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International Journal for Equity in Health logoLink to International Journal for Equity in Health
. 2015 Jan 8;14:1. doi: 10.1186/s12939-014-0131-1

How the government intervention affects the distribution of physicians in Turkey between 1965 and 2000

Erdinç Ünal 1,
PMCID: PMC4307150  PMID: 25566790

Abstract

Introduction

One of the main weaknesses of the health system in Turkey is the uneven distribution of physicians. The diversity among geographical districts was huge in the beginning of the 1960s. After the 1980s, the implementation of a two-year compulsory service for newly graduated physicians is an interesting and specific experience for all countries. The aim of this study is to analyse the distribution of physicians, GPs and specialists between the years 1965-2000 and the efficiency of the strict 15 year government intervention (1981-1995).

Methods

The data used in this study includes the published data by the Ministry of Health and The State Institute of Statistics between the years 1965–2000. Covering 35 years for total physicians, GPs and specialists, Gini coefficients are calculated so as to observe the change in the distribution. In order to measure the efficiency of government intervention, Gini index belonging to the previous 15 years (first period-1965 to 1980) and the last 15 years (second period) of 1981 when the compulsory service was enacted is also analysed including the statistical tests.

Results

In 1965, the Gini for total physician is quite high (0.47), and in 2000 it decreases considerably (0.20). In 1965, the Gini for GPs and the Gini for specialists is 0.44 and 0.52, respectively and in 2000 these values decrease to 0.13 and 0.28, respectively. It is observed that, with this government intervention, the level of diversity has decreased dramatically up to 2000. Regarding to regression, the rate of decrease in Gini index in the second period is higher for the GPs than that of the specialists.

Conclusion

The inequalities in the distribution between GPs and specialists are significantly different; inequality of specialist distribution is higher than the GP. The improvement of the inequality in the physician distribution produced by the market mechanism shows a long period when it is left to its own devices. It is seen that the compulsory service policy is efficient since the physician distribution has improved significantly. The government intervention provides a faster improvement in the GP distribution.

Keywords: Distribution of physicians, Government intervention on health, Compulsory service for physicians

Introduction

The unequal distribution of physicians is a fact seen almost all over the world. The distribution of human resources in health care has been recognised as one of the most important issues for the evaluation of persistent inequities. This problem is not peculiar to Turkey and could be seen throughout the world as well [1-4]. Any differences in the distribution of health care personnel density are seen in various regions of all countries. But these differences are also seen in the cities of each region and, moreover, they are also encountered in the surrounding areas and suburbs of each metropolis [5].

The inequality in distribution of physicians was generally higher than other health human resources [6]. To provide a fair distribution of physicians between developed urban areas and underdeveloped rural areas has been a continuous effort of the decision-makers of health policy and practitioners of national health policy in almost all countries. Planning the geographical distribution of physicians has been one of the most important policy implications. Similar to many countries, the problem of arranging the distribution of physicians with the aim of meeting the needs of national health organisation and the public demand have always been on the agenda of the Turkish governments.

Health services and market failures

Health services used to advance out of the market mechanism in many ways throughout the world. The motivations and mechanism of the market cannot provide a socially efficient production and a fair distribution of the health services. This means the failure of efficiency and equity, both of which are expected from an every economic activity, and the situation that arises when these two concepts do not happen as expected is the basic subject of market failures.

Due to the increase in the demand for healthcare in big cities, employing a greater number of physicians is an expected case. Demand is not the sole reason of physician density in big and developed cities/regions.a The factors affecting the physician distribution are divided into four categories: (1) supportive facilities; (2) socioeconomic and demographic characteristics of an area; (3) socio-cultural considerations; and (4) need for medical services [7,8].

The market failure argument about the physician distribution is related to the intensive distribution of physicians in more advantaged areas. Even though the regions and cities that could be called more advantaged than others reach a saturation point in regard to the number of physicians, the market failure continues to exist. Cities and developed regions in developing countries especially continue to absorb newly graduated physicians due to an inadequate supply of physicians. Another factor valid for both developing and developed countries is the increasing demand for new medical services in developed regions and cities. Of course, physicians don’t have the ability to create demand unlimitedly, but they could face a loss of income to a certain extent. Even in these conditions, they prefer living in large cities and socioeconomically developed urban areas.

“The quantitative evidence supporting the case for market failure usually takes two forms: (1) At each point in time, physician/population ratios in nonmetropolitan counties are markedly lower than those in metropolitan counties. (2) Over time, physician/population ratios in small towns or counties have risen more slowly than those in metropolitan areas” [9].

In their studies, Newhouse et al. [10], consider the total population as a critical factor in the distribution of physicians since they prefer the areas with a higher population to have sufficient demand. Besides, they not only seek to maximize their profits but also to increase the quality of their social life profile, non-cash benefits and access to the medical facilities [3,8].

