3. 1 Basic information of GPs in China
Since the establishment of the GP system in China in 2011 and its formal classification as a specialized type of doctor, the number of GPs in China has increased significantly. In 2021, the total number of GPs on the Chinese mainland was 434,868, about four times that in 2012 (109,794), representing a total increase of 325,074 over the decade, with an annual growth rate of 16.53%. Of these, 314,279 were registered as GPs. After 10 years of development, the number of GPs with GP training certificates and successfully registered has increased from 33.86% to 72.27%, changing the low registration rate phenomenon, and their composition ratio has changed significantly. The percentage of those who obtained the GP training certificate has decreased year after year (the Chinese government has not announced the number of those who obtained the GP training certificate in 2021).
From the perspective of each province, the growth rate of GPs in Guizhou (27.62%), Shaanxi (24.65%), and Henan (24.46%) is at the top of the list over the 10 years, except for Tibet, where no comparison is made due to the low base of GPs, While Jiangsu, Guangdong and Sichuan provinces saw the largest increase in the number of GPS on the Chinese mainland, with 34,560, 29,237 and 20,548 GPS added respectively over the past 10 years. Regionally, the number of GPs in 2021 was 44,868, including 224,229 in the Eastern region, 113,757 in the Central region and 96,882 in the Western region, representing 51.56 percent, 26.16 percent and 22.28 percent, respectively. The 10-year average growth rates for GPs in the Eastern region, Central and Western region were 14.48%, 19.91% and 18.39% respectively, with 157,828, 91,565 and 75,681 new GPs. The Eastern region had the highest rate of growth in the number of GPs and the Central region the highest annual rate. Tables 1 and 2 show the detailed results.
In 2021, GPs have grown to 10.14% of all practicing (assistant) physicians, with the highest percentage of 11.54% in the Eastern region, 9.17% and 8.78% in the Central and Western regions, respectively, according to the results of the geographical division. From a national perspective, the number of GPs per 10,000 people will be 3.08 by 2021, with a regional breakdown showing a high of 3.69 per 10,000 in the Eastern region and a slight difference of 2.71 per 10,000 in the Central region and 2.53 per 10,000 in the Western region. By 2021, the number of GPs per 10,000 population in mainland China has gradually increased from 0.81 in 2012 to 3.08 in 2021, and China has successfully achieved the goal set when the GP system was launched in 2012, to initially establish a GP system by 2020, and basically achieve 2-3 qualified GPs per 10,000 residents in urban and rural areas, and initially meet the medical needs of the residents. From an overall perspective, the ratio of GPs in the three regions is still at a low level. See Table 3 for details.
Table 1 Current situation of GPs in China (2012-2021)
Year
|
Total number of GPs
|
Number of registered GPs (n (%))
|
The number of people who have obtained training certificates for GPs (n (%))
|
Number of GPs per 10 000 population
|
2012
|
109794
|
37173 (33.86%)
|
72621 (66.14%)
|
0.81
|
2013
