271 5.476 1.413 6.244 5.482 1.436
Qazvin 1.925 2.427 0.837 2.144 2.639 0.825 2.33 2.663 0.832
Qom 3.613 6.684 1.806 3.547 6.562 2.128 3.473 6.425 2.084
Kordestan 4.246 2.328 0.959 4.77 3.203 1.295 4.687 3.147 1.272
Kerman 4.247 3.028 1.81 4.275 3.664 1.934 4.695 3.981 2.076
Kermanshah 3.687 6.11 2.37 3.83 6.244 2.361 3.599 6.118 2.313
Kohkiluyeh& Buyer Ahmad 2.272 2.423 0.909 2.242 2.391 2.242 2.277 2.429 2.277
Golestan 4.673 3.895 1.019 5.453 3.853 1.185 5.177 3.883 1.351
Gilan 3.36 2.5 0.533 3.872 2.853 0.53 4.394 2.983 0.524
Lorestan 5.323 4.693 1.66 6.427 4.778 2.275 6.67 4.788 2.451
Mazandaran 5.519 7.348 2.294 5.86 7.572 2.272 7.222 7.612 2.245
Markazi 4.777 3.619 1.882 4.74 3.806 1.867 4.668 3.748 1.839
Hormozgan 4.343 2.237 0.526 4.298 2.374 0.706 4.309 2.535 0.887
Hamedan 2.883 4.824 1 2.883 5.001 1.236 3.071 5.631 1.308
Yazd 12.13 7.165 1.528 11.91 7.318 1.501 11.82 7.911 1.489
Total 4.291 4.595 1.614 4.59 4.785 1.733 4.877 4.921 1.795

NE: Not exist (after the Parliamentary approval, Karaj was introduced as 31st province of Iran from 2011).

The Gini coefficient for CCU bed was calculated as 0.02, 0.04 and 0.06 in 2010, 2011 and 2012 respectively. The Gini coefficient for ICU bed was calculated as 0.03, 0.05 and 0.05 in 2010, 2011 and 2012 respectively. Also, the Gini coefficient for NICU bed was calculated as 0.02, 0.03 and 0.04 in 2010, 2011 and 2012 respectively. Table 3 shows the Gini coefficient for CCU, ICU and NICU beds from 2010 to 2012. Also, Figure 1 illustrates the trend of inequality in geographical distribution of each intensive bed during 2010-2012.

Table 3.

Gini coefficient for CCU, ICU and NICU from 2010 to 2012

Gini coefficient 2010 2011 2012
CCU 0.0227 0.0468 0.0676
ICU 0.0386 0.0542 0.0526
NICU 0.0210 0.0358 0.0416

Figure 1.

Figure 1

Trend of Gini coefficient of CCU, ICU and NICU during 2010-2012

4. Discussion

Generally speaking, it should be noted that the cost-effectiveness of the establishment of intensive care units is much less than the cost-effectiveness of preventive measures such as immunization and primary health care. Therefore, based on the principle of prioritizing resource allocation, especially in the developing countries like Iran, it is necessary to consider the cost-opportunity of investment in the development of intensive care units. The shortage of intensive care beds in Iran has been cited in numerous studies (Abedi et al., 2012; Ameryoun et al., 2011; Tofighi et al., 2011). However, this study was intended to examine the issue of inequality trend in the distribution of existing intensive care beds in Iran regardless of whether or not a shortage exists in number of such beds. As a matter of fact, the unequal distribution of intensive care beds often leads to unequal distribution of valuable health resources such as specialist doctors, medical equipment and trained nurses.

The findings show that the mean number of CCU beds per 100.000 population in 2010, 2011 and 2012 are 4.29, 4.59 and 4.87, respectively. In each of the three years, Yazd province with 12.13, 11.91 and 11.82 beds per 100.000 population had the highest CCU beds than any other provinces (two times more than that of other provinces). Also, Qazvin province in 2010 and 2011 with 1.92 and 2.14 respectively and Kohkiluyeh Province in 2012 with 2.27 had the lowest CCU beds per 100.000 population. The obtained Gini coefficient for the distribution of CCU beds in 2010, 2011 and 2012 was 0.022, 0.046 and 0.067 respectively which statically proves the equality in geographical distribution of CCU beds across Iran. But the trend of Gini coefficient during the three years was toward inequality, So that the numerical value of the Gini coefficient was nearly tripled from 2010 to 2012.