The distribution of health labour power in the population and geography is an important element in terms of reproducibility and availability of health services. Physician supply is the most important element for equitability in access to medical care. Intervention of the government appears where there is an unbalanced physician distribution. Taking measures in regard to a balanced physician distribution will improve the allocation of human resources in health system [11]. On the other hand, the medical staffs, especially physicians, prefer living in socially and economically developed cities, regions and metropolitan areas in the country [2,12].

The market mechanism is insufficient to provide an optimum geographical distribution, leading to a great failure. In such cases, it is possible to provide a better distribution of physicians through utilisation of appropriate public policies. This was one of the most important problems in the health systems of the leader countries of free market mechanisms such as US and Britain in the 1960s. Even today, it is still possible to see this problem but to a lesser degree due to the effects of applied interventional policies [1,4,13].

Therefore, the distribution of physicians has always been subject to governmental intervention at universal level. The provision of equal access to health care providers in all regions as far as possible must be one of the targets for the health system of a country. The governments are developing two main policies in this field: The first one is to increase the number of physicians and the second one is to improve the geographical distribution of physicians with several arrangements.

Geographical distribution of physicians in Turkey

The level of regional inequalities in the geographic distribution of physicians was very high in the early years of the Republic of Turkey. Inasmuch as there was a shortage of physicians throughout the country which was in the beginning phase of the socioeconomic development, the results of unrestrained distribution of physicians did not pose any problem for the government. Together with the increase in the number of physicians, this trend continued. However, the inequalities in the distribution of physicians and the problem of physician shortage in rural areas were often put on the agenda of the politicians by the people living in rural and underdeveloped areas which were in need of health service. Despite the political efforts of the governments that generally increase in the run-up to elections, a well-balanced distribution of physicians could not be achieved; on the contrary, the law that was enacted to improve and regulate the distribution of physicians in the country and that included the compulsory service was considered to be valid as of August 1981. According to “The Law Regarding the Obligation of Civil Service for Some Medical Staff”, it became obligatory for the newly appointed general practitioners (GPs) and the specialists to do a two year compulsory public service. This law was in force for 15 years between 1981 and 1995.

A fair distribution of the physicians throughout the country was the main aim of this law in which the health authority (The Ministry of Health) determined where the newly appointed physicians would work. Thanks to this unique experience, Turkey set a prime example to all countries in the world in regard to what extent the distribution of physicians would be affected or changed by legal arrangements.

The study, in short, consists of the distribution of physicians in Turkey during 35 years that includes 15 years of strict government intervention and the comparison of periods before and during this intervention. As a correcting mechanism, was the legislation about the distribution of physicians efficient, and how? The aim of this study is to present the unique experience of Turkey through the scientific analysis method, which would be a guide for the legislators and political decision-makers.

Materials and methods

In this study, the inequalities and the change in the distribution of physicians in Turkey between 1965 and 2000 are analysed. Besides, the periods before 1980 when the distribution of physicians was not governmentally regulated and after 1980 till 1995 when compulsory service law was applied strictly are comparatively examined. The years from 1965 to 1980 are labelled as the first period while the years from 1981 to 1995 are defined as the second period. To what extent the legal arrangement as a public intervention was successful in providing the even distribution that the market failed to do is assessed.

The data used in this study includes the published data by the Ministry of Health and The State Institute of Statistics between the years 1965 and 2000. There was a noticeable decrease in the effect of the regulation between the years 1995 and 2000 when the law was suspended. During this five-year period, the rate of decrease in Gini index apparently diminished. At the same time, the fact that the data was cut due to the change of regional definition by the Ministry of Health after 2000 has meant that the period after 1995 could not be included in the comparative analysis. In addition, the data regarding the population of regions for the term between 2000 and 2007 could not be obtained due to certain alterations in the census system of the Turkish Statistical Institute.

In Turkey, every physician who works in their own clinics or every hospital and clinic must inform the Ministry of Health about the place where they work. According to the legal regulations, the doctors cannot work outside of their region. Therefore, the data used in this study covers all the physicians in the country and they are categorised into two groups according to being specialist or not. In these analyses, the data on the distribution of physicians both for GPs and specialists is present.

Sixteen groups were defined according to the regional city groups that contain a few (generally 3–4) neighbour cities by Ministry of Health (Figure 1). In general, the initial groups cover cities with high population, or located in coasts and/or at the regional economic centres. They have approximately 2/3 of Turkey’s population. From top to down, the cities in the groups are getting smaller, more rural, underdeveloped and lower population.

Figure 1.

Figure 1

Map of Turkey in respect to health regions determined by the Ministry of Health.

