| Home | E-Submission | Sitemap | Contact Us |  
top_img

Aghapour, Basakha, Kamal, and Pourreza: Inequality in Private Health Care Expenditures: A 36-Year Trend Study of Iranian Households

ABSTRACT

Objectives

Throughout history, societies have been impacted by inequality. Many studies have been conducted on the topic more broadly, but only a few have investigated inequalities in out-of-pocket health payments (OHP). This study measures OHP inequality trends among the Iranian households.

Methods

This study used data from the Iranian Statistics Center on Iranian household income and expenditures. The analysis included a total of 995 300 households during the 36 years from 1984 to 2019. The Gini coefficient, Atkinson index, and Theil index were calculated for Iranian OHP.

Results

Average Iranian household OHP increased from 33 US dollar (USD) in 1984 to 47 USD in 2019. During this 36-year span, the average±standard deviation Gini coefficient for OHP was 0.73±0.04, and the Atkinson and Theil indexes were 0.68±0.05 and 1.14±0.29, respectively. The Gini coefficients for the subcategories of OHP of outpatient diagnostic services, medical assistant accessories, hospital inpatient services, and addiction cessation were 0.70, 0.61, 0.84, and 0.64, respectively.

Conclusions

In this study, we scrutinized trends of inequality in the OHP of Iranian households. Inequality in OHP decreased slightly over the past four decades. An analysis of trends among different subgroups revealed that affluent households, such as households with insurance coverage and households in higher income deciles, experienced higher inequality. Therefore, lower inequality in health care expenditures may be related to restricted access to health care services in Iran.

INTRODUCTION

A key concern for policymakers has been providing households with financial support for health care services [1,2]. To address this concern, systems involving out-of-pocket health payments (OHP) have been introduced, and their importance has steadily grown in many countries [1,3]. Health care services are commonly financed through a combination of taxation, social health insurance, private health insurance, community financing, and OHP [4,5].
OHP may combat the phenomenon known as “moral hazard,” whereby households might use less necessary or unnecessary health services too frequently when they are free of charge, whereas household contributions could reduce this. OHP can also serve as a source of health care financing [1,6]. One way to measure fairness in health care financing is by analyzing OHP [7]. A high proportion of OHP can be considered a threat to a health care financing system, since relying on a high-risk source can limit the availability of health services for epidemics or life changes such as aging. While OHP overall is an issue that requires more attention, studying OHP inequality is the more critical aspect, because an unequal distribution of OHP can divert family income away from essential needs such as food, education, shelter, and utilities [810]. Numerous studies have calculated inequality in well-being indicators such as income, wealth and consumption, or various indicators of health, such as access to services [11]. In Iran, OHP is a major source of health care financing [5,12,13], and evidence shows that health care expenditures have been increasing over the decades [1416].
Inequality in OHP has become an increasing health policy challenge for many countries [17,18]. The health care system in Iran was formed from the principles of the Conference of Alma Ata, namely access to health services for all, a focus on primary care and prevention, attention to disadvantaged groups, and investments in public health workers. The system is a public/private partnership, with the public health sector funded by public expenditures, including direct government spending, and reimbursement from the Iranian Social Security Organization and Health Insurance Organization [19]. In 2018, health system funding in Iran consisted of government expenditures (about 24%), social health insurance (about 31%), direct OHP (about 35%), private health insurance (about 6%), and other sources (about 4%), with health care expenditures accounting for 8.4% of Iran’s gross domestic product [20].
Indicators of inequality in health expenditures have been widely studied by Iranian researchers, but this study is the first to address the issue comprehensively over a 36-year timeframe [5,21]. Mehrolhassani et al. [22] reported that the distribution of health care expenditures was unequal, especially in OHP, with the highest rate ranging from 0.50 to 0.59 during the study timeframe and the disparity index for OHP fluctuating between 37.01% and 65.85%. Bock et al. [1] reported a mean OHP over three months of €119, with 34% for medical supplies, 22% for dental prostheses, 21% for pharmaceuticals, 17% for outpatient physician and non-physician services, 5% for inpatient care, and 1% for nursing care. In Iran, there is some limited evidence on inequality trends in health care expenditures, particularly Ghaedamini et al. [23] who studied inequality in Iranian household expenditures over a decade. The Gini coefficient (GC) in their study was unusually high for health care expenditures, averaging 0.78. The current study uses the GC as well but has also added two more refined indicators of inequality, the Theil and Atkinson indexes. These incorporate additional qualitative criteria such as inequality aversion and entropy when calculating inequality indexes [24]. This study also considered inequality in OHP among different socio-demographic subgroups. The findings, therefore, make a significant contribution to the understanding of health inequalities and provide valuable input for policymakers in Iran aiming to ensure more equity in health care. In summary, this study measured the trends in inequality indexes for Iranian household OHP over 36 years, and further analyzed this inequality based on household income ranges and insurance coverage status.

