Introduction
Research design
Methodology
The Malmquist productivity index (MPI)
Data sources and indicator selection
Project | Inputs/Outputs | Abbreviation | Measurement and Explanations | References |
---|---|---|---|---|
Input indicators | Healthcare expenditure per capita (yuan) | PPP | Total rural medical and health expenditure / rural population. This input is related to financial health expenditure per capita in rural areas, | |
Total expenditure on health (% GDP) | EXP | Total rural medical and health expenditure / GDP × 100%. This input represents the degree of government emphasis on health and its fiscal functions. | ||
health institution outputs | Number of village clinics per thousand rural population (unit) | NC | Number of village clinics / (rural population × 1000). This output reflects the health level of the rural residents near a village clinic. | |
Number of township health centers per thousand rural population (unit) | NTH | Number of township health centers / (rural population × 1000). This output describes the health level of the rural residents near a township health center. | ||
health technical personnel outputs | Village doctors and assistants per 1000 rural population (ren) | DA | Village doctors and assistants / (rural population × 1000). This output explains the level of human resources in a village clinic. | |
Doctors of township health centers per 1000 rural population (ren) | DTH | Doctors of township health centers / (rural population × 1000). This output indicates the proportion of doctors in the township health centers per 1000 rural population. | ||
Licensed (assistant) doctors of township health centers per 1000 rural population (ren/1000) | LDT | Licensed (assistant) doctors of township health centers / (rural population × 1000). This output indicates the technical level of the medical staff in rural areas. | ||
Registered nurses of township health centers per 1000 rural population (ren/1000) | NTH | Registered nurses of township health centers / (rural population × 1000). This output indicates the technical level of nurses in rural areas. | ||
health facility outputs | Beds per 1000 rural population (beds) | BED | Beds of medical institutions / (rural population × 1000). This output indicates the relative number of beds provided by health institutions. | |
utilization rate of health resource outputs | Outpatients per 1000 rural population (person-times) | NV | Outpatients in township health centers / rural population × 1000.This output describes the outpatient service level. | |