The distribution of physicians is organised as the ratio of population to physician in every each 16 groups for 35 years at three different categories (total physicians, GPs and specialists). This measurement is a basic and simple indicator of the physician distribution. The other measurements of distribution or mal-distribution are Gini index, Atkinson index, Theil index, etc. The Gini index has been widely used to compare geographic distributions of physicians among regions or over time [5,14]. The inequality in the distribution of physicians is measured through using Gini coefficient indices and population to physician ratios in this study. The Gini coefficient is derived from the Lorenz curve of the plot of cumulative percentage of the population by socio-economic status and cumulative percentage of total income. The Gini coefficient is calculated as the ratio of the area between the Lorenz curve and the 45° line, to the whole area below the 45° line; a Gini coefficient of 0 reflects a perfectly equal society, and a Gini coefficient of 1 represents a perfectly unequal society [15,16]. The Brown formula is used for this purpose [17].

G=1i=0k1Yi+1+YiXi+1Xi

G: Gini coefficient

Yi: Cumulative proportion of the physicians (total, GP sor specialists) in the ith region

Xi: Cumulative proportion of the population variable in the ith region

k: total number of region

In the operationalised using of this formula, gini coefficents were derived from the Lorenz curve with plotting the region having the highest population per physician (starting from the worst to the best among the 16 regions), the corresponding cumulative population ratio of the region to the cumulative physician number of that region.

Covering 35 years for total physicians, GPs and specialists, Gini coefficients are calculated so as to observe the change in the distribution. While the physicians have a right to express their preferences in their work and settlement place before 1981 (first period), during the compulsory service legislation period (second period), the newly graduated physicians (both GPs and specialists) have to work for two years in the place which is already appointed by the Ministry of Health. Changes in the distribution of physicians between the first and the second period are compared. In order to measure the efficiency of government intervention, changes in Gini index for both periods are analysed including the statistical tests. The effect of independent variables (years) on dependent variable (Gini index) is diagnosed via multiple linear regression analysis using SPSS after preliminary regression assumptions are confirmed. The effect of law intervention is examined from two perspectives. The first one is between periods (pre-after 1981) and, second one is between GPs and specialists in the second period. The effect of group differentiation is analysed through Mann-Whitney U test due to limited number of observations that does not fit with normal distribution. Thus we tested whether the rates of decrease of the Gini coefficients for the GP and specialist were equal over the period from 1981 to 1995 using the Mann-Whitney U test.

Results

Trends in number of physicians and their geographic distribution

In 1965, the average population to physicians is 2881 in Turkey; the Region 1 has the best ratio with 675 and the Region 12 has the worst ratio with 11471 (approximately 17 times). The new student quotas and number of medical schools were increased in Turkey after 1980’s. While the number of physicians was significantly increasing, compulsory service law was levied at the same period to improve the distribution of physicians. Hence, the ratios of population to physicians (for total, GPs and specialists) decreased dramatically. In the year 2000, the average population to physicians is 792 in Turkey; the Region 7 has the best ratio with 445 and the Region 16 has the worst ratio with 2213 (approximately 5 times) (Table 1 and Figure 2).

Table 1.