In a study, Kiadaliri et al. (Kiadaliri, Safari, & Hosseinpour, 2010) showed that Yazd province enjoys the most equal distribution of CCU beds and Ilam province suffers from the least equal distribution of CCU beds. A study on the distribution of active hospital beds in Iran, the Gini coefficient for active beds was reported 0.08 and active beds per 10.000 population in 2006 was reported 9.2, while Yazd province had maximum and Lorestan province had the minimum beds per population (Tofighi, Maleki, Shahabi, Delpasand, & Nafisi, 2010). In another study conducted in 2002 based on Morris Imbalance Coefficient, Yazd province stands at the highest rank in terms of the number of hospital beds and Semnan province ranks the highest in terms of the number of health centers (Eskandari, 2010). A study conducted on the distribution of CCU beds in 24 university hospitals in the Netherlands from 2004 to 2006, Gini coefficients were reported 0.638, 0.569 and 0.569, which reflect the unequal distribution (De Bruin, Bekker, & Van Zanten, 2010).

The mean number of ICU beds per 100.000 population in 2010, 2011 and 2012 are 4.59, 4.78 and 4.92, respectively. In each of the three years, Semnan province with 8.60, 8.48 and 8.39 beds per 100.000 population had the highest ICU beds than any other provinces. Also, Hormozgan province in 2010 with 2.23 and Alborz province (Karaj) in 2011 and 2012 with 1.96 and 1.99 respectively had the lowest ICU beds per population. The obtained Gini coefficient for the distribution of ICU beds in 2010, 2011 and 2012 was 0.038, 0.054 and 0.052 respectively; as a result it proves the equality in geographical distribution of CCU beds across Iran. However, the general trend of Gini coefficient during the three years was toward inequality, so that the numerical value of the Gini coefficient has generally been rising from 2010 to 2012.

In the same study conducted by Ameryoun et al. (2011) in 2011, the number of ICU beds per 100.000 population in Iran in 2006 was reported 5.3 and the Gini coefficient was reported 0.17. Also, Semnan with 8.6 ICU beds per 100.000 population considered as the second province with the maximum of ICU beds. In comparison with the results of our study, the mean number of ICU beds is much more than the obtained Gini coefficient, since according to Ameryoun et al. (2011) the reported number of ICU beds was belonged to both public and private sectors. In a study on the distribution of ICU beds in Western Europe countries, Wunsch et al. (Wunsch et al., 2008) showed that the proportion of ICU beds per 100.000 people in 2005 was 9.3 in France, 8.4 in the Netherlands, 8.2 in Spain and 5.3 in England. In South Africa, there were 4, 168 ICU beds in 2005, from which 86% were installed in three provinces. The proportion of beds varied greatly in different provinces of Iran, from 1:20.000 to 1:80.000 (Bhagwanjee & Scribante, 2007). A study conducted by Horev et al in the U.S. in 1998 on the distribution of hospital beds, the coefficients in different states of America were 0.0571-0.4303 (Horev et al., 2004). The 1970-1997 trends indicated the progressive equality in the distribution of hospital beds. It has been reported that the northern states enjoy an equal distribution of hospital beds (Horev et al., 2004).

Also, the mean number of NICU beds per 100.000 population in 2010, 2011 and 2012 are 1.61, 1.73 and 1.79, respectively. In each of the three years, Northern Khorasan province with 2.40, 2.38 and 2.30 beds per 100.000 population had the highest NICU beds than any other provinces (two times more than that of other provinces). In addition, Hormozgan province in 2010 with 0.52 and Alborz provience (Karaj) in 2011 and 2012 with 0.43 and 0.41 respectively had the lowest per population NICU beds. The obtained Gini coefficient for distribution of NICU beds in 2010, 2011 and 2012 was 0.021, 0.035 and 0.041, respectively which statically proves the equality in geographical distribution of CCU beds across Iran. However, the general trend of Gini coefficient during the three years was toward inequality, so that the numerical value of the Gini coefficient was about double from 2010 to 2012. In the same study which was conducted in Iran, the number of NICU beds per 100,000 population and Gini coefficient were reported 1.6 and 0.23, respectively (Ameryoun et al., 2011).

The high prevalence and morbidity associated with cardiovascular diseases is one of the most pressing health problems in Iran. The findings of the studies showed that the prevalence of cardiovascular diseases in Iran is higher than the prevalence of cardiovascular diseases in Western countries and some Middle East countries (Ebrahimi, Kazemi-Bajestani, Ghayour-Mobarhan, & Ferns, 2011; Talaei et al., 2013). According to this dilemma, therefore, it is necessary to pay more attention on appropriate distribution of intensive care beds in Iran.

However there are some limitations in this study including that in this study we examined the distribution of intensive care beds in the public sector only, so with considering the private sector the inequality may be more because the private sector is often developed by the demand and ability to pay not population needs. Also recommended that in future studies the equity in distribution of intensive care beds examined based on the epidemiology of diseases and specific needs of each province.