Number of inpatients (person) | NI | Number of inpatients in township health centers / rural population × 1000. This output describes the inpatient service level. | ||
Utilization rate of beds (%) | UB | Actual bed days used / actual available bed days × 100%. The key indicator evaluating bed efficiency. | ||
Average duration of hospitalization (day) | ADH | Total number of bed days occupied by discharged persons/total number of discharged persons. This output describes the extent of health care resource utilization. |
Correlation Coefficient | PPP | EXP | NC | NTH | DA | DTH | LDT | NTH | BED | NV | NI | UB | ADH |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PPP | 1.000 | .561a | .403a | .716a | .337a | .169a | .216a | .195a | .492a | .223a | -.215a | -.209a | .207a |
EXP | 0.561a | 1.000 | .355a | .703a | .294a | -.384a | -.143b | -.196a | -.117b | -.204a | -.136b | -.216a | -.204a |
NC | 0.403a | .355a | 1.000 | .532a | .741a | -.185a | .215a | 0.039 | .131b | -.229a | -0.024 | -.233a | -.200a |
NTH | 0.716a | .703a | .532a | 1.000 | .320a | 0.041 | -0.062 | -.210a | 0.098 | .187a | -.274a | -.314a | .150a |
DA | .337a | .294a | .741a | .320a | 1.000 | -.197a | .166a | 0.034 | .113b | -.325a | 0.078 | -.135b | -.289a |
DTH | .169a | -.384a | -.185a | 0.041 | -.197a | 1.000 | -0.037 | 0.039 | .351a | .660a | -0.040 | 0.090 | .587a |
LDT | .216a | -.143b | .215a | -0.062 | .166a | -0.037 | 1.000 | .887a | .598a | -.215a | 0.111 | -0.023 | -.141b |
NTH | .195a | -.196a | 0.039 | -.210a | 0.034 | 0.039 | .887a | 1.000 | .636a | -.185a | .246a | 0.080 | -.130b |
BED | .492a | -.117b | 0.131b | 0.098 | .113b | .351a | .598a | .636a | 1.000 | .262a | .160a | .164a | .319a |
NV | .223a | -.204a | -.229a | .187a | -.325a | .660a | -.215a | -.185a | .262a | 1.000 | -0.103 | .294a | .958a |
NI | -.215a | -.136b | -0.024 | -.274a | 0.078 | -0.040 | 0.111 | .246a | .160a | -0.103 | 1.000 | .774a | -.115b |
UB | -.209a | -.216a | -.233a | -.314a | -.135b | 0.090 | -0.023 | 0.080 | .164a | .294a | .774a | 1.000 | .326a |
ADH | .207a | -.204a | -.200a | .150a | -.289a | .587a | -.141b | -.130b | .319a | .958a | -.115b | .326a | 1.000 |
KMO-Measure of Sampling Adequacy | 0.601 | |
Bartlett Test of Sphericity | Approx. Chi-Square | 2922.019 |
df | 55 | |
sig | 0 |
Component | Initial Eigenvalues | Extract Sums of Squared Loadings | ||||
---|---|---|---|---|---|---|
Total | Variance % | Cumulative % | Total | Variance % | Cumulative % | |
1 | 3.066 | 27.872 | 27.872 | 3.066 | 27.872 | 27.872 |
2 | 2.619 | 23.811 | 51.683 | 2.619 | 23.811 | 51.683 |
3 | 2.164 | 19.677 | 71.360 | 2.164 | 19.677 | 71.360 |