Regional distribution of physicians in Turkey 1965-2000

Years 1965 1970 1975 1980 1985 1990 1995 2000
Total population/total physician 2881 2572 1858 1642 1391 1115 890 792
Region 1 Total phys. Number of. 4654 5350 7959 8215 11403 13495 17551 19392
Pop/Physc 675 728 607 700 608 629 574 590
Specialists Number of. 3138 3493 4721 5860 7328 8272 8646 10404
Pop/Specia 1002 1115 1024 981 946 1027 1166 1099
GP's Number of. 1516 1857 3238 2367 4075 5223 8905 8988
Pop/GP's 2073 2098 1493 2429 1701 1626 1132 1272
Region 2 Total phys. Total Physc 337 374 643 681 1150 1671 2628 3335
Pop/Physc 5264 5326 3481 3777 2524 1933 1343 1068
Specialists Number of. 211 238 425 415 661 827 1149 1477
Pop/Specia 8408 8370 5266 6198 4392 3906 3072 2412
GP's Number of. 126 136 218 266 489 844 1479 1858
Pop/GP's 14079 14647 10266 9669 5937 3827 2387 1917
Region 3 Total phys. Total Physc 373 442 673 666 1490 2346 3157 4009
Pop/Physc 4863 4430 3150 3593 1780 1283 1055 909
Specialists Number of. 282 316 425 455 887 1266 1459 1784
Pop/Specia 6433 6196 4988 5259 2990 2377 2283 2043
GP's Number of. 91 126 247 211 603 1080 1698 2225
Pop/GP's 19934 15540 8583 11341 4398 2786 1961 1638
Region 4 Total phys. Total Physc 1281 1401 3011 3375 4776 6606 9253 11935
Pop/Physc 2581 2625 1368 1367 1102 906 720 596
Specialists Number of. 802 933 1784 1846 2895 3266 3948 5434
Pop/Specia 4122 3941 2308 2499 1819 1833 1687 1308
GP's Number of. 479 468 1227 1529 1881 3340 5305 6501
Pop/GP's 6902 7857 3356 3017 2799 1793 1255 1094
Region 5 Total phys. Total Physc 261 307 455 634 1027 1533 2223 2510
Pop/Physc 6303 5824 4200 3207 2181 1581 1156 1069
Specialists Number of. 163 207 277 371 502 609 825 943
Pop/Specia 10092 8638 6899 5480 4462 3980 3115 2845
GP's Number of. 98 100 178 263 525 924 1398 1567
Pop/GP's 16786 17880 10736 7730 4267 2623 1838 1712
Region 6 Total phys. Total Physc 185 195 248 537 736 1349 2369 3205
Pop/Physc 5124 5579 4899 2484 2068 1351 894 770
Specialists Number of. 113 136 165 257 385 624 960 1372
Pop/Specia 8389 8000 7364 5191 3953 2920 2205 1798
GP's Number of. 72 59 83 280 351 725 1409 1833
Pop/GP's 13167 18441 14639 4764 4336 2513 1503 1346
Region 7 Total phys. Total Physc 1503 3142 4932 5816 7069 8582 12125 14044
Pop/Physc 2112 1165 866 785 722 631 465 445
Specialists Number of. 782 1927 2720 3247 3995 452 5714 6616
Pop/Specia 4060 1899 1570 1406 1278 1336 986 948
GP's Number of. 721 1215 2212 2557 3074 4530 6411 7341
Pop/GP's 4404 3012 1931 1786 1660 1195 879 851
Region 8 Total phys. Total Physc 194 214 259 281 859 1535 2171 2634
Pop/Physc 7655 7893 7282 7381 2711 1694 1292 1200
Specialists Number of. 114 152 163 129 426 612 719 900
Pop/Specia 13026 11112 11571 16078 5467 4248 3903 3511
GP's Number of. 80 62 96 152 433 923 1452 1734
Pop/GP's 18563 27242 19646 13645 5379 2817 1933 1822
Region 9 Total phys. Total Physc 252 274 454 553 1088 1736 2512 3075
Pop/Physc 9274 9201 5967 5264 2858 1855 1299 1068
Specialists Number of. 169 203 314 302 540 673 887 1236
Pop/Specia 13828 12419 8627 9639 5759 4786 3680 2657
GP's Number of. 83 71 140 251 548 1063 1625 1839
Pop/GP's 28157 35507 19350 11598 5675 3030 2009 1786
Region 10 Total phys. Total Physc 192 224 332 611 1101 1810 2104 2639
Pop/Physc 9047 8353 6078 3524 2103 1343 1187 999
Specialists Number of. 127 151 222 276 513 754 709 882
Pop/Specia 13677 12391 9090 7801 4513 3223 3523 2990
GP's Number of. 65 73 110 335 588 1056 1395 1757
Pop/GP's 26723 25630 18346 6427 3937 2301 1791 1501
Region 11 Total phys. Total Physc 606 625 961 1352 2478 3097 4389 6786
Pop/Physc 4736 5365 4222 3501 2247 2049 1518 1116
Specialists Number of. 385 431 633 744 1443 1514 1788 2746
Pop/Specia 7455 7780 6410 6362 3859 4191 3727 2758
GP's Number of. 221 194 328 608 1035 1583 2553 3764
Pop/GP's 12986 17284 12369 7785 5381 4008 2610 2012
Region 12 Total phys. Total Physc 155 237 342 723 846 1268 1742 2064
Pop/Physc 11471 8165 5965 2873 2569 1682 1167 1131
Specialists Number of. 84 112 191 245 376 449 531 689
Pop/Specia 21167 17277 10681 8478 5779 4751 3829 3388
GP's Number of. 71 125 151 478 470 819 1211 1375
Pop/GP's 25042 15480 13510 4345 4623 2604 1679 1698
Region 13 Total phys. Total Physc 147 220 282 330 564 963 1677 2227
Pop/Physc 9163 6941 6082 5461 3500 2179 1302 1071
Specialists Number of. 57 106 162 118 229 294 479 656
Pop/Specia 23632 14406 10586 15271 8620 7136 4557 3636
GP's Number of. 90 114 120 212 335 669 1198 1571
Pop/GP's 14967 13395 14292 8500 5893 3136 1822 1518
Region 14 Total phys. Total Physc 245 310 43 383 745 1707 1780 2240
Pop/Physc 6486 6106 4451 6243 3901 2053 2275 2030
Specialists Number of. 81 179 220 120 243 678 480 687
Pop/Specia 19617 10575 9773 19925 11959 5168 8435 6620
GP's Number of. 164 131 263 263 502 1029 1297 1553
Pop/GP's 9689 14450 8175 9091 5789 3405 3122 2929
Region 15 Total phys. Total Physc 382 450 576 647 843 1066 1471 1832
Pop/Physc 4555 4247 3590 3326 2728 2108 1446 1313
Specialists Number of. 112 215 234 268 371 314 438 549
Pop/Specia 15536 8888 8838 8030 6200 7156 4856 4383
GP's Number of. 270 235 342 379 472 752 1033 1185
Pop/GP's 6444 8132 6047 5678 4873 2988 2059 2030
Region 16 Total phys. Total Physc 128 78 104 165 252 440 676 877
Pop/Physc 5500 10872 9596 7176 5437 3445 2506 2213
Specialists Number of. 37 19 41 32 84 100 188 272
Pop/Specia 19027 44632 24342 37000 16310 15160 9011 7136
GP's Number of. 91 59 63 133 168 340 488 605
Pop/GP's 7736 14373 15841 8902 8155 4459 3471 3208