5. Conclusion

According to our study, although in all years (2010-2012) the numerical value of Gini coefficients proves equality in distribution of Intensive Care Beds across Iran but the trend of Gini coefficients was toward inequality. In other words, increasing rate of inequality observed in Gini coefficient trend for Intensive care beds in Iran. Particularly the inequalities in distribution of CCU beds are significantly increased during past years. If this trend of inequality did persist, in the next five years the distribution of intensive care beds in Iran can be extremely unequal.

References

  1. Abdi Z, Delgoshaei B, Ravaghi H, Abbasi M, Heyrani A. The culture of patient safety in an Iranian intensive care unit. J Nurs Manag. 2013. http://dx.doi.org/10.1111/jonm.12135 . [DOI] [PubMed]
  2. Abedi G, Seiyamiyan H, Rostami F. The study of waiting line of receiving intensive care unit services in the hospitals. Health MED. 2012;6(1):126–130. [Google Scholar]
  3. Ahmad-Kiadaliri A, Najafi B, Haghparast-Bidgoli H. Geographic distribution of need and access to health care in rural population: an ecological study in Iran. Int J Equity Health. 2011;10(1):39. doi: 10.1186/1475-9276-10-39. http://dx.doi.org/10.1186/1475-9276-10-39 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Ahmad-Kiadaliri A, Safari H, Hosseinpour R. Geographic Distribution of CCU Beds in Iran. Paper presented at the 13th Biennial European Conference of the Society for Medical Decision Making, Hall i.T./Innsbruck, Austria. 2010 [Google Scholar]
  5. Ameryoun A, Meskarpour-Amiri M, Lorgard Dezfuli-Nejad M, Khoddami-Vishteh H, Tofighi S. The Assessment of Inequality on Geographical Distribution of Non-Cardiac Intensive Care Beds in Iran. Iranian J Publ Health. 2011;40(2):25–33. [PMC free article] [PubMed] [Google Scholar]
  6. Balarajan Y, Selvaraj S, Subramanian S. V. Health care and equity in India. Lancet. 2011;377(9764):505–515. doi: 10.1016/S0140-6736(10)61894-6. http://dx.doi.org/10.1016/S0140-6736(10)61894-6 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Berndt D. J, Fisher J. W, Rajendrababu R. V, Studnicki J. Measuring healthcare inequities using the Gini index. Paper presented at the 36th Annual Hawaii International Conference on System Sciences, Hawaii. 2003 [Google Scholar]
  8. Bhagwanjee S, Scribante J. National audit of critical care resources in South Africa- unit and bed distribution. S Afr Med J. 2007;97(12 Pt 3):1311–1314. [PubMed] [Google Scholar]
  9. Chun-xia M, Lang Z, Yu-ming G, Zhao-hui Q. Study of large medical equipment allocation in Xuzhou. J Zhejiang Univ Sci B. 2007;8(12):881–884. doi: 10.1631/jzus.2007.B0881. http://dx.doi.org/10.1631/jzus.2007.B0881 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. De Bruin A, Bekker R, Van Zanten L. Dimensioning hospital wards using the Erlang loss model. Annals of Operations Research. 2010;178:23–43. http://dx.doi.org/10.1007/s10479-009-0647-8 . [Google Scholar]
  11. Ebrahimi M, Kazemi-Bajestani S, Ghayour-Mobarhan M, Ferns G. Coronary artery disease and its risk factors status in Iran: A review. Iranian Red Crescent Medical Journal. 2011;13(9):610. doi: 10.5812/kowsar.20741804.2286. http://dx.doi.org/10.5812/kowsar.20741804.2286 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Eskandari A. Hospital in Tehran. In Hospital management congress, Tehran. 2010:171–178. [Google Scholar]
  13. Falahinia G, Zareian A, Oshvandi K, Farhanchi A, Moghimbigi A. Comparison of intensive care units Structural Standards. Iranian Journal of Critical Care Nursing. 2013;5(4):222–227. [Google Scholar]
  14. Fülöp G, Kopetsch T, Hofstätter G, Schöpe P. Regional distribution effects of ’needs planning’for office-based physicians in Germany and Austria-methods and empirical findings. J Public Health. 2008;16(6):447–455. http://dx.doi.org/10.1007/s10389-008-0187-8 . [Google Scholar]
  15. He D, Yu H, Chen Y. Equity in the distribution of CT and MRI in China: a panel analysis. Int J Equity Health. 2013;12:39. doi: 10.1186/1475-9276-12-39. http://dx.doi.org/10.1186/1475-9276-12-39 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Horev T, Pesis-Katz I, Mukamel D. B. Trends in geographic disparities in allocation of health care resources in the US. Health Policy. 2004;68(2):223–232. doi: 10.1016/j.healthpol.2003.09.011. http://dx.doi.org/10.1016/j.healthpol.2003.09.011 . [DOI] [PubMed] [Google Scholar]