|
145511
|
47402 (32.58%)
|
98109 (67.42%)
|
1.07
|
2014
|
172597
|
64156 (37.17%)
|
108441 (62.83%)
|
1.27
|
2015
|
188649
|
68364 (36.24%)
|
120285 (63.76%)
|
1.37
|
2016
|
209083
|
77631 (37.13%)
|
131452 (62.87%)
|
1.51
|
2017
|
252717
|
96235 (38.08%)
|
156482 (61.92%)
|
1.82
|
2018
|
308740
|
156800 (50.79%)
|
151940 (49.21%)
|
2.22
|
2019
|
365082
|
210622 (57.69%)
|
154460 (42.31%)
|
2.61
|
2020
|
408820
|
255867 (62.59%)
|
152953 (37.41%)
|
2.90
|
2021
|
434868
|
314279 (72.27%)
|
-
|
3.08
|
Table 2 The Number of GPs in different regions of China (2012-2021)
Area
|
2012
|
2013
|
2014
|
2015
|
2016
|
2017
|
2018
|
2019
|
2020
|
2021
|
Average growth rate
|
Total
|
109794
|
145511
|
172597
|
188649
|
209083
|
252717
|
308740
|
365082
|
408820
|
434868
|
16.53%
|
Eastern region
|
66401
|
84464
|
96979
|
104015
|
116537
|
139473
|
170362
|
192116
|
207862
|
224229
|
14.48%
|
Beijing
|
8137
|
8458
|
8221
|
8269
|
8402
|
8591
|
8861
|
9267
|
9918
|
9303
|
1.50%
|
Tianjin
|
1095
|
1427
|
1622
|
2144
|
2403
|
3749
|
4138
|
4568
|
5051
|
5615
|
19.92%
|
Hebei
|
3493
|
6730
|
8637
|
9286
|
9355
|
10017
|
11292
|
18407
|
18995
|
24410
|
24.11%
|
Liaoning
|
3304
|
3513
|
3777
|
3624
|
4195
|
6273
|
9002
|
10847
|
11771
|
11922
|
15.32%
|
Shanghai
|
5323
|
5957
|
6925
|
7352
|
7967
|
8491
|
8629
|
9924
|
9876
|
10673
|
8.04%
|
Jiangsu
|
15068
|
17650
|
19748
|
20841
|
25162
|
27578
|
47794
|
47601
|
49628
|
49433
|
14.11%
|
Zhejiang
|
12251
|
17041
|
19640
|
21627
|
22571
|
30467
|
26047
|
27406
|
27628
|
23446
|
7.48%
|
Fujian
|
2594
|
3634
|
4310
|
5122
|
5786
|
6897
|
8182
|
9157
|
10145
|
11644
|
18.16%
|
Shandong
|
6775
|
7709
|
8967
|
9920
|
11372
|
13565
|
17426
|
21034
|
24760
|
35914
|
20.36%
|
Guangdong
|
7940
|
11765
|
14404
|
14955
|
18338
|
22712
|
27638
|
31950
|
37177
|
39016
|
19.35%
|
Hainan
|
421
|
580
|
728
|
875
|
986
|
1133
|
1353
|
1955
|
2913
|
2853
|
23.69%
|
Middle region
|
22192
|
29674
|
39020
|
45344
|
49944
|
63269
|
75302
|
94847
|
106306
|
113757
|
19.91%
|
Shanxi
|
2552
|
2958
|
3618
|
4014
|
4175
|
6372
|
5962
|
6516
|
7033
|
7441
|
12.63%
|
Jilin
|
1231
|
1680
|
2299
|
2891
|
3384
|
5130
|
4965
|
7536
|
7992
|
8272
|
23.57%
|
Heilongjiang
|
2081
|
2889
|
3730
|
4320
|
4454
|
4493
|
5637
|
6593
|
6942
|
6906
|
14.26%
|
Anhui
|
3191
|
4319
|
6814
|
7360
|
8625
|
10430
|
12917
|
15116
|
18501
|
17101
|
20.51%
|
Jiangxi
|
2081
|
2429
|
3020
|
3319
|
3641
|
5268
|
5620
|
6705
|
8031
|
9624
|
18.55%
|
Henan
|
4722
|
6427
|
8394
|
10349
|
12129
|
15567
|
20497
|
22763
|
24358
|
33830
|
24.46%
|
Hubei
|
3752
|
5044
|
6090
|
6970
|
7020
|
8969
|
10863
|
12857
|
13847
|
12625
|
14.43%
|
Hunan
|
2582
|
3928
|
5055
|
6121
|
6516
|
7040
|
8841
|
16761
|
19602
|
17958
|
24.05%
|
Western region
|
21201
|
31373
|
36598
|
39290
|
42602
|
49975
|
63076
|
78119
|
94652
|
96882
|
18.39%
|
Inner Mongolia
|
1679
|
2374
|
2937
|
3085
|
3178
|
3986
|
4894
|
5801
|
6042
|
6103
|
15.42%
|
Guangxi
|
3087
|
4039
|
4527
|
4671
|
5104
|
6275
|
7958
|
10662
|
13149
|
13091
|
17.41%
|
Chongqing
|
1632
|
2187
|
2527
|
2872
|
3127
|
3866
|
6348
|
8117
|
8769
|
8944
|
20.81%
|
Sichuan
|
4665
|
8983
|
9819
|
10394
|
10360
|
11343
|
13404
|
17838
|
25213
|
20776
|
18.05%
|
Guizhou
|
1032
|
1511
|
2416
|
3147
|
3714
|
