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A Method for Assessing the Fairness of Health Resource Allocation Based on Geographical Grid

Jin Han1, Wenhao Jiang1, Jin Shi2, *, Sun Xin2, Jin Peng2, Haibo Liu3

1 School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
2 School of Information Management, Nanjing University, Nanjing, 210036, China.
3 Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, UK.

* Corresponding Author: Jin Shi. Email: email.

Computers, Materials & Continua 2020, 64(2), 1171-1184.


The assessment of the fairness of health resource allocation is an important part of the study for the fairness of social development. The data used in most of the existing assessment methods comes from statistical yearbooks or field survey sampling. These statistics are generally based on administrative areas and are difficult to support a fine-grained evaluation model. In response to these problems, the evaluation method proposed in this paper is based on the query statistics of the geographic grid of the target area, which are more accurate and efficient. Based on the query statistics of hot words in the geographic grids, this paper adopts the maximum likelihood estimation method to estimate the population in the grid region. Then, according to the statistical yearbook data of Hunan province, the estimated number and actual number of hospitals in each grid are analyzed and compared to measure the fairness of health resource allocation in the target region. Experiments show that the geographical grid population assessment based on hot words is more accurate and close to the actual value. The estimated average error is only about 17.8 percent. This method can assess the fairness of health resource allocation in any scale, and is innovative in data acquisition and evaluation methods.


Cite This Article

J. Han, W. Jiang, J. Shi, S. Xin, J. Peng et al., "A method for assessing the fairness of health resource allocation based on geographical grid," Computers, Materials & Continua, vol. 64, no.2, pp. 1171–1184, 2020.


cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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