METHODS

Data

This study used data from the Household Income and Expenditure Survey gathered annually by the Statistical Center of Iran. The analysis included a total of 995 300 households over the 36 years from 1984 to 2019. Among Iranian households, OHP (also referred to as out-of-pocket expenditures or co-payments) are paid in 1 of 3 ways: deductibles, or amounts paid for covered health care expenditures before insurance starts paying, additional payments triggered when a stipulated insurance threshold is reached, and direct contributions to health care services, including for outpatient diagnostic services, equipment, supplies, medical assistant accessories, hospital inpatient service, and addiction cessation [25]. This study used Stata version 14.2 (StataCorp., College Station, TX, USA) to analyze the data, with the INEQDECO Stata module used to estimate the full range of inequality indexes [26].

Measures

Inequality in household expenditures was measured using 3 different indicators: the GC, the Theil index of inequality (with its sensitivity to disparities at the top and the bottom of the OHP distribution), and the Atkinson index of inequality (with 2 parameters for inequality aversion).
The GC has many desirable characteristics as a measure of inequality, including mean and population size independence symmetry and Pigou-Dalton transfer sensitivity. The GC ranges from 0 to 1, where 0 indicates perfect equality (all individuals have the same resources) and 1 indicates perfect inequality (where one person has all the resources and the rest have none). The closer the GC is to 1, therefore, the more unequal the population and vice-versa. Focusing on the GC as a measure of inequality allows comparisons of inequalities in health care expenditures over time and space [27]. Its cumulative frequency curve compares the distribution of total health care expenditures yi with the cumulative percentage of population xi. The GC was calculated using the formula [27,28] of Haughton as shown in equation (1):
(1)
GC=1-i=1N(xi-xi-1)(yi+yi-1)
where N is the total number of observations. If N is equal to the interval on the x-axis, the GC can be simplified to equation (2):
(2)
GC=1-i=1N(yi+yi-1)
The Atkinson index shows the percentage of total resources that a population would have to forego in order to have more equal shares of income between the individuals. Atkinson (1970) approached inequality from a normative perspective and proposed welfare-based inequality measures called Atkinson’s class measures A(ɛ). The parameter(ɛ) represents aversion to inequality and has values between zero and infinity. The larger the parameter(ɛ), the stronger the inequality aversion in a society. This means that the Atkinson index is more sensitive to the bottom of the income/expenditure distribution [29]. A greater aversion parameter(ɛ) indicates that social welfare is more sensitive to a shift in the income of a poorer individual than to the same shift for a richer individual [30].
(3)
Aε=1-i=1N(yi(1N))y¯ε=1
(4)
Aε=1-[1ni=1nyiy¯1-ε]11-εμε1
The Theil index was also calculated for OHP among Iranian households. The Theil index is a generalized entropy inequality measure, GE(ɲ). The parameter ɲ represents the weight given to distances between income/expenditure at different parts of the income/expenditure distribution. The parameter ɲ can take any real value, with commonly used values of 0, 1, and 2. When ɲ is equal to 0, the GE(0) index is called the Theil L index, when ɲ is equal to 1, the GE(1) index is called the Theil T index, and when ɲ is equal to 2, the GE(2) index is called the coefficient of variation [31]. With a large and positive ɲ, the GE index is more sensitive to changes at the upper tail of the income/expenditure distribution, while with ɲ values closer to zero, the GE index is more sensitive to changes at the bottom tail of the distribution.
(5)
E(a)=1n(a2-a)i[(yiy¯)a-1]
(6)
E(1)=T=1ni=1n(yiy)ln(yiy¯)

Ethics Statement

This research was in accordance with the ethical standards of the Committee of Ethics in Research in the University of Social Welfare and Rehabilitation Sciences and approved by ethical code: IR. USWRREC.1398.201.

RESULTS

Profile of Iranian Households

Historically, the heads of most Iranian households have been men (around 90%), while more recently there has been a slight increase in women-headed households (from 10.1% in 1984 to 14.3% in 2019). During this period, the rate of insurance coverage also increased rapidly from 26.6% in 1984 to 88.8% in 2019. The proportions of urban and rural households during this time were consistent, with only slight fluctuations. The literacy rate for heads of households increased considerably from 51.0% in 1984 to 75.5% in 2019. Household size has also dropped over the years, from an average of 5.1 persons per household in 1994 to 3.4 in 2019. Since 2011, health care expenditures have grown at least 12% year over year (Tables 1 and 2).