5014
|
6238
|
6466
|
7572
|
9269
|
27.62%
|
Yunnan
|
3212
|
4261
|
4106
|
4289
|
4737
|
5253
|
6381
|
8812
|
9481
|
9250
|
12.47%
|
Tibet
|
34
|
67
|
109
|
161
|
202
|
247
|
352
|
642
|
730
|
467
|
33.79%
|
Shaanxi
|
1824
|
1978
|
2770
|
2126
|
2738
|
3578
|
4979
|
5300
|
8098
|
13255
|
24.65%
|
Gansu
|
1389
|
2106
|
2710
|
3312
|
3773
|
3824
|
4835
|
5994
|
6516
|
7422
|
20.47%
|
Qinghai
|
462
|
758
|
881
|
961
|
993
|
1230
|
1315
|
1514
|
1625
|
1686
|
15.47%
|
Ningxia
|
260
|
392
|
471
|
565
|
654
|
926
|
1279
|
1500
|
1638
|
1627
|
22.60%
|
Xinjiang
|
1925
|
2717
|
3325
|
3707
|
4022
|
4433
|
5093
|
5473
|
5819
|
4992
|
11.17%
|
Table 3 Number of GPs in three regions of China in 2021
Area
|
Total number of GPs
|
Number of GPs per 10 000 population
|
Total
|
434868
|
3.08
|
Eastern region
|
224229
|
3.69
|
Middle region
|
113757
|
2.71
|
Western region
|
96882
|
2.53
|
3.2 Analysis of GP allocation
3. 2. 1 Lorenz curve and Gini coefficient
From 2012 to 2021, the Gini coefficient of the distribution of GPs by population in China decreased from 0.312 to 0.147 and the Gini coefficient of the economic perspective decreased from 0.230 to 0.152. In addition, the Gini coefficient of allocation of GPs by geography remained between 0.7 and 0.75 (Table 4). By plotting the trend of Gini coefficient changes in the demographic/economic/geographic dimensions of Chinese GPs from 2012 to 2021 (Figure 1), we can see that the Gini coefficients of all three dimensions show a decreasing trend, and the decreasing trend is more obvious in the demographic and economic dimensions, which means that the equity level of allocation of Chinese GPs improves faster in the demographic and economic dimensions. While the geographic dimension of the Gini coefficient has a smaller tendency to decrease, it fluctuates from 0.745 to 0.715 over a decade. The Gini coefficients of the demographic and economic dimensions were both below the warning line (below the warning line of 0.40), and were less than 0.2, indicating that their GP allocation levels were more equitable and reasonable in the demographic and economic dimensions, but in the geographic dimension, the Gini coefficients were far above the warning line, were above 0.7, indicating that in the geographic dimension, the disparity of GP resource allocation in China is large.
As can be seen from the Lorenz curves of GP allocation from 2012 to 2021, the radians of the Lorenz curves of the population dimension and the economic dimension become smaller and the residual region between them and the absolute line of equity becomes smaller. The Lorenz curve of the population dimension gradually approaches the Lorenz curve of the economic dimension over the course of a decade, and both reach a fairer level. This indicates a more equitable allocation of resources. In contrast, the radian of the geographical dimension is the largest, with a slight change over the past ten years, which is significantly different from the Lorentz curve of the population and economic dimensions, and further away from the absolute fair line, indicating that the equity of GP resources allocation in the geographical dimension is poor in mainland China. The detailed results are shown in Figure 2 in the Lorenz plot for each year.