4 | 1.476 | 13.423 | 84.783 | 1.476 | 13.423 | 84.783 |
5 | 0.569 | 5.172 | 89.954 | |||
6 | 0.424 | 3.854 | 93.808 | |||
7 | 0.286 | 2.599 | 96.407 | |||
8 | 0.196 | 1.786 | 98.193 | |||
9 | 0.101 | 0.919 | 99.112 | |||
10 | 0.070 | 0.637 | 99.749 | |||
11 | 0.028 | 0.251 | 100 |
Component | ||||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
NC | -0.558 | 0.111 | 0.615 | 0.406 |
NTH | -0.112 | -0.179 | 0.790 | 0.213 |
DA | -0.590 | 0.134 | 0.433 | 0.475 |
DTH | 0.692 | 0.178 | 0.326 | -0.088 |
LDT | -0.290 | 0.840 | 0.119 | -0.309 |
NTH | -0.175 | 0.894 | -0.049 | -0.323 |
BED | 0.193 | 0.806 | 0.356 | -0.071 |
NV | 0.900 | 0.004 | 0.361 | 0.093 |
NI | 0.035 | 0.477 | -0.504 | 0.651 |
UB | 0.439 | 0.373 | -0.460 | 0.623 |
ADH | 0.871 | 0.067 | 0.360 | 0.090 |
Component | ||||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
NC | -0.319 | 0.069 | 0.418 | 0.334 |
NTH | -0.064 | -0.111 | 0.537 | 0.175 |
DA | -0.337 | 0.083 | 0.294 | 0.391 |
DTH | 0.395 | 0.110 | 0.222 | -0.072 |
LDT | -0.166 | 0.519 | 0.081 | -0.254 |
NTH | -0.100 | 0.552 | -0.033 | -0.266 |
BED | 0.110 | 0.498 | 0.242 | -0.058 |
NV | 0.514 | 0.002 | 0.245 | 0.077 |
NI | 0.020 | 0.295 | -0.343 | 0.536 |
UB | 0.251 | 0.230 | -0.313 | 0.513 |
ADH | 0.497 | 0.041 | 0.245 | 0.074 |
Results of empirical analysis and discussion
Analysis of health expenditure efficiency (HEE) in rural China
Provinces | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | Average |
---|---|---|---|---|---|---|---|---|---|---|---|
Beijing (E) | 0.513 | 0.515 | 0.482 | 0.534 | 0.544 | 0.548 | 0.534 | 0.538 | 0.576 | 1.015 | 0.580 |
Tianjin (E) | 0.740 | 0.728 | 0.573 | 0.653 | 0.613 | 0.627 | 0.579 | 0.563 | 0.625 | 0.998 | 0.670 |
Hebei (E) | 0.858 | 0.709 | 0.459 | 0.525 | 0.484 | 0.517 | 0.501 | 0.486 | 0.473 | 0.543 | 0.555 |
Shanxi (C) | 1.007 | 0.627 | 0.455 | 1.005 | 0.473 | 0.477 | 0.462 | 0.419 | 0.381 | 0.393 | 0.570 |
Inner Mongolia (W) | 1.013 | 0.670 | 0.475 | 0.550 | 0.513 | 0.533 | 0.534 | 0.573 | 0.629 | 1.010 | 0.650 |
Liaoning (NE) | 0.833 | 0.820 | 0.589 | 0.728 | 0.675 | 0.720 | 0.736 | 0.645 | 0.645 | 0.598 | 0.699 |
Jinlin (NE) | 0.715 | 0.646 | 0.442 | 0.501 | 0.473 | 0.490 | 0.428 | 0.432 | 0.372 | 0.388 | 0.489 |
Heilongjiang (NE) | 0.812 | 0.729 | 0.501 | 0.574 | 0.471 | 0.525 | 0.541 | 0.483 | 0.470 | 0.514 | 0.562 |
Shanghai (E) | 1.126 | 1.013 | 1.004 | 1.009 | 1.031 | 0.956 | 1.006 | 1.009 | 0.953 | 1.004 | 1.011 |
Jiangsu (E) | 0.837 | 0.788 | 0.637 | 1.011 | 0.759 | 0.743 | 0.773 | 0.836 | 0.815 | 1.038 | 0.824 |
Zhejiang (E) | 0.595 | 0.548 | 0.423 | 0.450 | 0.331 | 0.319 | 0.304 | 0.299 | 0.355 | 1.023 | 0.465 |