Inequality in Out-of-pocket Health Payments

Using the annual data on Iranian household health expenditures, inequality indexes were calculated over the 36 years. All inequality measures showed inequality slowly declining from 1984 to 2019. The one exception was 2010, when all the measures suddenly dropped. Inequality in OHP then remained mostly constant until 2019. During this period, the mean±standard deviation (SD) of the GC was 0.73±0.04, with a minimum and maximum of 0.65 and 0.78 in the years 2011 and 1988, respectively. The mean±SD of the Atkinson index for inequality among Iranian households was A(0.5)=0.46±0.06. Focusing on the OHP of the lowest income group, the Atkinson index is higher with the mean A(1)=0.68±0.05. Similarly, Figure 1 shows the trends for the Thiel index of inequality using the inequality aversion parameters 1 and 0. Over the 36-year period, the average for GE(1) and GE(0) was 1.39±0.29 and 1.14±0.14, respectively. It is clear that more sensitivity to inequalities at the top of the OHP distribution has led to higher levels of inequality. This is evidenced by the fact that inequality was much more pronounced among households with higher OHP. In 2010 the inequality converged for both inequality aversion parameters, most likely indicating that households with better economic conditions were less able to meet their health needs.
Figure 2 shows the inequality trend in OHP among sample subgroups (note that data for expenditures on addiction cessation are only available for 2005 onward). The mean of the GCs for expenditures on equipment, supplies, and medical assistant accessories was 0.61±0.02, suggesting it was the least important factor measured here affecting inequality in health care expenditures. The mean of the GC for outpatient diagnostic services expenditures was 0.70±0.01, with the coefficient at its highest level in 1995 (0.74). Among all the components of OHP, hospital services expenditures had the highest level of inequality (0.84±0.08). Inequality in expenditures for addiction cessation, despite a few peturbations, was almost constant.
The mean GCs were 0.74±0.05 for households covered by insurance and 0.71±0.04 for those without insurance coverage (Table 3). The trend of inequality had slight fluctuations before 2011, but in 2011 it dropped significantly, and inequality between the 2 groups of households has since converged. Table 3 also gives the GCs for different income deciles, to help understand differences in inequality between households with different income levels. The OHP was highly unequal in the topmost decile subgroup, with a mean GC for 1984 to 2019 of 0.75±0.05. All deciles showed decreased inequality in 2011, with the mean of GCs for the bottom decile (first) of 0.70±0.06.

DISCUSSION

This study calculated inequality measures in OHP among Iranian households over 36 years and provided a breakdown of inequality trends. All inequality indicators showed slightly decreases in OHP inequality in line with previous studies [16,31]. A similar trend of declining inequality in health spending has been reported in some other countries. According to Çinaroğlu [32], GC results indicated decreasing inequality in OHP expenditures between 2003 (0.75), 2009 (0.71), and 2015 (0.69). The level of progressivity decreased from 2003 to 2015, with less progressivity in distribution of OHP expenditures [32].
The highest inequality has been detected in hospital services expenditures (Figure 2), with outpatient diagnostic services and equipment and medical supplies showing a relatively smooth trend over the 36 years. Ghaedamini et al. [23] showed that Iranian households experienced severe inequality in health care expenditures. The present study found that the highest level of inequality was among households with insurance coverage as well as households in the tenth income decile. More access to health care services, often facilitated by insurance coverage and high income, appeared to be an important factor in this higher inequality in health care spending.
To understand the overall status of inequality in health care expenditures, all the observed trends should be analyzed simultaneously. In 2011 there was a sudden and significant decline in all measures of inequality. The Theil index showed that an important part of this reduction in inequality was related to households with higher health expenditures. This analysis has also shown that inequality in hospital spending has decreased significantly. It appears that households with insurance coverage and higher incomes have become more similar in terms of inequality to households without insurance coverage and with lower incomes. Households that used to experience higher inequality in health care expenditures, namely high-income and insurance-covered households, are now experiencing declining inequality. Reduced household spending inequality should be distributed unequally because of unequal health needs. The observed reductions, however, may be a result of limited access to health care services, especially expensive hospital services. In 2011, the Iranian economy experienced a shock in foreign exchange rates that destroyed the purchasing power of Iranian households. This sharp decline in real incomes has made health care services more unaffordable for families [33] especially for those with extensive needs, such as people with disabilities and families with other specialized needs. According to Rezapour et al. [34], economic problems are making patients less likely to seek out medical services, with Kordbache and Ahmadi [35] showing that the exchange rate has significant and direct impacts on medical care prices both in the short and long term. They showed effects of exchange rate changes on medical care price indexes for consumers and producers of 0.23 and 0.14 in the short term and 0.327 and 0.256 in the long term, respectively. Atkinson index values show the proportion of total OHP which would be required to achieve an level of social welfare equal to the present state if expenditures were perfectly distributed. The mean Atkinson index values of A(0.5)= 0.46 and A(1)=0.68 suggest that Iran’s health system could achieve the same level of social welfare with only 1−0.46=0.54 and 1−0.68=0.32 the amount of current OHP. In the last decade, the “target subsidies plan” was implemented in Iran with the aim of reducing government subsidies in the economy. This plan started in 2010 and sought to expand government funding for social insurance and health care services, as well as affordable medical care for specific diseases. The high inflationary effects of this policy [36], however, worsened the inequality in health care financing and made access to health care services more limited than before. Reducing the inequality in household OHP was considered auspicious in previous study [37], but the current study showed that high inequality in health spending was related to affluent families (households with insurance coverage and high-income households) in society. As a result, inequality should be interpreted cautiously in counties with high OHP shares in health care expenditures.
This study used a large raw data set from Iranian households to calculate inequality indexes. The measures of inequality included the GC and the Theil and Atkinson indexes. For the first time, a long-term trend of for inequality was established and analyzed based on households’ income decile and insurance coverage status. The data suggest that implementation of the “targeted subsidies plan” and the following exchange rate shock has reduced inequality in OHP since 2011. The higher inequality rates seen for households with higher socioeconomic status suggest that lowering inequality in Iran may have been due to limited access to health care services. The trend of inequality indexes as well as more detailed analysis of the 36 years of data reinforce this viewpoint. A significant reduction in the inequality of hospital services’ expenditures, for example, suggests that some households in need of expensive medical services may have been deprived of these services, possibly with devastating health consequences. This study provides a time series of data that can be used for further health inequality analysis.