Table 4 Gini coefficient of Chinese GPs in 2012-2020
Dimension
|
2012
|
2013
|
2014
|
2015
|
2016
|
2017
|
2018
|
2019
|
2020
|
2021
|
Population
|
0.312
|
0.287
|
0.256
|
0.246
|
0.235
|
0.231
|
0.225
|
0.177
|
0.157
|
0.147
|
Economy
|
0.230
|
0.223
|
0.204
|
0.200
|
0.178
|
0.170
|
0.161
|
0.147
|
0.136
|
0.152
|
Geographic
|
0.745
|
0.728
|
0.721
|
0.718
|
0.722
|
0.726
|
0.729
|
0.714
|
0.707
|
0.715
|
3.2.2 Health resource agglomeration degree
From the regional classification analysis, it was found that the agglomeration degree in the Eastern region was 4.618 in 2021, which is much higher than 1, indicating that the concentration of GP assignments is far too high; the Central region has an agglomeration degree of 1.493, which is slightly greater than that of, indicating that the distribution of GPs is relatively fair; The agglomeration degree of GP in the Western region is 0.312, which is much lower than 1, and this level is highly unfair to the distribution of GPs. Analyzing the agglomeration degree of each province, autonomous region and municipality directly under the central government, the agglomeration degree of Guangxi (1.221), Guizhou (1.166), Shanxi (1.052), Jilin (0.978) and Sichuan (0.947) is around 1, which tends to be absolutely fair. Some regions have an agglomeration degree less than one. Heilongjiang (0.324), Inner Mongolia (0.114), Xinjiang (0.066), Qinghai (0.052), and Tibet (0.008) have a low agglomeration degree, which indicates a highly inequitable allocation of GPs based on geographic regions. In contrast, Shanghai (37.546), Beijing (12.572), Tianjin (10.370), and Jiangsu (10.220) have values of agglomeration degree based on geographic area that exceed 10, indicating that their GP allocations are too concentrated in terms of geographic area. The results for the agglomeration degree of population showed that the agglomeration degree in 2021 was 1.196, 0.880 and 0.821 in the Eastern, Central and Western regions, respectively. There is still a concentration of GPs in the Eastern region, while the distribution levels of GPs in the Central and Western regions are similar and the allocated to GPs are relatively scarce. From the perspective of provinces, autonomous regions, and municipalities directly under the central government, based on population agglomeration degree, most regions are between 0.8 and 1.2, indicating that the overall distribution of GPs is more balanced in terms of population distribution, but GP resources in Jiangsu (1.885) are still concentrated.
From 2012 to 2021, the agglomeration degree of GP in the Eastern region decreased from 5.416 to 4.618, in the Central region increased from 1.153 to 1.493, and in the Western region increased from 0.271 to 0.312. Analyzing the agglomeration degree of each region, Shanghai, Jiangsu, Beijing and Zhejiang all had an agglomeration degree above 10 in 2012, especially Shanghai and Beijing, which reached 43.553 and 74.167, respectively, but after a decade of development, the agglomeration degree of each region decreased. In Beijing, for example, the agglomeration degree of GPs fell from 43.553 in 2012, at an annual rate of -12.90%, to 12.572 in 2021, while in Shanghai, it fell from 74.167 in 2012, at an annual rate of -7.28%, to 37.546 in 2021. The GP in Liaoning, Inner Mongolia, Qinghai and Guangxi showed a relatively stable situation (-1%-1%) in terms of population agglomeration degree in the past ten years. In contrast, the four provinces of Henan, Hebei, Hunan and Hainan are still growing with a population agglomeration degree of 1 in 2012, and the equity of their GP resources in terms of population agglomeration degree is becoming more and more unequal.
