Spatial Difference and Equity Analysis for Accessibility to Three-Level Medical Services Based on Actual Medical Behavior in Shaanxi, China
Abstract
:1. Introduction
2. Materials
2.1. Research Area
2.2. Data Collection
3. Methodology
3.1. Improved Network Analysis Model and Accessibility Calculation
3.1.1. Space-Time Distance Model
3.1.2. Two-Step Floating Catchment Area Method
3.2. Spatial Autocorrelation
3.3. Lorenz Curves and Gini Coefficient
4. Results
4.1. Spatial Difference in Accessibility to Three-Level Medical Services
4.1.1. Spatial Difference in Accessibility to Primary Medical Services
4.1.2. Spatial Difference in Accessibility to Secondary Medical Services
4.1.3. Spatial Difference in Accessibility to Tertiary Medical Services
4.2. Equity in Obtaining Medical Services Based on Accessibility
4.2.1. Equity of Accessibility to Medical Services in Different Areas
4.2.2. Equity of Accessibility to Medical Services in Different Groups
4.3. Sensitivity Analysis of Service Threshold and Service-Capability Weight Setting
5. Discussion
5.1. Improvement in Traffic Conditions Can Reduce Difference in Accessibility to Medical Services
5.2. Improvement in Hospital Service Level Has No Significant Effect on Accessibility Spatial Pattern
5.3. Policy Suggestion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Region | Pri_T | Sec_T | Ter_T | |||||||||
Max | Min | Mean | Moran’ I | Max | Min | Mean | Moran’ I | Max | Min | Mean | Moran’ I | |
Province | 151.68 | 0.77 | 23.90 | 0.742 | 0.15 | 0 | 4.7 × 10−3 | 0.830 | 3.1 × 10−2 | 5.3 × 10−4 | 1.7 × 10−3 | 0.847 |
Guanzhong | 132.13 | 1.12 | 18.88 | 0.762 | 0.05 | 0 | 4.8 × 10−3 | 0.819 | 2.1 × 10−2 | 9.1 × 10−4 | 2.5 × 10−3 | 0.913 |
Shaanbei | 140.87 | 1.56 | 27.14 | 0.706 | 0.15 | 0 | 6.0 × 10−3 | 0.829 | 3.1 × 10−2 | 5.5 × 10−4 | 1.3 × 10−3 | 0.688 |
Shaannan | 151.68 | 0.77 | 24.13 | 0.728 | 0.07 | 0 | 3.4 × 10−3 | 0.828 | 1.7 × 10−2 | 5.3 × 10−4 | 1.6 × 10−3 | 0.670 |
Region | Pri_S | Sec_S | Ter_S | |||||||||
Max | Min | Mean | Moran’ I | Max | Min | Mean | Moran’ I | Max | Min | Mean | Moran’ I | |
Province | 1.4 × 105 | 93 | 1.1 × 104 | 0.757 | 0.89 | 0 | 3.9 × 10−3 | 0.530 | 3.9 × 10−2 | 3.3 × 10−4 | 1.2 × 10−3 | 0.768 |
Guanzhong | 1.4 × 105 | 93 | 8.6 × 103 | 0.672 | 0.30 | 0 | 3.2 × 10−3 | 0.365 | 3.3 × 10−2 | 5.1 × 10−4 | 1.8 × 10−3 | 0.860 |
Shaanbei | 6.4 × 104 | 223 | 1.3 × 104 | 0.767 | 0.89 | 0 | 4.9 × 10−3 | 0.467 | 3.9 × 10−2 | 3.3 × 10−4 | 0.8 × 10−3 | 0.680 |
Shaannan | 7.9 × 104 | 121 | 1.0 × 104 | 0.764 | 0.48 | 0 | 3.1 × 10−3 | 0.563 | 3.5 × 10−2 | 4.0 × 10−4 | 1.0 × 10−3 | 0.576 |
Region | Pri_T | Pri_S | Sec_T | Sec_S | Ter_T | Ter_S |
---|---|---|---|---|---|---|
Province | 0.446 | 0.636 | 0.471 | 0.883 | 0.457 | 0.623 |
Guanzhong | 0.392 | 0.613 | 0.436 | 0.816 | 0.414 | 0.577 |
Shaanbei | 0.442 | 0.492 | 0.518 | 0.985 | 0.257 | 0.409 |
Shaannan | 0.459 | 0.532 | 0.479 | 0.961 | 0.215 | 0.332 |
Accessibility | Province | Shaannan | ||
---|---|---|---|---|