CONFLICT OF INTEREST

The authors have no conflicts of interest associated with the material presented in this paper.

Notes

FUNDING
None.

ACKNOWLEDGEMENTS

Authors acknowledge the Research Deputy of the University of Social Welfare and Rehabilitation Sciences for their support in providing scientific resources.

Notes

AUTHOR CONTRIBUTIONS
Conceptualization: Aghapour E, Basakha M. Data curation: Aghapour E, Basakha M. Formal analysis: Aghapour E, Basakha M, Mohaqeqi Kamal SH. Funding acquisition: None. Methodology: Aghapour E, Basakha M, Pourreza A. Project administration: Basakha M. Writing – original draft: Aghapour E, Basakha M. Writing – review & editing: Aghapour E, Basakha M, Mohaqeqi Kamal SH, Pourreza A.

Figure 1
Inequality indexes for Iranian households’ out-of-pocket health payment (1984–2019).
jpmph-22-123f1.jpg
Figure 2
Trends in the Gini coefficients for coefficients of out-of-pocket health payment expenditures (1984–2019).
jpmph-22-123f2.jpg
Table 1
Summary statistics of Iranian households’ income and health care expenditures
Year Total population Family size, n Average household income Average health care expenditure Average per capita health care expenditure Insurance coverage, % Growth rate of health care expenditures



IRR USD IRR USD IRR USD
1984 45 814.000 5.1 44 304 482 3036 33 595 6 26.3 0.12
1985 47 606.000 5.0 43 723 497 3046 35 609 7 25.2
1986 49 445.000 5.1 35 380 459 3011 39 590 8 24.3
1987 50 661.000 5.2 51 988 743 3807 54 732 78 25.7
1988 51 908.000 5.3 62 509 906 4222 61 797 10 25.1
1989 53 185.000 5.3 73 013 1014 4741 66 894 12 23.0
1990 54 493.000 5.6 91 012 1360 5345 80 954 14 24.8
1991 55 837.000 5.6 124 586 1838 7588 112 1355 10 25.2

1992 56 658.000 5.3 167 670 115 10 588 7 1998 2 26.6 0.32
1993 57 491.000 5.3 203 170 123 11 870 7 2240 2 29.0
1994 58 336.000 5.4 290 237 166 20 750 12 3843 3 36.1
1995 59 193.000 5.4 361 812 207 27 269 16 5050 2 37.2
1996 60 055.000 5.2 483 854 276 33 223 19 6389 4 35.4
1997 61 070.000 5.1 599 723 342 40 570 23 7955 5 39.4
1998 62 103.000 5.0 736 224 420 49 467 28 9893 6 37.1
1999 63 152.000 5.1 859 810 490 65 923 38 12 926 7 37.3
2000 64 219.000 4.9 1 001 739 571 80 099 46 16 347 9 37.0
2001 65 301.000 4.9 1 177 110 671 97 268 55 19 851 11 37.1