Table 5 Agglomeration degree in 2012-2021
Region
|
Dimension
|
2012
|
2013
|
2014
|
2015
|
2016
|
2017
|
2018
|
2019
|
2020
|
2021
|
Eastern region
|
Geographic
|
5.416
|
5.198
|
5.032
|
4.938
|
4.991
|
4.942
|
4.942
|
4.713
|
4.553
|
4.618
|
Population
|
1.460
|
1.399
|
1.354
|
1.328
|
1.311
|
1.294
|
1.290
|
1.228
|
1.181
|
1.196
|
Beijing
|
Geographic
|
43.553
|
34.159
|
27.991
|
25.759
|
23.615
|
19.977
|
16.866
|
14.917
|
14.257
|
12.572
|
Population
|
4.828
|
3.724
|
3.016
|
2.768
|
2.545
|
2.166
|
1.837
|
1.632
|
1.563
|
1.379
|
Tianjin
|
Geographic
|
8.010
|
7.876
|
7.548
|
9.128
|
9.231
|
11.914
|
10.764
|
10.049
|
9.923
|
10.370
|
Population
|
0.951
|
0.903
|
0.844
|
1.007
|
1.107
|
1.471
|
1.360
|
1.272
|
1.256
|
1.327
|
Hebei
|
Geographic
|
1.631
|
2.371
|
2.565
|
2.523
|
2.294
|
2.032
|
1.875
|
2.585
|
2.382
|
2.878
|
Population
|
0.588
|
0.855
|
0.923
|
0.909
|
0.843
|
0.748
|
0.691
|
0.953
|
0.878
|
1.063
|
Liaoning
|
Geographic
|
1.988
|
1.595
|
1.446
|
1.269
|
1.325
|
1.640
|
1.926
|
1.963
|
1.902
|
1.811
|
Population
|
0.924
|
0.745
|
0.679
|
0.601
|
0.645
|
0.805
|
0.953
|
0.978
|
0.954
|
0.914
|
Shanghai
|
Geographic
|
74.167
|
62.627
|
61.379
|
59.619
|
58.292
|
51.399
|
42.756
|
41.584
|
36.956
|
37.546
|
Population
|
2.746
|
2.297
|
2.253
|
2.212
|
2.147
|
1.904
|
1.584
|
1.543
|
1.369
|
1.391
|
Jiangsu
|
Geographic
|
12.338
|
10.905
|
10.287
|
9.932
|
10.819
|
9.811
|
13.917
|
11.722
|
10.914
|
10.220
|
Population
|
2.336
|
2.070
|
1.958
|
1.899
|
1.996
|
1.811
|
2.572
|
2.168
|
2.019
|
1.885
|
Zhejiang
|
Geographic
|
10.193
|
10.698
|
10.395
|
10.473
|
9.862
|
11.013
|
7.707
|
6.858
|
6.174
|
4.925
|
Population
|
2.746
|
2.887
|
2.815
|
2.837
|
2.471
|
2.731
|
1.887
|
1.658
|
1.473
|
1.163
|
Fujian
|
Geographic
|
1.836
|
1.941
|
1.941
|
2.110
|
2.151
|
2.121
|
2.060
|
1.949
|
1.929
|
2.081
|
Population
|
0.850
|
0.897
|
0.894
|
0.970
|
0.958
|
0.938
|
0.906
|
0.854
|
0.841
|
0.902
|
Shandong
|
Geographic
|
3.817
|
3.277
|
3.214
|
3.253
|
3.365
|
3.320
|
3.491
|
3.564
|
3.746
|
5.109
|
Population
|
0.859
|
0.738
|
0.723
|
0.732
|
0.758
|
0.748
|
0.786
|
0.803
|
0.840
|
1.145
|
Guangdong
|
Geographic
|
3.879
|
4.336
|
4.476
|
4.252
|
4.704
|
4.820
|
4.801
|
4.694
|
4.877
|
4.812
|
Population
|
0.920
|
1.029
|
1.060
|
1.002
|
1.024
|
1.035
|
1.017
|
0.987
|
1.016
|
0.998
|
Hainan
|
Geographic
|
1.044
|
1.085
|
1.148
|
1.263
|
1.284
|
1.221
|
1.193
|
1.458
|
1.940
|
1.786
|
Population
|
0.583
|
0.604
|
0.636
|
0.698
|
0.685
|
0.645
|
0.626
|
0.758
|
0.993
|
0.907
|
Middle region
|
Geographic
|
1.153
|
1.164
|
1.290
|
1.372
|
1.363
|
1.429
|
1.392
|
1.483
|
1.484
|
1.493
|
Population
|
0.641
|
0.648
|
0.719
|
0.765
|
0.784
|
0.826
|
0.809
|
0.865
|
0.873
|
0.880
|
Shanxi
|
Geographic
|
1.430
|
1.250
|
1.289
|
1.309
|
1.228
|
1.551
|
1.188
|
1.098
|
1.058
|
1.052
|
Population
|
0.868
|
0.759
|
0.783
|
