3.1 Equity of medical and health resources in Western China in 2019
(1) Distribution of medical and health resources based on geographical area in western China in 2019
From Equ.1, HRAD of Inner Mongolia was obtained as follow.
HRAD Inner Mongolia = [(HR Inner Mongolia / HR Western China)×100%] / [(A Population of Inner Mongolia / A Population in western China)×100%]=[(24564/31548)×100%] / [(1183000/6830600)]=0.45.
Other results are shown in the Table 3. (See Table 3).
From Table 3, we find the agglomeration degree of medical and health resources in Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu and Ningxia was greater than 1 in 2019, indicating that the equity of geographical area allocation was good.
In 2019, the agglomeration degree of medical and health resources in Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu and Ningxia was greater than 1, indicating that the equity of geographical area allocation was good. Among them, Chongqing was the most typical. The agglomeration degree of various medical and health resources was much higher than the standard of equity of 1, and the geographical area allocation was the best in the western region. The agglomeration degree of medical and health resources in Inner Mongolia, Tibet, Qinghai and Xinjiang is far less than 1, indicating that the equity of geographical allocation needs to be improved. (See Table 3)
(2) Distribution of health resources based on population size in western China in 2019
From Equ.1and Equ.2, PAD in Inner Mongolia was obtained as follow.
PADInner Mongolia=[(PInner Mongolia/PWestern China)×100%] / [(APopulation of Inner Mongolia/APopulation in western China)×100%]=[(25400000/381800000)×100%] / [(1183000/6830600)]=0.384.
Then, Rate=HRAD Inner Mongolia / PAD Inner Mongolia=1.17.
Other results are shown in the table. (See Table 3)
The ratio of medical and health resources agglomeration degree to population agglomeration degree in 12 provinces and autonomous regions in the western region is between 0.007 and 1.979. Among them, Chongqing has the highest ratio of medical and health resources agglomeration degree to population agglomeration degree, reaching 1.489, 1.979, 1.780, 1.879 and 1.851, respectively, indicating that the surplus of medical and health resources was serious. The ratios of Tibet and Qinghai were between 0.007 and 0.054, indicating that there was a serious shortage of medical and health resources in these regions, which cannot meet the needs of population for medical treatment. Thus, there was a significant difference in the equity of medical and health resources allocation between regions in the western region.
Table 3 Analysis of HRAD and PAD in 12 Provinces and Autonomous Regions of Western China in 2019
City
|
PAD
|
Health institutions
|
Beds
|
Health workers
|
Practicing (assistant) physician
|
Registered nurse
|
HRAD
|
Rate
|
HRAD
|
Rate
|
HRAD
|
Rate
|
HRAD
|
Rate
|
HRAD
|
Rate
|
Inner Mongolia
|
0.384
|
0.450
|
1.170
|
0.433
|
0.927
|
0.403
|
1.049
|
0.456
|
1.187
|
0.374
|
0.973
|
Guangxi
|
3.735
|
3.069
|
0.822
|
3.710
|
0.818
|
3.487
|
0.934
|
3.346
|
0.896
|
3.525
|
0.944
|
Chongqing
|
6.816
|
5.560
|
1.489
|
8.982
|
1.979
|
6.649
|
1.780
|
7.017
|
1.879
|
6.914
|
1.851
|
Sichuan
|
3.083
|
3.731
|
1.000
|
4.131
|
0.910
|
3.008
|
0.805
|
3.151
|
0.844
|
3.060
|
0.819
|
Guizhou
|
3.683
|
3.507
|
0.939
|
4.785
|
1.054
|
3.690
|
0.988
|
3.524
|
0.944
|
3.790
|
1.015
|
Yunnan
|
2.269
|
1.446
|
0.387
|
2.588
|
0.570
|
2.153
|
0.576
|
2.057
|
0.551
|
2.274
|
0.609
|
Tibet
|
0.052
|
0.125
|
0.034
|
0.045
|
0.010
|
0.043
|
0.011
|
0.054
|
0.014
|
0.027
|
0.007
|
Shanxi
|
3.366
|
3.721
|
0.996
|
4.100
|
0.904
|
4.169
|
1.116
|
3.644
|
0.976
|
4.013
|
1.075
|
Gansu
|
1.112
|
1.357
|