2002 66 300.000 4.8 1 499 351 188 125 927 16 26 235 3 28.3 0.60
2003 67 315.000 4.7 1 901 900 230 139 913 17 29 769 4 40.4
2004 68 345.000 4.6 2 342 928 269 192 559 22 41 861 5 35.4
2005 9390.000 4.4 2 702 105 299 219 936 24 49 985 6 41.5
2006 70 496.000 4.3 3 117 117 339 245 596 27 57 115 6 68.1
2007 71 346.000 4.2 3 639 840 392 294 092 32 70 022 8 64.7
2008 72 279.000 4.1 3 781 924 395 365 673 38 89 189 9 75.1
2009 73 223.000 4.0 4 172 805 421 426 953 43 106 738 11 77.4
2010 74 180.000 3.9 4 780 635 462 523 352 51 134 193 13 77.3
2011 75 150.000 3.9 6 474 853 591 517 923 47 132 801 12 78.8

2012 76 082.000 3.8 8 108 269 661 646 568 53 170 149 14 80.8 0.15
2013 77 025.000 3.7 9 639 775 454 843 979 40 228 102 11 81.2
2014 77 980.000 3.7 11 344 847 528 917 977 35 248 102 9 81.7
2015 78 947.000 3.7 13 068 728 442 1 014 362 34 274 152 9 87.4
2016 79 926.000 3.6 14 566 771 464 1 115 497 36 309 860 10 88.7
2017 81 150.000 3.5 16 672 478 487 1 359 098 40 388 314 11 88.9
2018 82 200.000 3.5 20 824 220 496 1 874 602 45 535 601 13 87.5
2019 83 100.000 3.4 24 250 814 577 1 982 000 47 582 941 14 88.8

IRR, Iranian rial; USD, US dollar.

Table 2
Average income and insurance coverage based among income deciles
Year Variable Income deciles

1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th
1984 Insurance coverage status
 Not covered 77.9 94.3 93.6 87.3 85 75.2 65 55.5 48.3 51.7
 Covered 22.1 5.7 6.4 12.7 15 24.8 35 44.5 51.7 48.3
Average income
 IRR 294 4935 12 672 20 887 29 344 38 138 47 895 60 182 78 537 150 414
 USD 3 54 138 227 319 415 521 654 854 1635

1991 Insurance coverage status
 Not covered 98.4 96.1 88.6 83.3 73.9 64.3 58.4 56.9 61.2 67.1
 Covered 1.6 3.9 11.4 16.7 26.1 35.7 41.6 43.1 38.8 32.9
Average income
 IRR 11 942 23 997 45 306 63 363 80 010 97 771 118 710 147 863 195 788 485 319
 USD 176 354 668 935 1180 1442 1751 2181 2888 7158

2001 Insurance coverage status
 Not covered 85.1 89.5 82.8 72.7 62.9 53.9 48.2 45.5 41.6 47.1
 Covered 14.9 10.5 17.2 27.3 37.1 46.4 51.8 54.5 58.4 52.9
Average income
 IRR 117 667 327 331 485 204 633 371 786 131 960 988 1 174 255 1 460 254 1 921 026 3 907 941
 USD 67 187 276 361 448 548 669 832 1095 2227

2011 Insurance coverage status
 Not covered 30.6 27.4 26 25.9 23.29 19.7 17.7 15.5 13.8 12
 Covered 69.4 72.6 74 74.1 76.8 80.3 82.3 84.5 86.2 88
Average income
 IRR 1 032 514 2 482 310 3 522 558 4 366 017 5 134 680 5 940 038 6 884 306 8 115 208 10 103 478 17 179 676
 USD 94 226 321 398 468 541 628 740 922 1567

2019 Insurance coverage status
 Not covered 17.5 14 12.6 12 9.8 11.8 9.5 8.9 8.4 7.2
 Covered 82.5 86 87.4 88 90.2 88.2 90.5 91.1 91.6 92.8
Average income
 IRR 3 500 858 8 454 445 12 192 852 15 399 604 18 315 671 21 644 567 25 794 321 31 081 806 38 882 903 67 303 983
 USD 834 2012 2903 3666 4360 5153 6141 7400 9258 16 024

IRR, Iranian rial; USD, US dollar.