0.796
|
0.790
|
1.004
|
0.774
|
0.719
|
0.695
|
0.694
|
Jilin
|
Geographic
|
0.577
|
0.594
|
0.685
|
0.788
|
0.832
|
1.044
|
0.827
|
1.062
|
1.005
|
0.978
|
Population
|
0.550
|
0.569
|
0.659
|
0.763
|
0.876
|
1.123
|
0.908
|
1.187
|
1.149
|
1.130
|
Heilongjiang
|
Geographic
|
0.386
|
0.405
|
0.440
|
0.467
|
0.434
|
0.362
|
0.372
|
0.368
|
0.346
|
0.324
|
Population
|
0.666
|
0.702
|
0.768
|
0.824
|
0.855
|
0.731
|
0.770
|
0.781
|
0.755
|
0.717
|
Anhui
|
Geographic
|
1.999
|
2.042
|
2.716
|
2.684
|
2.838
|
2.839
|
2.878
|
2.848
|
3.113
|
2.705
|
Population
|
0.654
|
0.667
|
0.884
|
0.871
|
0.950
|
0.952
|
0.966
|
0.957
|
1.045
|
0.907
|
Jiangxi
|
Geographic
|
1.094
|
0.964
|
1.010
|
1.016
|
1.006
|
1.204
|
1.051
|
1.061
|
1.134
|
1.278
|
Population
|
0.567
|
0.500
|
0.525
|
0.528
|
0.538
|
0.646
|
0.566
|
0.573
|
0.613
|
0.691
|
Henan
|
Geographic
|
2.482
|
2.549
|
2.807
|
3.166
|
3.348
|
3.555
|
3.831
|
3.598
|
3.438
|
4.490
|
Population
|
0.616
|
0.636
|
0.702
|
0.793
|
0.825
|
0.876
|
0.944
|
0.887
|
0.845
|
1.110
|
Hubei
|
Geographic
|
1.772
|
1.797
|
1.829
|
1.915
|
1.741
|
1.840
|
1.824
|
1.826
|
1.756
|
1.505
|
Population
|
0.797
|
0.810
|
0.827
|
0.866
|
0.793
|
0.840
|
0.834
|
0.837
|
0.831
|
0.702
|
Hunan
|
Geographic
|
1.070
|
1.228
|
1.333
|
1.476
|
1.418
|
1.268
|
1.303
|
2.089
|
2.182
|
1.879
|
Population
|
0.477
|
0.547
|
0.592
|
0.656
|
0.654
|
0.587
|
0.606
|
0.974
|
1.017
|
0.880
|
Western region
|
Geographic
|
0.271
|
0.302
|
0.297
|
0.292
|
0.286
|
0.277
|
0.286
|
0.300
|
0.325
|
0.312
|
Population
|
0.714
|
0.798
|
0.784
|
0.769
|
0.755
|
0.731
|
0.754
|
0.789
|
0.852
|
0.821
|
Inner Mongolia
|
Geographic
|
0.125
|
0.133
|
0.139
|
0.133
|
0.124
|
0.128
|
0.129
|
0.129
|
0.120
|
0.114
|
Population
|
0.828
|
0.885
|
0.926
|
0.893
|
0.867
|
0.906
|
0.918
|
0.926
|
0.867
|
0.825
|
Guangxi
|
Geographic
|
1.140
|
1.126
|
1.064
|
1.004
|
0.990
|
1.007
|
1.046
|
1.185
|
1.305
|
1.221
|
Population
|
0.809
|
0.797
|
0.752
|
0.708
|
0.699
|
0.707
|
0.731
|
0.825
|
0.904
|
0.843
|
Chongqing
|
Geographic
|
1.739
|
1.758
|
1.712
|
1.781
|
1.749
|
1.789
|
2.405
|
2.600
|
2.509
|
2.406
|
Population
|
0.680
|
0.686
|
0.667
|
0.692
|
0.668
|
0.680
|
0.912
|
0.982
|
0.943
|
0.903
|
Sichuan
|
Geographic
|
0.843
|
1.224
|
1.128
|
1.093
|
0.983
|
0.890
|
0.861
|
0.969
|
1.223
|
0.947
|
Population
|
0.709
|
1.032
|
0.952
|
0.921
|
0.835
|
0.757
|
0.732
|
0.824
|
1.039
|
0.805
|
Guizhou
|
Geographic
|
0.514
|
0.568
|
0.766
|
0.912
|
0.972
|
1.085
|
1.105
|
0.969
|
1.013
|
1.166
|
Population
|
0.364
|
0.402
|
0.544
|
0.648
|
0.657
|
0.729
|
0.742
|
0.648
|
0.677
|
0.781
|
Yunnan
|
Geographic
|
0.715
|
0.716
|
0.582
|
0.556
|
0.554
|
0.508
|
0.505
|
0.590
|
0.567
|
0.520
|
Population
|
0.846
|
0.847
|
0.688
|
0.657
|
0.673
|
0.619
|
0.617
|
0.721
|
0.693
|
0.640
|
Tibet
|
Geographic
|
0.002
|
0.004
|
0.005
|
0.007
|
0.008
|
0.008