Anhui (C) | 0.674 | 0.599 | 0.452 | 0.485 | 0.383 | 0.395 | 0.391 | 0.396 | 0.409 | 0.476 | 0.466 |
Fujian (E) | 0.841 | 0.745 | 0.578 | 0.777 | 0.670 | 0.734 | 0.739 | 0.666 | 0.643 | 0.685 | 0.708 |
Jiangxi (C) | 0.674 | 0.788 | 0.462 | 0.533 | 0.529 | 0.701 | 0.636 | 0.544 | 0.547 | 0.586 | 0.600 |
Shandong (E) | 1.107 | 0.933 | 0.698 | 1.050 | 0.872 | 1.004 | 1.027 | 0.891 | 0.850 | 1.014 | 0.945 |
Henan (C) | 0.767 | 0.763 | 0.490 | 0.556 | 0.476 | 0.494 | 0.488 | 0.487 | 0.494 | 0.539 | 0.555 |
Hubei (C) | 0.846 | 0.726 | 0.539 | 0.695 | 0.614 | 0.722 | 0.789 | 0.855 | 0.873 | 1.018 | 0.768 |
Hunan (C) | 1.066 | 1.007 | 0.581 | 0.729 | 0.635 | 0.730 | 0.748 | 0.739 | 0.853 | 1.018 | 0.810 |
Guangdong (E) | 1.070 | 0.791 | 0.637 | 0.927 | 0.603 | 0.573 | 0.556 | 0.504 | 0.481 | 0.489 | 0.663 |
Guangxi (W) | 0.694 | 0.611 | 0.384 | 0.452 | 0.397 | 0.450 | 0.513 | 0.489 | 0.478 | 0.497 | 0.497 |
Hainan (E) | 0.605 | 0.508 | 0.356 | 0.389 | 0.301 | 0.287 | 0.293 | 0.283 | 0.280 | 0.280 | 0.358 |
Chongqing (W) | 1.020 | 1.016 | 1.011 | 1.023 | 0.707 | 0.981 | 1.008 | 0.820 | 0.832 | 1.043 | 0.946 |
Sichuan (W) | 0.714 | 0.719 | 0.515 | 0.591 | 0.536 | 0.669 | 0.685 | 0.678 | 0.685 | 1.000 | 0.679 |
Guizhou (W) | 0.413 | 0.388 | 0.278 | 0.333 | 0.298 | 0.327 | 0.377 | 0.349 | 0.355 | 0.393 | 0.351 |
Yunan (W) | 0.404 | 0.380 | 0.277 | 0.321 | 0.298 | 0.333 | 0.368 | 0.369 | 0.364 | 0.407 | 0.352 |
Tibet (W) | 0.287 | 0.305 | 0.239 | 0.251 | 0.503 | 0.523 | 0.722 | 1.009 | 1.011 | 1.012 | 0.586 |
Shaanxi (W) | 0.755 | 0.607 | 0.411 | 0.470 | 0.440 | 0.516 | 0.532 | 0.534 | 0.525 | 0.617 | 0.541 |
Gansu (W) | 0.352 | 0.400 | 0.294 | 0.357 | 0.302 | 0.344 | 0.344 | 0.334 | 0.322 | 0.352 | 0.340 |
Qinghai (W) | 0.321 | 0.317 | 0.243 | 0.287 | 0.311 | 0.316 | 0.329 | 0.334 | 0.269 | 0.297 | 0.302 |
Ningxia (W) | 0.383 | 0.399 | 0.275 | 0.340 | 0.341 | 0.339 | 0.327 | 0.307 | 0.314 | 0.336 | 0.336 |
Xinjiang (W) | 0.522 | 0.482 | 0.333 | 0.537 | 0.553 | 0.589 | 0.744 | 0.862 | 0.861 | 1.011 | 0.649 |
Annual average | 0.728 | 0.654 | 0.487 | 0.601 | 0.520 | 0.564 | 0.581 | 0.572 | 0.572 | 0.697 | 0.598 |
Analysis of dynamic health expenditure efficiency (DHEE) in rural China
Provinces | 2007–2008 | 2008–2009 | 2009–2010 | 2010–2011 | 2011–2012 | 2012–2013 | 2013–2014 | 2014–2015 | 2015–2016 | Average |
---|---|---|---|---|---|---|---|---|---|---|
Beijing (E) | 1.074 | 0.995 | 1.031 | 1.037 | 1.002 | 1.005 | 1.018 | 1.022 | 1.073 | 1.028 |
Tianjin (E) | 1.012 | 0.876 | 1.183 | 1.015 | 0.992 | 0.919 | 0.981 | 1.066 | 1.116 | 1.014 |