Table 3
Gini coefficient (decomposed), Theil index, and Atkinson index of inequality
Year Gini coefficient Theil index Atkinson index

OHP Health care expenditures sub-categories Insurance status Income decile





Medical accessories Outpatient services Hospital service Quitting addiction Covered Not covered 1st 5th 10th GE(0) GE(1) A(0.5) A(1)
1984 0.76 0.59 0.71 0.93 - 0.78 0.75 0.74 0.73 0.80 1.39 1.57 0.52 0.75

1985 0.74 0.59 0.68 0.91 - 0.77 0.73 0.76 0.65 0.78 1.28 1.45 0.49 0.72

1986 0.72 0.57 0.68 0.90 - 0.78 0.68 0.76 0.73 0.76 1.09 1.29 0.45 0.66

1987 0.75 0.59 0.68 0.92 - 0.80 0.73 0.62 0.66 0.80 1.23 1.62 0.50 0.71

1988 0.79 0.60 0.70 0.93 - 0.80 0.78 0.82 0.82 0.73 1.39 1.79 0.55 0.75

1989 0.76 0.61 0.70 0.92 - 0.78 0.68 0.79 0.67 0.78 1.26 1.62 0.51 0.72

1990 0.74 0.61 0.69 0.91 - 0.76 0.74 0.75 0.73 0.74 1.19 1.47 0.49 0.70

1991 0.78 0.60 0.69 0.92 - 0.81 0.77 0.75 0.69 0.80 1.33 1.84 0.54 0.73

1992 0.78 0.60 0.70 0.92 - 0.82 0.77 0.75 0.77 0.84 1.34 1.87 0.55 0.74

1993 0.75 0.59 0.71 0.89 - 0.77 0.74 0.72 0.71 0.76 1.17 1.53 0.49 0.69

1994 0.76 0.65 0.73 0.88 - 0.77 0.75 0.77 0.73 0.78 1.21 1.59 0.50 0.70

1995 0.76 0.61 0.74 0.88 - 0.77 0.75 0.77 0.74 0.76 1.21 1.55 0.50 0.70

1996 0.76 0.62 0.74 0.87 - 0.78 0.75 0.75 0.72 0.79 1.21 1.57 0.50 0.70

1997 0.75 0.60 0.72 0.85 - 0.78 0.74 0.73 0.71 0.80 1.21 1.64 0.51 0.70

1998 0.74 0.62 0.73 0.81 - 0.76 0.74 0.77 0.73 0.74 1.17 1.42 0.48 0.69

1999 0.75 0.60 0.71 0.83 - 0.78 0.73 0.73 0.71 0.78 1.20 1.56 0.50 0.70

2000 0.74 0.58 0.70 0.82 - 0.75 0.73 0.69 0.68 0.78 1.14 1.52 0.48 0.68

2001 0.75 0.58 0.70 0.81 - 0.75 0.74 0.74 0.70 0.80 1.17 1.62 0.49 0.69

2002 0.73 0.60 0.69 0.83 - 0.75 0.72 0.69 0.69 0.78 1.12 1.44 0.47 0.67

2003 0.71 0.61 0.67 0.80 - 0.72 0.69 0.65 0.65 0.74 1.03 1.28 0.44 0.64

2004 0.75 0.60 0.70 0.87 - 0.77 0.74 0.71 0.68 0.75 1.21 1.61 0.50 0.70

2005 0.74 0.63 0.70 0.86 0.58 0.75 0.72 0.71 0.72 0.75 1.17 1.47 0.48 0.69

2006 0.74 0.63 0.69 0.86 0.52 0.75 0.71 0.72 0.73 0.76 1.16 1.41 0.47 0.69

2007 0.75 0.64 0.70 0.88 0.50 0.76 0.71 0.68 0.71 0.82 1.20 1.65 0.50 0.70

2008 0.74 0.66 0.69 0.88 0.46 0.75 0.72 0.70 0.69 0.78 1.18 1.51 0.48 0.69

2009 0.73 0.63 0.68 0.88 0.46 0.72 0.76 0.69 0.71 0.74 1.13 1.48 0.47 0.68

2010 0.73 0.63 0.69 0.88 0.53 0.73 0.72 0.69 0.72 0.74 1.11 1.37 0.46 0.67

2011 0.65 0.63 0.68 0.74 0.59 0.65 0.64 0.63 0.65 0.67 0.88 0.90 0.36 0.59

2012 0.66 0.63 0.69 0.75 0.36 0.66 0.66 0.62 0.68 0.68 0.91 0.97 0.37 0.60

2013 0.66 0.62 0.69 0.73 0.44 0.66 0.67 0.62 0.63 0.68 0.89 0.92 0.36 0.59

2014 0.66 0.61 0.69 0.67 0.63 0.66 0.66 0.65 0.63 0.68 0.90 0.90 0.36 0.59

2015 0.67 0.62 0.69 0.69 0.37 0.67 0.66 0.62 0.65 0.67 0.95 0.91 0.37 0.61

2016 0.68 0.62 0.71 0.72 0.57 0.68 0.67 0.63 0.65 0.69 0.99 0.96 0.39 0.63

2017 0.66 0.62 0.70 0.68 0.48 0.67 0.65 0.60 0.63 0.67 0.96 0.90 0.37 0.62

2018 0.67 0.62 0.72 0.70 0.64 0.68 0.65 0.69 0.64 0.67 1.00 0.98 0.39 0.63

2019 0.67 0.62 0.72 0.69 0.54 0.67 0.66 0.63 0.65 0.68 0.97 0.97 0.38 0.62

OHP, out-of-pocket health payment.