|
0.009
|
0.014
|
0.014
|
0.008
|
Population
|
0.136
|
0.200
|
0.271
|
0.361
|
0.395
|
0.391
|
0.452
|
0.686
|
0.688
|
0.414
|
Shaanxi
|
Geographic
|
0.779
|
0.637
|
0.752
|
0.528
|
0.614
|
0.664
|
0.756
|
0.681
|
0.929
|
1.429
|
Population
|
0.597
|
0.489
|
0.579
|
0.407
|
0.470
|
0.507
|
0.576
|
0.518
|
0.706
|
1.087
|
Gansu
|
Geographic
|
0.286
|
0.328
|
0.355
|
0.397
|
0.408
|
0.342
|
0.354
|
0.372
|
0.361
|
0.386
|
Population
|
0.661
|
0.760
|
0.826
|
0.926
|
0.995
|
0.839
|
0.874
|
0.921
|
0.899
|
0.967
|
Qinghai
|
Geographic
|
0.056
|
0.070
|
0.068
|
0.068
|
0.063
|
0.065
|
0.057
|
0.055
|
0.053
|
0.052
|
Population
|
0.990
|
1.221
|
1.193
|
1.188
|
1.134
|
1.161
|
1.018
|
0.990
|
0.945
|
0.921
|
Ningxia
|
Geographic
|
0.344
|
0.391
|
0.396
|
0.435
|
0.454
|
0.532
|
0.601
|
0.596
|
0.582
|
0.543
|
Population
|
0.493
|
0.558
|
0.562
|
0.615
|
0.626
|
0.726
|
0.819
|
0.807
|
0.784
|
0.728
|
Xinjiang
|
Geographic
|
0.101
|
0.108
|
0.112
|
0.114
|
0.111
|
0.102
|
0.095
|
0.087
|
0.082
|
0.066
|
Population
|
1.058
|
1.118
|
1.142
|
1.141
|
1.101
|
0.989
|
0.918
|
0.825
|
0.775
|
0.625
|
3.3 Grey forecast model
In this study, the Grey forecast model was established using the original series of GP resources data in mainland China from 2012 to 2021, and the number of GPs was assigned to the time series for a total of 10 years from 2012 to 2021, and the final prediction of the number of GPs in mainland China in the next five years (2022-2026) was obtained through the calculation formula. The prediction results of the number of GPs in the whole country and the Eastern, Central and Western regions were modeled from the regional perspective, and the model prediction results were tested by the post-test difference method, and the test statistic C was less than 0.35 and the p-value was greater than 0.95, which indicated that the model accuracy level was very good and the model was well adapted, the accuracy level of each model is 1. Therefore, the model can be applied to extrapolating prediction studies of the number of GPs and the population of mainland China. The results showed that the development coefficients A, which were -0.055, -0.051, -0.061 and -0.058 for the whole country and the Eastern, Central and Western regions respectively, have values less than 0.3, indicating that they can be used for medium- and long-term forecasting with high accuracy. The endogenous control gray numbers B were 519387, 279536, 128328, and 111627, respectively (Table 6). The predicted number of GPs in 2026 calculated by the gray prediction model based on the original data were 719,198 nationwide, 357,900 in the eastern region, 198,472 in the central region, and 163,835 in the western region (all within 5% error at the later stage), as shown in Table 7. After a decade of development since the establishment of the GP system, the GPs in the Chinese