Hebei (E) | 0.791 | 0.737 | 1.147 | 0.869 | 0.990 | 0.875 | 0.921 | 0.927 | 1.086 | 0.919 |
Shanxi (C) | 0.806 | 0.811 | 1.305 | 0.820 | 0.950 | 0.943 | 0.905 | 0.903 | 1.075 | 0.936 |
Inner Mongolia (W) | 0.859 | 0.950 | 1.158 | 0.914 | 1.035 | 0.952 | 1.011 | 0.990 | 1.008 | 0.983 |
Liaoning (NE) | 0.918 | 0.750 | 1.283 | 0.949 | 1.003 | 0.950 | 0.903 | 0.999 | 0.922 | 0.955 |
Jinlin (NE) | 0.860 | 0.679 | 1.274 | 0.927 | 0.981 | 0.919 | 0.977 | 0.869 | 1.008 | 0.932 |
Heilongjiang (NE) | 0.853 | 0.701 | 1.166 | 0.867 | 1.028 | 0.942 | 0.855 | 0.913 | 1.055 | 0.922 |
Shanghai (E) | 0.945 | 0.911 | 1.065 | 1.031 | 0.967 | 0.998 | 0.945 | 0.941 | 0.936 | 0.97 |
Jiangsu (E) | 0.899 | 0.752 | 1.332 | 0.953 | 1.050 | 1.041 | 1.034 | 0.977 | 1.084 | 1.003 |
Zhejiang (E) | 0.905 | 0.761 | 1.546 | 0.983 | 1.114 | 1.063 | 1.043 | 1.104 | 1.115 | 1.053 |
Anhui (C) | 0.814 | 0.714 | 0.996 | 0.722 | 0.982 | 0.932 | 0.950 | 0.973 | 1.123 | 0.903 |
Fujian (E) | 0.966 | 0.851 | 1.287 | 0.869 | 1.020 | 0.949 | 0.930 | 0.988 | 1.061 | 0.984 |
Jiangxi (C) | 1.050 | 0.737 | 1.101 | 0.916 | 1.002 | 0.877 | 0.853 | 0.946 | 1.009 | 0.937 |
Shandong (E) | 0.913 | 0.807 | 1.308 | 0.903 | 1.032 | 0.999 | 0.918 | 0.973 | 1.025 | 0.978 |
Henan (C) | 0.917 | 0.697 | 1.144 | 0.829 | 0.896 | 0.886 | 0.907 | 0.937 | 1.017 | 0.907 |
Hubei (C) | 0.855 | 0.705 | 1.177 | 0.839 | 1.062 | 0.938 | 0.933 | 0.944 | 1.038 | 0.934 |
Hunan (C) | 0.928 | 0.751 | 1.197 | 0.833 | 0.984 | 0.933 | 0.911 | 0.986 | 1.049 | 0.945 |
Guangdong (E) | 0.864 | 0.779 | 1.233 | 0.753 | 0.910 | 0.921 | 0.833 | 0.948 | 0.972 | 0.904 |
Guangxi (W) | 0.888 | 0.671 | 1.084 | 0.745 | 1.053 | 1.030 | 0.880 | 0.922 | 0.969 | 0.906 |
Hainan (E) | 0.800 | 0.653 | 1.130 | 0.776 | 0.923 | 0.922 | 0.900 | 0.935 | 0.983 | 0.882 |
Chongqing (W) | 0.937 | 0.816 | 1.205 | 0.841 | 1.042 | 0.981 | 0.924 | 0.952 | 1.097 | 0.97 |
Sichuan (W) | 0.927 | 0.760 | 1.168 | 0.798 | 1.017 | 0.919 | 0.919 | 0.938 | 0.995 | 0.931 |
Guizhou (W) | 0.884 | 0.694 | 1.002 | 0.790 | 1.044 | 0.947 | 0.827 | 0.923 | 1.031 | 0.897 |
Yunan (W) | 0.860 | 0.706 | 1.097 | 0.856 | 1.063 | 1.016 | 0.948 | 0.940 | 1.041 | 0.94 |
Tibet (W) | 0.992 | 0.624 | 1.066 | 1.164 | 1.059 | 1.010 | 0.983 | 0.916 | 1.016 | 0.969 |
Shaanxi (W) | 0.785 | 0.673 | 1.199 | 0.921 | 0.997 | 0.906 | 0.939 | 0.939 | 1.094 | 0.928 |
Gansu (W) | 0.792 | 0.680 | 1.098 | 0.779 | 1.086 | 0.949 | 0.902 | 0.910 | 1.014 | 0.902 |
Qinghai (W) | 1.060 | 0.763 | 1.227 | 0.968 | 0.936 | 0.972 | 0.994 | 0.891 | 1.064 | 0.979 |
Ningxia (W) | 0.803 | 0.611 | 1.080 | 0.934 | 0.958 | 0.905 | 0.907 | 0.985 | 1.028 | 0.902 |