0.363
|
1.352
|
0.298
|
1.019
|
0.273
|
1.018
|
0.273
|
1.025
|
0.275
|
Qinghai
|
0.151
|
0.196
|
0.052
|
0.183
|
0.040
|
0.160
|
0.043
|
0.167
|
0.045
|
0.144
|
0.039
|
Ningxia
|
1.884
|
1.442
|
0.386
|
1.974
|
0.435
|
2.038
|
0.546
|
2.172
|
0.582
|
2.024
|
0.542
|
xinjiang
|
0.271
|
0.239
|
0.064
|
0.356
|
0.078
|
0.271
|
0.073
|
0.282
|
0.075
|
0.255
|
0.068
|
Table 4 HRAD and PAD in Western China from 2009 to 2019
Year
|
PAD
|
Health institutions agglomeration degree
|
medical beds agglomeration degree
|
Health workers agglomeration degree
|
Practicing (assistant) physician agglomeration degree
|
Registered nurse agglomeration degree
|
2009
|
0.366
|
0.306
|
0.271
|
0.250
|
0.253
|
0.238
|
2010
|
0.365
|
0.308
|
0.273
|
0.249
|
0.247
|
0.241
|
2011
|
0.368
|
0.311
|
0.276
|
0.254
|
0.250
|
0.246
|
2012
|
0.372
|
0.316
|
0.281
|
0.257
|
0.248
|
0.250
|
2013
|
0.349
|
0.317
|
0.286
|
0.262
|
0.249
|
0.206
|
2014
|
0.380
|
0.318
|
0.288
|
0.266
|
0.248
|
0.260
|
2015
|
0.385
|
0.317
|
0.288
|
0.267
|
0.246
|
0.263
|
2016
|
0.390
|
0.316
|
0.289
|
0.270
|
0.247
|
0.267
|
2017
|
0.395
|
0.316
|
0.292
|
0.273
|
0.248
|
0.274
|
2018
|
0.400
|
0.314
|
0.293
|
0.274
|
0.246
|
0.275
|
2019
|
0.383
|
0.313
|
0.269
|
0.277
|
0.250
|
0.280
|
3.2 Equity of medical and health resource allocation in Western China from 2009 to 2019
(1) Distribution of medical and health resources based on geographical area in western China from 2009 to 2019
From 2009 to 2019, the agglomeration degree of various medical and health resources in the western region was between 0.206 and 0.318, with little fluctuation and no significant improvement in equity. The agglomeration degree of various medical and health resources was : medical institutions > registered nurses > health technicians > medical beds > licensed ( assistant ) physicians. Among them, practicing ( assistant ) physicians in these 11 periods of concentration decreased, need special attention. Overall, the allocation of various types of medical and health resources in the western region was relatively poor relative to the national equity, and medical and health resources was scarce. This is due to the complex terrain in the western region, traffic inconvenience, resulting in medical difficulties, poor geographical accessibility[34,35]. (See Table 4).
(2) Distribution of health resources based on population size in western China from 2009 to 2019
From the ratio of resource concentration and population concentration, the ratio of all kinds of medical and health resources in the western region was less than 1, indicating that all kinds of medical and health resources in the western region were seriously short and cannot meet the needs of the population. Among them, the development and reform commission issued《The“ 12th Five-Year”Plan Western Development》to arrange the western development work in 2013, strengthen the construction of primary health care, and actively improve the level of health care. Perhaps affected by this, the ratio of resource concentration fluctuations, in addition to registered nurses have increased. (Fig. 2)
3.3 Efficiency analysis of medical and health resource allocation in 12 provinces in Western China from 2009 to 2019
In terms of comprehensive efficiency, the comprehensive efficiency of Guangxi, Chongqing, Sichuan, Guizhou and Gansu provinces is greater than 1, indicating that the comprehensive efficiency has improved. The comprehensive efficiency of Yunnan and Ningxia is 1, and the comprehensive efficiency has not changed. The comprehensive efficiency of Inner Mongolia, Tibet, Shaanxi, Qinghai and Xinjiang is less than 1, among which Qinghai ’ s comprehensive efficiency is the most seriously reduced by 2.6 percentage points.