REFERENCES

1. Bock JO, Matschinger H, Brenner H, Wild B, Haefeli WE, Quinzler R, et al. Inequalities in out-of-pocket payments for health care services among elderly Germans--results of a population-based cross-sectional study. Int J Equity Health 2014;13: 3.
crossref pmid pmc
2. Organization for Economic Cooperation and Development (OECD). Health data. 2022. [cited 2022 Mar 5]. Available from: http://www.oecd.org/health/healthdata .

3. Tambor M, Pavlova M, Woch P, Groot W. Diversity and dynamics of patient cost-sharing for physicians’ and hospital services in the 27 European Union countries. Eur J Public Health 2011;21(5):585-590.
crossref pmid
4. Gottret P, Schieber G. Health financing revisited: a practitioner’s guide. 2006. [cited 2021 Oct 17]. Available from: https://openknowledge.worldbank.org/handle/10986/7094 .

5. Rezaei S, Woldemichael A, Ebrahimi M, Ahmadi S. Trend and status of out-of-pocket payments for healthcare in Iran: equity and catastrophic effect. J Egypt Public Health Assoc 2020;95(1):29.
crossref pmid pmc pdf
6. Corrieri S, Heider D, Matschinger H, Lehnert T, Raum E, König HH. Income-, education- and gender-related inequalities in out-of-pocket health-care payments for 65+ patients - a systematic review. Int J Equity Health 2010;9: 20.
crossref pmid pmc
7. Pourasghari H, Jafari M, Bakhtiari M, Keliddar I, Irani A, Afshari M. Analysis of equality in Iranian household healthcare payments during Iran’s fourth development program. Electron Physician 2016;8(7):2645-2649.
crossref pmid pmc
8. Ekholuenetale M, Barrow A. Inequalities in out-of-pocket health expenditure among women of reproductive age: after-effects of national health insurance scheme initiation in Ghana. J Egypt Public Health Assoc 2021;96(1):6.
crossref pmid pmc pdf
9. Akazili J, McIntyre D, Kanmiki EW, Gyapong J, Oduro A, Sankoh O, et al. Assessing the catastrophic effects of out-of-pocket healthcare payments prior to the uptake of a nationwide health insurance scheme in Ghana. Glob Health Action 2017;10(1):1289735.
crossref pmid pmc pdf
10. Kanmiki EW, Bawah AA, Phillips JF, Awoonor-Williams JK, Kachur SP, Asuming PO, et al. Out-of-pocket payment for primary healthcare in the era of national health insurance: evidence from northern Ghana. PLoS One 2019;14(8):e0221146.
crossref pmid pmc
11. O’Donnell O, van Doorslaer E, Wagstaff A, Lindelow M. Analyzing health equity using household survey data: a guide to techniques and their implementation. 2008. [cited 2021 Oct 17]. Available from: https://openknowledge.worldbank.org/handle/10986/6896 .

12. Chu A, Kwon S, Cowley P. Health financing reforms for moving towards universal health coverage in the Western Pacific Region. Health Syst Reform 2019;5(1):32-47.
crossref pmid
13. Fakhri MA, Juni MH, Rosliza AM. Assesing progressivity of out-of-pocket expenditures for health care: evidence from households in Malaysia. Int J Public Health Clin Sci 2019;6(3):187-202.

14. Hajimahmoudi H, Zahedi F. Justice in the healthcare system: payment and reimbursement policies in Iran. Iran J Med Ethics Hist Med 2014;6(3):1-16 (Persian).

15. Abolhallaje M, Mousavi SM, Jafari M. Implementation of performance-based budgeting in the health system: luxury or necessity? Iran J Public Health 2014;43(11):1593-1594.
pmid pmc
16. Hajimahmoudi H, Zahedi F. Justice in the healthcare system: payment and reimbursement policies in Iran. Iran J Med Ethics Hist Med 2013;6(3):1-16 (Persian).
pmid
17. Murray CJ, Knaul F, Musgrove P, Xu K, Kawabata K. Defining and measuring fairness in financial contribution to the health system. GPE Discussion Paper Series: No. 24. 2000. [cited 2021 Dec 12]. Available from: https://apps.who.int/iris/handle/10665/68706 .

18. Jafari M, Bastani P, Ibrahimipour H, Dehnavieh R. Attitude of health information system managers and officials of the hospitals regarding the role of information technology in reengineering the business procedures: a qualitative study. HealthMED 2012;6(1):208-215.