Xinjiang (W) | 1.006 | 0.717 | 1.576 | 0.977 | 1.024 | 1.079 | 0.977 | 0.977 | 1.075 | 1.026 |
Annual average | 0.898 | 0.748 | 1.182 | 0.884 | 1.005 | 0.956 | 0.932 | 0.955 | 1.037 | 0.949 |
Provinces | effch | techch | pech | sech | tfpch |
---|---|---|---|---|---|
Beijing (E) | 1.007 | 1.021 | 1.000 | 1.007 | 1.028 |
Tianjin (E) | 1.021 | 0.993 | 1.002 | 1.019 | 1.014 |
Hebei (E) | 1.006 | 0.913 | 1.001 | 1.006 | 0.919 |
Shanxi (C) | 0.998 | 0.938 | 1.000 | 0.998 | 0.936 |
Inner Mongolia (W) | 0.993 | 0.990 | 1.000 | 0.993 | 0.983 |
Liaoning (NE) | 1.006 | 0.949 | 1.003 | 1.003 | 0.955 |
Jinlin (NE) | 0.987 | 0.945 | 0.989 | 0.998 | 0.932 |
Heilongjiang (NE) | 0.992 | 0.929 | 1.006 | 0.986 | 0.922 |
Shanghai (E) | 1.000 | 0.970 | 1.000 | 1.000 | 0.970 |
Jiangsu (E) | 1.006 | 0.997 | 1.005 | 1.001 | 1.003 |
Zhejiang (E) | 1.022 | 1.030 | 1.012 | 1.010 | 1.053 |
Anhui (C) | 1.003 | 0.900 | 1.013 | 0.990 | 0.903 |
Fujian (E) | 0.990 | 0.994 | 0.993 | 0.997 | 0.984 |
Jiangxi (C) | 1.008 | 0.930 | 1.007 | 1.001 | 0.937 |
Shandong (E) | 1.000 | 0.978 | 1.000 | 1.000 | 0.978 |
Henan (C) | 0.991 | 0.915 | 0.994 | 0.997 | 0.907 |
Hubei (C) | 1.000 | 0.934 | 1.001 | 0.998 | 0.934 |
Hunan (C) | 1.000 | 0.945 | 1.000 | 1.000 | 0.945 |
Guangdong (E) | 0.964 | 0.938 | 0.979 | 0.984 | 0.904 |
Guangxi (W) | 0.983 | 0.922 | 0.987 | 0.995 | 0.906 |
Hainan (E) | 0.958 | 0.920 | 0.970 | 0.988 | 0.882 |
Chongqing (W) | 1.000 | 0.970 | 1.000 | 1.000 | 0.970 |
Sichuan (W) | 1.010 | 0.921 | 1.018 | 0.993 | 0.931 |
Guizhou (W) | 0.999 | 0.898 | 1.006 | 0.993 | 0.897 |
Yunan (W) | 1.030 | 0.912 | 1.032 | 0.999 | 0.940 |
Tibet (W) | 1.070 | 0.906 | 1.000 | 1.070 | 0.969 |
Shaanxi (W) | 1.008 | 0.921 | 1.007 | 1.001 | 0.928 |
Gansu (W) | 1.012 | 0.892 | 1.011 | 1.001 | 0.902 |
Qinghai (W) | 1.040 | 0.941 | 1.058 | 0.983 | 0.979 |
Ningxia (W) | 0.991 | 0.909 | 1.007 | 0.984 | 0.902 |
Xinjiang (W) | 1.009 | 1.017 | 1.024 | 0.985 | 1.026 |
Average | 1.003 | 0.946 | 1.004 | 0.999 | 0.949 |
Year | effch | techch | pech | sech | tfpch |
---|---|---|---|---|---|
2007–2008 | 1.009 | 0.890 | 1.020 | 0.990 | 0.898 |
2008–2009 | 0.952 | 0.785 | 0.957 | 0.995 | 0.748 |
2009–2010 | 0.999 | 1.183 | 1.007 | 0.992 | 1.182 |
2010–2011 | 1.016 | 0.870 | 1.021 | 0.996 | 0.884 |
2011–2012 | 1.015 | 0.990 | 1.016 | 0.999 | 1.005 |
2012–2013 | 1.004 | 0.952 | 1.000 | 1.004 | 0.956 |
2013–2014 | 1.017 | 0.916 | 1.007 | 1.010 | 0.932 |
2014–2015 | 0.988 | 0.966 | 0.989 | 0.999 | 0.955 |
2015–2016 | 1.028 | 1.008 | 1.021 | 1.007 | 1.037 |
Average | 1.003 | 0.946 | 1.004 | 0.999 | 0.949 |