In terms of technological progress rate, Ningxia and Xinjiang in 12 provinces and cities showed a technological decline, the largest decline in Ningxia, a decline of 2.6 percentage points. The remaining 10 provinces and cities showed technological progress, of which Sichuan had the largest progress, an increase of 12 percentage points, and Tibet had a relatively low progress, an increase of 0.2 percentage points.
In terms of scale efficiency, the scale efficiency values of Tibet, Gansu, Qinghai and Xinjiang are less than 1, among which Tibet and Qinghai decrease greatly. The scale efficiency values of Guizhou, Yunnan and Ningxia are 1, and the efficiency does not change. The scale efficiency of the other provinces and cities has improved, and Sichuan has the largest increase by 1.7 percentage points.
In terms of total factor productivity changes, 8 of the 12 provinces and cities in the western region have total factor productivity greater than 1, of which Sichuan has increased by 13.9 percentage points, and Inner Mongolia has increased by 0.1 percentage points. In addition, the total factor production index of Tibet, Qinghai, Ningxia and Xinjiang is less than 1, indicating that the efficiency of medical and health resource allocation in these four places decreased from 2009 to 2019.( See Table 5).
Table 5 Regional characteristics of health resource allocation from 2009 to 2019
City
|
EFF
|
TECH
|
PEC
|
SE
|
TEP
|
Neimenggu
|
0.995
|
1.006
|
0.989
|
1.006
|
1.001
|
Guangxi
|
1.012
|
1.021
|
1.000
|
1.012
|
1.003
|
Chongqing
|
1.017
|
1.025
|
1.013
|
1.004
|
1.043
|
Sichuan
|
1.017
|
1.120
|
1.000
|
1.017
|
1.139
|
Guizhou
|
1.003
|
1.010
|
1.002
|
1.000
|
1.013
|
Yunnan
|
1.000
|
1.021
|
1.000
|
1.000
|
1.021
|
Xizang
|
0.992
|
1.002
|
1.000
|
0.992
|
0.994
|
Shanxi
|
0.999
|
1.018
|
0.989
|
1.010
|
1.016
|
Gansu
|
1.017
|
1.028
|
1.019
|
0.998
|
1.045
|
Qinghai
|
0.974
|
1.010
|
1.002
|
0.972
|
0.984
|
Ningxia
|
1.000
|
0.974
|
1.000
|
1.000
|
0.974
|
xinjiang
|
0.996
|
0.998
|
0.998
|
0.998
|
0.994
|
Mean
|
1.002
|
1.019
|
1.001
|
1.001
|
1.021
|
3.4 Efficiency Analysis of Health Resource Allocation in Western China from 2009 to 2019
From 2009 to 2010, the total factor productivity of medical and health resources in the western region reached 2.012. In 2010 ~ 2011, 2012 ~ 2013, 2013 ~ 2014, 2014 ~ 2015, 2016 ~ 2017, 2017 ~ 2018, the total factor productivity was less than 1. The total factor productivity changed with the rate of technological progress. The total factor productivity of 2009 ~ 2019 was 1.021. It showed that although the efficiency of medical and health resources allocation has declined, it has generally increased by 2.1 percentage points.(See Table 6).
Table 6 Time characteristics of health resource allocation from 2009 to 2019
Time
|
EFF
|
TECH
|
PEC
|
SE
|
TEP
|
2009~2010
|
1.043
|
1.929
|
1.000
|
1.043
|
2.012
|
2010~2011
|
1.004
|
0.983
|
1.003
|
1.001
|
0.987
|
2011~2012
|
0.994
|
1.063
|
0.994
|
1.000
|
1.056
|
2012~2013
|
0.997
|
0.982
|
0.999
|
0.998
|
0.979
|
2013~2014
|
1.004
|
0.972
|
1.002
|
1.001
|
0.976
|
2014~2015
|
1.003
|
0.960
|
1.005
|
0.999
|
0.963
|
2015~2016
|
1.004
|
1.001
|
1.002
|
1.001
|
1.004
|
2016~2017
|
1.000
|
0.982
|
1.003
|
0.997
|
0.982
|
2017~2018
|
1.016
|
0.603
|
1.020
|
0.997
|
0.613
|
2018~2019
|
0.955
|
1.104
|
0.982
|
0.972
|
1.054
|
均值
|
1.002
|
1.019
|
1.001
|
1.001
|
1.021
|