Figure 2.

Figure 2

Change on the ratios of population to physicians for total (a), GP’s (b) and (c) specialists in regions that have the most and least ratios of population to physicians.

Change of gini index

Gini coefficients that are calculated for the analysis of inequalities in the distribution of physicians are shown in Table 2. It also demonstrates a serious decrease in the unequal distribution of physicians between 1965 and 2000 in Turkey. In 1965, the Gini for total physician is quite high (0.47), and in 2000 it decreases considerably (0.20). In 1965, the Gini for GPs and specialists are 0.44 and 0.52, respectively and in 2000 these values decrease to 0.13 and 0.28, respectively. The inequality in the distribution of specialists is still at an important level.

Table 2.

Gini indices for three categories between 1965 and 2000

Years Gini total Gini GP Gini specialist
1965 0.47 0.44 0.52
1966 0.46 0.44 0.51
1967 0.45 0.44 0.49
1968 0.46 0.42 0.51
1969 0.47 0.48 0.49
1970 0.48 0.47 0.49
1971 0.49 0.48 0.50
1972 0.47 0.43 0.50
1973 0.46 0.47 0.46
1974 0.49 0.49 0.49
1975 0.49 0.48 0.47
1976 0.49 0.53 0.47
1977 0.45 0.45 0.47
1978 0.46 0.45 0.47
1979 0.44 0.39 0.49
1980 0.42 0.35 0.49
1981 0.42 0.37 0.47
1982 0.36 0.32 0.42
1983 0.37 0.29 0.44
1984 0.35 0.29 0.41
1985 0.34 0.26 0.41
1986 0.33 0.25 0.39
1987 0.33 0.27 0.40
1988 0.30 0.22 0.38
1989 0.27 0.18 0.36
1990 0.25 0.17 0.34
1991 0.25 0.17 0.35
1992 0.23 0.16 0.33
1993 0.24 0.17 0.33
1994 0.22 0.16 0.33
1995 0.22 0.16 0.31
1996 0.23 0.18 0.31
1997 0.22 0.17 0.31
1998 0.23 0.16 0.31
1999 0.20 0.14 0.29
2000 0.20 0.13 0.28

In the first period between the years 1965–1980, there is not a considerable amount of decrement in the Gini index compared to the second period between the years 1981–1995 during which a dramatic decline is observed (Table 3).

Table 3.

Changes in gini index

Years Gini total % Change Gini GP’s % Change Gini specialists % Change
1965 0.47 - 0.44 - 0.52 -
1970 0.48 2.13 0.47 6.82 0.49 −5.77
1975 0.49 2.08 0.48 2.13 0.47 −4.08
1980 0.42 −14.29 0.35 −27.08 0.49 4.26
1985 0.34 −19.05 0.26 −25.71 0.41 −16.33
1990 0.25 −26.47 0.17 −34.62 0.34 −17.07
1995 0.22 −12.00 0.16 −5.88 0.31 −8.82
2000 0.20 −9.09 0.13 −18.75 0.28 −9.68

The geographic distribution of physicians was seriously unequal during the first period. Geographic disparities in physician density were still quite high at the beginning of 1980s. The Turkish authoritarian government at the beginning of 1980s passed the “compulsory service law” to improve the geographic distribution of physicians. At the same time the quotas for medical students were also increased. Despite these interventions, the inequality was still present in 2000, but it decreased.

Concentration of physicians in developed-urban regions is observed among both GP’s and specialists. The degree of this concentration is higher in specialists than in GP’s (Table 2). This tendency is driven during all years and two periods. But inequalities have been decreasing and this decrease is especially remarkable in the second period when the two years of compulsory service for newly appointed physicians and newly appointed specialists is enacted.

