Geographical accessibility to healthcare by point-of–interest data from online maps: a comparative study

Submitted: 19 June 2024
Accepted: 21 November 2024
Published: 20 December 2024
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Geographical accessibility is important for promoting health equity, and calculating it requires the locations of all existing healthcare facilities in a region. Authoritative location data collected by governments is accurate but mostly not publicly available, while point-of-interest (POI) data from online sources, such as Baidu Maps and AutoNavi Maps are easily accessible. However, the accuracy of the latter has not been thoroughly analyzed. Taking Baotou, a medium-sized city in China, as aneample, we assessed the suitability of using POI data for measuring geographic accessibility to healthcare facilities.We computedthe difference of geographic accessibility calculated based on POI data and that on authoritative data.Logistic regression and a multiple linear regression model was applied to identify factors related to the consistency between the two data sources. Compared to authoritative data, POI data exhibited discrepancies, with completeness of 54.9% and accuracy of 63.7%. Geographic accessibility calculated based on both data showed similar patterns, with good consistency for hospitals and in urban areas. However, large differences (>30 minutes) were shown in rural areas for primary healthcare facilities. The differences were small regarding to population- weighted average accessibility (with slight underestimation of 3.07 minutes) and population coverage across various levels of accessibility (with differences less than 1% of the population) for the entire area. In conclusion, POI data can be considered foruse in both urban areas and at the level of entire city; however, awareness should be raised in rural areas.

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How to Cite

Huang-fu, H.-Q., Zhang, N., Wang, L., Liang, H.-J., Xian, B.-S., Gan, X.-F., & Lai, Y. (2024). Geographical accessibility to healthcare by point-of–interest data from online maps: a comparative study. Geospatial Health, 19(2). https://doi.org/10.4081/gh.2024.1322

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