mainland in 2021 showed a continuous growth trend. The number of GPs in mainland China has reached 430,000, an increase of approximately 320,000 or 396% compared to 109,794 in 2012. By forecasting the next five years, it is expected that the number of GPs in mainland China will reach 720,000 in 2026, an increase of about 280,000 (65.38%) compared to 2021. The Eastern region, the Central region and the Western region grew by about 133,671, 84,715 and 66,953 respectively, an increase of 59.61 per cent, 74.47 per cent and 69.11 per cent. See Fig. 3 for details.
In addition, this study also predicted the population size of mainland China in the next five years and used it to calculate the number of GPs per 10,000 population in 2026, which showed that the population size of mainland China will reach 1451 million in 2026 and the number of GPs per 10,000 population will reach 4.9 [46]. The number of people in the eastern, central and western regions will reach 642, 415 and 394 million, respectively, and the number of GPs per 10,000 population will reach 5.5, 4.8 and 4.1, which is basically consistent with the government's proposal in 2018 to reach 700,000 GP by 2030, reaching the goal of 5 GPs per 10,000 people. But the actual number of GPs in mainland China may be lower than the results of the predicted model, and also the number of GPs per 10,000 population will be lower than the results shown in the study, due to factors such as the impact of the COVID-19 epidemic, saturation of GP resources or job restrictions in high agglomeration degree areas. Table 8.
Table 6 Grey forecast model test value
Project
|
East region
|
Central region
|
West region
|
Total
|
Development coefficients A
|
-0.051
|
-0.061
|
-0.058
|
-0.055
|
Endogenous control gray numbers B
|
279536
|
128328
|
111627
|
519387
|
Test statistic C
|
0.013
|
0.011
|
0.035
|
0.014
|
P-value
|
1
|
1
|
1
|
1
|
Table 7 Grey forecast model results of the East, Central and West regions (2022-2026)
Year
|
East region
|
Central region
|
West region
|
Total
|
2022
|
251356
|
130677
|
109534
|
491369
|
2023
|
276008
|
146103
|
121944
|
543719
|
2024
|
301938
|
162502
|
135101
|
599027
|
2025
|
329213
|
179937
|
149049
|
657461
|
2026
|
357900
|
198472
|
163835
|
719198
|
Table 8 Population forecast and number of GPs per 10 000 people in Mainland China
Year
|
East region
|
Central region
|
West region
|
Total
|
Predictive value
|
GPs/10 000 people
|
Predictive value
|
GPs/10 000 people
|
Predictive value
|
GPs/10 000 people
|
Predictive value
|
GPs/10 000 people
|
2022
|
62186
|
4.0
|
41849
|
3.1
|
38772
|
2.8
|
142773
|
3.4
|
2023
|
62866
|
4.4
|
41734
|
3.5
|
39005
|
3.1
|
143546
|
3.8
|
2024
|
63554
|
4.8
|
41619
|
3.9
|
39239
|
3.4
|
144324
|
4.2
|
2025
|
64249
|
5.1
|
41505
|
4.3
|
39474
|
3.8
|
145106
|
4.5
|
2026
|
64952
|
5.5
|
41391
|
4.8
|
39711
|
4.1
|
145893
|
4.9
|