Changes in mal-distribution and efficacy of regulation

For the total period, 1965–1995, it has been determined that the difference between the average Gini index of general practitioners (GPs) and specialists is significant (p < 0.01) (Tables 4 and 5). The average Gini index of GPs is lower than that of specialists, indicating that the geographic distribution among GPs is better (i.e. shows more equality) than specialists. As the Figure 3 suggests, the Gini coefficient for the GPs has almost always been lower than that of the specialists. In order to test whether the Gini coefficient for the GPs has statistically been lower than the Gini coefficient of the specialists, we conduct the test of equality of these two coefficients over time by using the standard Z-test. We find Z = 8.724 with p < 0.000, suggesting that the Gini coefficient for the GPs has indeed statistically been lower than the Gini coefficient of the specialists.

Table 4.

Period under discussion

Count Percentage
1965-1980 16 51.61
1981-1995 15 48.39
Total 31 100

Table 5.

Gini scores by periods

Period Gini total Gini GP Gini specialist
1965-1995 Mean 0.385 0.344 0.435
N = 31 Std. Dev 0.096 0.125 0.066
Median 0.42 0.37 0.47
Minimum 0.22 0.16 0.31
Maximum 0.49 0.53 0.52
1965-1980 Mean 0.466 0.451 0.488
N = 16 Std. Dev. 0.0200 0.042 0.017
Median 0.465 0.45 0.49
Minimum 0.42 0.35 0.46
Maximum 0.49 0.53 0.52
1981-1995 Mean 0.299 0.229 0.378
N = 15 Std. Dev. 0.063 0.069 0.047
Median 0.30 0.22 0.38
Minimum 0.22 0.16 0.31
Maximum 0.42 0.37 0.47
P 0.001** 0.001** 0.001**

Mann Whitney U test **p < 0.01.

Figure 3.

Figure 3

Gini index by periods.

It has been found that the difference between average Gini index of two periods is significant for both GPs and specialists. The average Gini index of the second period is lower than that of first period for both doctor groups (namely GPs and specialists). The significance of differentiation between first and second period is analysed through Mann–Whitney U test (p < 0.001). This means that the doctor distribution improved significantly within the second period; the result is consistent for both GPs and specialists.

The analysis of improvement in gini index

In the previous section, it is remarked that the average Gini index of both GPs and specialists is significantly lower in the second period compared to first period. The Gini index exhibits a downward trend through the years (Figure 4).

Figure 4.

Figure 4

Gini index for two periods.

In order to confirm this trend and to determine how this trend changes among doctor groups and periods, regression analysis is used. Before estimating the regression equation, we test stationarity of the series. For this purpose, we apply the stationarity test proposed by Kwiatkowski et al. [18]. The results of this stationarity test are provided below in Table 6.

Table 6.

Stationarity test results

Series Test statistic
Physicians (total) 0.142
GP 0.114
Specialists 0.165

Notes: Test includes constant and trend. Critical value of the test statistic at 1% significance level is 0.216.

As the estimated test statistics for all three variables are less than the critical value, the null hypothesis of stationarity cannot be rejected at 1% significance level. This finding implies that all the three series under investigation are stationary, and hence, regression results will be robust. Therefore, we proceed to estimate the regression equations.

The linear regression model is applied to the data. “Gini index” is the dependent variable and the time is the independent variable. Initially, separate regression models (equations) for each doctor group focusing on the total period are formed (1965 – 1995). Later on, for each period and for each doctor group regression models have been set. Below one can find regression equations on which our model is based:

Gini_GP=a+b*Year19651995Gini_Specialist=a+b*Year19651995Gini_GP=a+b*Year19651980Gini_Specialist=a+b*Year19651980Gini_GP=a+b*Year19811995Gini_Specialist=a+b*Year19811995

Results have been presented below (Table 7):

Table 7.

Regression analysis

Period a (constant) b Conf. interval of b* R 2
1965-1995 GP 0.545 −0.013 −0.015/-0.010 0.832
N = 31 Specialist 0.544 −0.007 −0.008/-0.006 0.889
1965-1980 GP 0.465 0.002** −0.007/0.003 0.036
N = 16 Specialist 0.509 −0.002 −0.004/-0.001 0.430
1981-1995 GP 0.578 −0.015 −0.017/-0.012 0.898
N = 15 Specialist 0.622 −0.010 −0.012/-0.009 0.941

*: 95% confidence level.