19. Bazyar M, Rashidian A, Alipouri Sakha M, Vaez Mahdavi MR, Doshmangir L. Combining health insurance funds in a fragmented context: what kind of challenges should be considered? BMC Health Serv Res 2020;20(1):26.
crossref pmid pmc pdf
20. Doshmangir L, Rashidian A, Kouhi F, Gordeev VS. Setting health care services tariffs in Iran: half a century quest for a window of opportunity. Int J Equity Health 2020;19(1):112.
crossref pmid pmc pdf
21. Jalali FS, Jafari A, Bayati M, Bastani P, Ravangard R. Equity in healthcare financing: a case of Iran. Int J Equity Health 2019;18(1):92.
crossref pmid pmc pdf
22. Mehrolhassani MH, Yazdi-Feyzabadi V, Lashkari M. Measuring inequalities in the selected indicators of National Health Accounts from 2008 to 2016: evidence from Iran. Cost Eff Resour Alloc 2020;18: 37.
crossref pmid pmc pdf
23. Ghaedamini GH, Sharifian Sani M, Raghfar H, Salehi M. Inequality trend of selected items of consumption household basket in Tehran: 1989–2006. Soc Welf Q 2011;11(40):315-339 (Persian).

24. Kawachi I, Subramanian SV, Almeida-Filho N. A glossary for health inequalities. J Epidemiol Community Health 2002;56(9):647-652.
crossref pmid pmc
25. Statistical Center of Iran. Household, Expenditure and Income Survey. 2022. [cited 2021 Jun 6]. Available from: https://www.amar.org.ir/english/Statistics-by-Topic/Household-Expenditure-and-Income#2220530-releases .

26. Jenkins SP. INEQDECO: Stata module to calculate inequality indices with decomposition by subgroup. 2001. [cited 2021 Feb 22]. Available from: https://ideas.repec.org/c/boc/bocode/s366007.html .

27. Haughton J, Khandker SR. Handbook on poverty and inequality. 2009. [cited 2021 Oct 12]. Available from: https://openknowledge.worldbank.org/handle/10986/11985 .

28. Raghfar H, Zargari N, Sangari MK. Measuring inequality in households’ health care expenditures in Iran. Hakim Res J 2013;16(2):89-97 (Persian).

29. Statistics South Africa. Inequality trends in South Africa: a multidimensional diagnostic of inequality. 2019. [cited 2021 Oct 12]. Available from: http://www.statssa.gov.za/publications/Report-03-10-19/Report-03-10-192017.pdf .

30. Tregenna F, Tsela M. Inequality in South Africa: the distribution of income, expenditure and earnings. Dev South Afr 2012;29(1):35-61.
crossref
31. Ghiasvand H, Naghdi S, Abolhassani N, Shaarbafchizadeh N, Moghri J. Iranian households’ payments on food and health out-of-pocket expenditures: evidence of inequality. Iran J Public Health 2015;44(8):1103-1113.
pmid pmc
32. Çinaroğlu S. Inequality and inequity in financing out-of-pocket health expenditures: an applied econometric approach. J Bus Res Turk 2018;10(1):876-897.

33. Zandian H, Takian A, Rashidian A, Bayati M, Zahirian Moghadam T, Rezaei S, et al. Effects of Iranian economic reforms on equity in social and healthcare financing: a segmented regression analysis. J Prev Med Public Health 2018;51(2):83-91.
crossref pmid pmc pdf
34. Rezapour A, Mahmoudi M, Gorji HA, Faradonbeh SB, Asadi S, Zadeh NY, et al. A survey of Unmet health needs and the related barriers to access them. J Health Adm 2014;17(57):87-98 (Persian).

35. Kordbache H, Ahmadi Z. Evaluation the effect of exchange rate fluctuations on medical care price indexes in Iran. J Healthc Manag 2018;8(4):17-27 (Persian).

36. Noferesti M, Jalouli M. Analyzing the impact of the removal of basic commodity subsidies on the main macroeconomic variables within a structural macro econometric framework. J Econ Model 2010;1(1):81-105 (Persian).

37. Jalali FS, Jafari A, Bayati M, Bastani P, Ravangard R. Equity in healthcare financing: a case of Iran. Int J Equity Health 2019;18(1):92.
crossref pmid pmc pdf
Editorial Office
#203, 92 Wangsan-ro, Dongdaemun-gu, Seoul 02585, Korea
Tel : +82-2-740-8328   Fax : +82-2-764-8328   E-mail: jpmph@prevmed.or.kr
About |  Browse Articles |  Current Issue |  For Authors and Reviewers
Copyright © 2022 by Korean Society for Preventive Medicine.                 Developed in M2PI