Year: 2022
Type: article
Study design: Observational Study
Abstract: Intercity patient mobility reflects the geographic mismatch between healthcare resources and population, and has rarely been studied with big data at large spatial scales. In this paper, we investigated the patterns of intercity patient mobility and factors influencing this behavior with more than 4 million hospitalization records of patients with chronic kidney disease in China. In order to provide practical policy recommendations, a role identification framework informed by complex network theory was proposed considering the strength and distribution of connections of cities in mobility network. Such a mobility network has formed multiscale community structures with the characteristic of "universal administrative constraints and a few boundary breaches". We discovered that cross-module visits which account for only 20% of the total visits produced more than 50% of the total travel distance. The explainable machine learning modeling results revealed that the distance had a power-law-like effect on flow volume, and high-quality healthcare resources were also an important driving factor. This paper provides not only a methodological reference for patient mobility studies but also offers valuable insights into public health policies.
Source: Cities
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $2,310
Awards: G104374653, G1227569118, G1585107247, G1930372441, G1965971194, G2366243032, G2560198807, G3432524871, G3584181854, G3598855245, G3840007528, G3910816902, G417417726, G4431910321, G4640135000, G4692697990, G4702341551, G4837035344, G4883020797, G5599278713, G5631124847, G583325053, G6059361768, G6190165079, G6252488297, G6269038257, G6679757348, G7120928233, G7337274960, G7381982869, G740128091, G7570687216, G7672769242, G7682462662, G777186803, G7801657285, G7852613056, G8245341833, G8819262171
OpenAlex ID: W4295836091