  17. Kottke T. E, Isham G. J. Measuring health care access and quality to improve health in populations. Prev Chronic Dis. 2010;7(4):A73. [PMC free article] [PubMed] [Google Scholar]
  18. Kreng V. B, Yang C. T. The equality of resource allocation in health care under the National Health Insurance System in Taiwan. Health Policy. 2011;100(2-3):203–210. doi: 10.1016/j.healthpol.2010.08.003. http://dx.doi.org/10.1016/j.healthpol.2010.08.003 . [DOI] [PubMed] [Google Scholar]
  19. Mackenbach J. P, Stirbu I, Roskam A.-J. R, Schaap M. M, Menvielle G, Leinsalu M, Kunst A. E. Socioeconomic inequalities in health in 22 European countries. New England Journal of Medicine. 2008;358(23):2468–2481. doi: 10.1056/NEJMsa0707519. [DOI] [PubMed] [Google Scholar]
  20. Mackenbach J. P, Bos V, Andersen O, Cardano M, Costa G, Harding S, Kunst A. E. Widening socioeconomic inequalities in mortality in six Western European countries. Int J Epidemiol. 2003;32(5):830–837. doi: 10.1093/ije/dyg209. http://dx.doi.org/10.1093/ije/dyg209 . [DOI] [PubMed] [Google Scholar]
  21. Marmot M. Inequality in health. N Engl J Med. 2001;345(2):134–136. doi: 10.1056/NEJM200107123450210. http://dx.doi.org/10.1056/nejm200107123450210 . [DOI] [PubMed] [Google Scholar]
  22. Nishiura H, Barua S, Lawpoolsri S, Kittitrakul C, Leman M. M, Maha M. S, Muangnoicharoen S. Health inequalities in Thailand: geographic distribution of medical supplies in the provinces. Southeast Asian J Trop Med Public Health. 2004;35(3):735–740. [PubMed] [Google Scholar]
  23. Pedersen P, Lilleeng S. Resource distribution in mental health services: changes in geographic location and use of personnel in Norwegian mental health services 1979-1994. J Ment Health Policy Econ. 2000;3(1):45–53. doi: 10.1002/1099-176x(200003)3:1<45::aid-mhp71>3.0.co;2-1. [DOI] [PubMed] [Google Scholar]
  24. Reddy K. S. Cardiovascular disease in non-Western countries. N Engl J Med. 2004;350(24):2438–2440. doi: 10.1056/NEJMp048024. http://dx.doi.org/10.1056/NEJMp048024 . [DOI] [PubMed] [Google Scholar]
  25. Talaei M, Sarrafzadegan N, Sadeghi M, Oveisgharan S, Marshall T, Thomas G. N, Iranipour R. Incidence of cardiovascular diseases in an Iranian population: the Isfahan Cohort Study. Arch Iran Med. 2013;16(3):138–144. [PubMed] [Google Scholar]
  26. Tang S, Meng Q, Chen L, Bekedam H, Evans T, Whitehead M. Tackling the challenges to health equity in China. Lancet. 2008;372(9648):1493–1501. doi: 10.1016/S0140-6736(08)61364-1. http://dx.doi.org/10.1016/S0140-6736(08)61364-1 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Theodorakis P, Mantzavinis G. Inequalities in the distribution of rural primary care physicians in tow remote neighboring prefectures of Greece and Albania. Rural and Remote Health. 2005;5:475. [PubMed] [Google Scholar]
  28. Tofighi S, Maleki M. R, Shahabi M, Delpasand M, Nafisi A. Distribution of Specialized Physicians and Active Beds in the Iranian Government Hospitals between 2001 and 2006. Journal of School of Public Health and Institute of Public Health Research. 2010;8(3):1–10. [Google Scholar]
  29. Tofighi S, Meskarpour Amiri M, Ameriuon A, Naseri H. Equity in distribution of intensive care beds in Iran with Gini coefficient and Lorenz curve approach. Yafteh. 2011;12(2):75–83. [Google Scholar]
  30. Tofighi S, Meskarpour M, Ameryoun A. Equality of geographical distribution of kidney transplant beds in Iran: A Gini index study. Management in Health. 2011;5(4):19–22. [Google Scholar]
  31. Williams R. F, Doessel D. P. Measuring inequality: tools and an illustration. Int J Equity Health. 2006;5:5. doi: 10.1186/1475-9276-5-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. World Health Organization. Health systems: improving performance. Geneva: World Health Organization; 2000. [Google Scholar]
  33. Wunsch H, Angus D, Harrison D, Collange O, Fowler R, Hoste E. Variation in critical care services across North America and Western Europe. Crit Care Med. 2008;36(10):2787–2793. doi: 10.1097/CCM.0b013e318186aec8. http://dx.doi.org/10.1097/CCM.0b013e318186aec8 . [DOI] [PubMed] [Google Scholar]

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