Aging Population | Agricultural Population | Aging Population | Agricultural Population | |
Pri_T | −0.102 | 0.327 ** | 0.199 | 0.241 |
Pri_S | −0.114 | 0.338 ** | 0.241 | 0.210 |
Sec_T | 0.079 | −0.754 ** | −0.101 | −0.754 ** |
Sec_S | 0.131 | −0.829 ** | −0.218 | −0.798 ** |
Ter_T | 0.156 | −0.747 ** | −0.417 * | −0.558 ** |
Ter_S | 0.164 | −0.752 ** | −0.510 * | −0.519 * |
Guanzhong | Shaanbei | |||
Aging Population | Agricultural Population | Aging Population | Agricultural Population | |
Pri_T | −0.203 | 0.331 * | 0.072 | −0.282 |
Pri_S | −0.230 | 0.376 ** | 0.253 | −0.161 |
Sec_T | 0.398 ** | −0.773 ** | −0.339 | −0.333 |
Sec_S | 0.468 ** | −0.854 ** | −0.426 * | −0.582 ** |
Ter_T | 0.339 * | −0.761 ** | −0.306 | −0.654 ** |
Ter_S | 0.351 ** | −0.762 ** | −0.385 | −0.662 ** |
Accessibility | Tolerance | Weight | |||||
---|---|---|---|---|---|---|---|
T = 90 | T = 120 | T = 150 | W = 1.5 | W = 2 | W = 2.5 | ||
Percentile (%) | 10 | 0 | 1.6 × 10−4 | 5.3 × 10−4 | 1.6 × 10−4 | 1.6 × 10−4 | 1.6×10−4 |
20 | 2.5 × 10−4 | 8.7 × 10−4 | 1.5 × 10−3 | 8.5 × 10−4 | 8.7 × 10−4 | 8.8×10−4 | |
30 | 9.1 × 10−4 | 1.6 × 10−3 | 2.4 × 10−3 | 1.5 × 10−3 | 1.6 × 10−3 | 1.6×10−3 | |
40 | 1.5 × 10−3 | 2.3 × 10−3 | 3.1 × 10−3 | 2.1 × 10−3 | 2.3 × 10−3 | 2.4 × 10−3 | |
50 | 2.0 × 10−3 | 3.1 × 10−3 | 3.7 × 10−3 | 2.8 × 10−3 | 3.1 × 10−3 | 3.5 × 10−3 | |
60 | 2.9 × 10−3 | 3.9 × 10−3 | 4.4 × 10−3 | 3.5 × 10−3 | 3.9 × 10−3 | 4.5 × 10−3 | |
70 | 4.1 × 10−3 | 5.0 × 10−3 | 5.1 × 10−3 | 4.4 × 10−3 | 5.0 × 10−3 | 5.8 × 10−3 | |
80 | 5.8 × 10−3 | 6.2 × 10−3 | 6.1 × 10−3 | 5.4 × 10−3 | 6.2 × 10−3 | 7.4 × 10−3 | |
90 | 8.5 × 10−3 | 8.1 × 10−3 | 7.6 × 10−3 | 7.0 × 10−3 | 8.1 × 10−3 | 9.6 × 10−3 | |
100 | 2.0 × 10−2 | 1.6 × 10−2 | 1.4 × 10−2 | 1.4 × 10−2 | 1.6 × 10−2 | 2.0 × 10-2 | |
max | 0.20 | 0.15 | 0.12 | 0.12 | 0.15 | 0.18 | |
min | 0 | 0 | 0 | 0 | 0 | 0 | |
mid | 2.4 × 10−3 | 3.5 × 10−3 | 4.0 × 10−3 | 3.2 × 10−3 | 3.5 × 10−3 | 4.0 × 10−3 | |
mean | 4.6 × 10−3 | 4.7 × 10−3 | 4.9 × 10−3 | 4.1 × 10−3 | 4.7 × 10−3 | 5.5 × 10−3 | |
std | 7.7 × 10−3 | 5.9 × 10−3 | 4.9 × 10−3 | 4.8 × 10−3 | 5.9 × 10−3 | 7.2 × 10−3 |
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Wang, K.; Bai, J.; Dang, X. Spatial Difference and Equity Analysis for Accessibility to Three-Level Medical Services Based on Actual Medical Behavior in Shaanxi, China. Int. J. Environ. Res. Public Health 2021, 18, 112. https://doi.org/10.3390/ijerph18010112
Wang K, Bai J, Dang X. Spatial Difference and Equity Analysis for Accessibility to Three-Level Medical Services Based on Actual Medical Behavior in Shaanxi, China. International Journal of Environmental Research and Public Health. 2021; 18(1):112. https://doi.org/10.3390/ijerph18010112
Chicago/Turabian StyleWang, Kan, Jianjun Bai, and Xing Dang. 2021. "Spatial Difference and Equity Analysis for Accessibility to Three-Level Medical Services Based on Actual Medical Behavior in Shaanxi, China" International Journal of Environmental Research and Public Health 18, no. 1: 112. https://doi.org/10.3390/ijerph18010112