**: Statistically not significant.

Between 1965 and 1995 (total period), average decrease in Gini index is 0.013 (standard error is 0.001) per annum in GP doctor group. On the other hand, the average decrease in Gini index in specialist group is 0.007 (std error is <0.001). We can conclude that the rate of decrease in Gini index is significantly higher in GP group compared to specialist. For both regression model R2 is reported as above 0.80 indicating that linear regression model represents real situation well enough. That is to say, linear regression model fits the examined data.

Regression analysis with regard to two different periods reveals that in the first period (1965–1980) the regression model for the GP group is not significant (i.e. b = 0), meaning that we cannot conclude a linear trend for this period for GPs. In the specialist group a significant downward linear trend is noted, nevertheless the magnitude is small (b = −0.002; confidence interval −0.004/-0.001). However R2 (0.43) is lower than the required for a model to be representative of the real situation.

On the other hand, the regression analysis of the second period (1981–1995) reveals more conclusive results. The average decrease in Gini index per annum is −0.015 (std. error 0.001) for the GP group and 0.010 (0.001) for the specialist group. It can be clearly concluded that the rate of decrease in Gini index in the second period is significantly higher in the GP group compared to the specialist group. In other words, the rate of improvement in GP distribution is faster than that of specialists. Another consistent finding by Mann–Whitney U is shown at Table 8. According to results, there is a significant difference between GPs and specialists (p < 0.05).

Table 8.

Comparing of changes in rate of gini index decrease between GPs and specialists

Test statistics Value
Mann-Whitney U 8.000
z −4.341
Asymp. Sig. (2-tailed) .000
Exact Sig. [2*(1-tailed Sig.)] .000 (a)

The following model is developed in order to analyse the effects of both the increasing number of physicians and the government regulation. A multiple regression analysis is conducted to estimate the model parameters.

Gini=β0+β1Phsicianper10000people+β2Regulation+β3Time+ε

Table 9 shows the estimated results of the multiple regression equation.

Table 9.

Regression analysis results for estimated variables

Coefficient t-statistics
Physician per 10000 people −0.035* −4.27
Regulation Dummy −0.051* −4.07
Time 0.001 0.41
Constant 0.619* 30.04
Adjusted-R2 0.935
Prob > F 0.00

Dependent Variable: Gini coefficient. *denotes 0.01 level of significance.

Overall model explains 93.5% of the variation in the Gini coefficient with three independent variables. The model is jointly significant at the 0.01 significance level. The regulations imposed by the government have a significant impact on the Gini. It indicates that the Gini coefficient decreased by 0.051 points when the law came into force. The effect of the Physician per 10000 people is also significant as expected. When the number of Physician per 10000 people increased by 1, the Gini coefficient decreased by 0.035 points.

Discussion

Standard location theory assumes that free market mechanism does not fail about physician location behaviour. According to standard location theory, as the number of physicians increases, the diffusion of the physicians from the centre to the periphery will spontaneously occur associated with the decrease in their income [10]. “Standard economic theory (neoclassical) assumes that physicians seek to maximize their profit and therefore tend to practice in region with high income” [3]. But in reality, this is not probable under this assumption since the physicians would create their own demands. The ability of creating their own demands does provide autonomy about the location of physicians. This ability will also cause an increment of supply of health services and expenditures which will provide the resources to be directed to physicians.

Some authors assume that physicians maximize utility rather than profit [9]. Utility function includes non-economic quality of life factors (i.e., percent graduates and professionals located in the area, public school expenditures, non-public teachers per capita, and sufficient hospital beds etc.) [8]. Population, people with high income, big-sized general hospitals, special branch and university hospitals, social utilities have been concentrated in big, developed, metropolitan and seaside cities or areas. Therefore, assumption of standard theory must be built on “utility” concept; otherwise, the uneven distribution of physicians must be accepted as a display of market failure.

Naturally, the concentration tendency of physicians in these urban-developed areas cannot be avoided. Most of the studies done in several countries have indicated that despite the increase in the number of physicians, the overall uneven geographic distribution has not decreased [3]. The number of physicians in non-metropolitan counties and rural areas increases more slowly than that in metropolitan and urban areas. Even though the number of physicians increases, the unequal distribution of physicians could not be improved adequately or the number of physicians in rural regions increases rather slowly when compared with the ratio in metropolises and urban regions. In the literature, it has been reported that despite the relative increase in the number of physicians in proportion to the population, the inequality in the distribution of physicians did not diminish, and increased at that [19,20].

The ratio of population to physicians is decreased spontaneously when the growth rate of physician number is bigger than the population growth rate. But this momentum of decrease is not same for the developed-urban and the undeveloped-rural areas. Physicians will not diffuse to all cities/regions with the same proportion as their numbers increase. Developed regions or urban cities will absorb newly graduated physicians because of the physician shortage and increasing demand for new medical services. Without government intervention, physicians would prefer attractive cities/regions and as a result of these preferences, there would be an uneven geographic distribution of physicians [5]. The situation of Turkey before the start of compulsory service practice in 1980, namely the rate of inequality in the number of physicians which almost remained the same even when the number of doctors arose is consistent with this.

The inequality in the distribution of physicians is higher for specialists than GPs [11]. Especially “specialists will serve comparatively larger market areas than family practitioners and general practitioners” [10]. The inequality in the distribution of specialists who are under the effect of market motivations (profit maximizing) is more significant. For example, Fülöp et al. [5] found that the regional distribution disparity is less pronounced in Germany than in Austria but also differences can be seen most clearly for specialists in both countries (Gini coefficients are significantly higher for specialists to general practitioners in both countries). Meliala et al. [21] found that there is substantial inequality in the distribution of specialist doctors in Indonesia. It is also likely that there is a concentration of specialist doctors in urban areas, where most hospitals are located. Moreover, the fact that they earn a rather high salary in cities due to private work practice is another factor behind this concentration. The outcomes of this study are consistent with these results. For all years (35 years) analysed, the Gini index for specialists, which is a measurement of inequality, is higher than the GPs index.

The health system of a country is deemed to be effective by looking at the distribution of primary care physicians [4]. In Turkey, primary health care services are mainly provided by GPs. Thus, the distribution of GPs is the most important variable of the primary care. Together with the regulation about compulsory service, a significant decrement has been observed for the Gini index of both groups -specialists and GPs- where it was more dramatic for GPs. Similarly, Matsumoto et al. [4] found that the distribution of primary care physicians in Britain is more equitable than in Japan since it is better regulated in Britain.

Newhouse et al. shows that, as the supply of physicians grow, medical and surgical specialists diffuse into smaller communities in the United States. “Contrary to conventional wisdom, physicians will diffuse to nonmetropolitan areas in response to growth in supply” [10]. Other evidence suggests that increasing the number of physicians has only a small impact on reducing the disparities seen in their geographical distribution [3]. For example, an increase in the number of physicians in Japan from 1980 to 1990 did not improve the inequality in physician distribution [22]. Sasaki et al. [23] find that more urbanized regions have more pediatricians and the total increase in pediatricians during 2002–2007 was primarily absorbed into the urban areas.

Increase in the supply of physicians in Turkey does not have a sizable effect –only a small effect, Gini index decreases from 0.47 to 0.42 between 1965 and 1981- on improving the geographic distribution of physicians up to the beginning of the 1980s. Newly graduated physicians do not go to the rural and nonmetropolitan areas even though real income in these areas is higher.

However, there is a dramatic decrement in the Gini index between 1981 and 1995 due to the compulsory service law. And also in the same period, the quotas for medical students have been increased, thus providing a positive effect for this decrement.

It can be argued that the Gini coefficient has declined as a result of increase in number of physicians during the analysed period, and hence, the regulation had a limited effect on reduction in the Gini coefficient. Our finding suggests that, the regulation in fact lowered the Gini coefficient in Turkey, and this decrease was statistically significant. While the improvement in the 1st period (a small decrement in the Gini index from 0.47 to 0.42) does only depend on to the increment in the physician number, the majority of the improvement (decrement in the Gini index from 0.42 to 0.22) in the 2nd period does mainly depend on the regulation.

In the research carried out by Yardım and Üner with respect to the unequal distribution of physicians in Turkey, the value of Gini for total physician for the year of 2010 was calculated as 0,14 [24].

Conclusions

One of the main weaknesses of the health system in Turkey is that there has not been an optimal distribution of physicians. In this study, the changes in the inequality of the physician distribution is analysed for Turkey by considering 16 regions and 35 years. In the early years of the health policy, the increase in the number of medical practitioners is the primary target while the government intervention in the physician distribution receives much less attention. The improvement of the physician distribution is one of the main objectives between the years 1980 and 2000. The increment of the physician supply is an important factor in reducing the inequalities in the physician distribution. This improvement is especially obvious between 1981 and 1995 when the government introduced a strict two-year compulsory service for newly graduated both GP’s and specialists.

As a result, it is observed that the inequalities in the distribution between GPs and specialists are significantly different; inequality of specialist distribution is higher than the GP. The government intervention in the second period (1981–1995) provides an effective and fast improvement in the physician distribution. The decrement in the inequality for GP distribution is seen to be in higher ratios than the specialist. In other words, the rate of improvement in GP distribution is faster than that of specialist.

The findings indicate that the improvement of physician distribution lasts too long when it is left to market mechanism or it does not develop adequately. This phenomenon is more dominant for specialists under market motivation effect than it is for GPs.

Endnote

aSee: Jiang, H.J. and Begun, J.W. [2] for an ecological perspective.

Footnotes

Competing interests

The author declares that he has no competing interests.

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