Mobile signaling big data, healthcare-seeking flows, and multidimensional healthcare access in Shanghai

Implications for healthcare supply–demand matching and medical security governance

Bibliographic Data

ID22068255
AuthorsQing Guo (0009-0007-0292-6930, University of Shanghai for Science and Technology, corresponding author), Hengna Ren (Shanghai University of Engineering Science), Xinmiao Shao (University of Shanghai for Science and Technology), Wenxiao Yang (0000-0003-3391-9593, University of Shanghai for Science and Technology)
Year2026
Volume14
Pages1841112-1841112
Publication date2026-06-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1841112
PMID42311999
OpenAlexW7163155492
LanguageEN
References cited54

Background/purpose: Broad medical insurance coverage alone does not ensure that a multilevel medical security system works effectively. In a megacity, the key issue is whether residents can reach suitable care, keep choices across provider tiers, and use high-quality services within daily time-space constraints. Proximity-based measures often miss this problem because they do not capture cross-district healthcare-seeking, preferences for higher-level hospitals, or the concentration of quality resources in limited urban locations. Using Shanghai as a case, this study used Mobile signaling big data to identify spatial inequalities in healthcare access and to inform service-side improvement. Methods: This study used anonymized mobile signaling records from March 2019 to reconstruct a directed, weighted healthcare-seeking flow network linking demand units with 352 hospitals in Shanghai. This study then constructed the Multidimensional Healthcare Access Capability Index (MHACI) with entropy-weighted TOPSIS. The index integrated spatial accessibility, healthcare-seeking choice diversity, and connectivity to high-quality healthcare resources. Multiscale geographically weighted regression (MGWR) was used to estimate associations of MHACI with demographic structure, economic capacity, transport infrastructure, population density, and local healthcare capacity across space. Results: Healthcare-seeking flows in Shanghai were concentrated toward the urban core, with cross-district movement. MHACI showed a clear center-periphery gradient. Aging share was positively related to MHACI mainly in central and adjacent areas, whereas child share was linked to lower MHACI in core districts. Per capita GDP and local healthcare capacity had positive but localized effects. Population density shifted from a crowding burden in central areas to an agglomeration advantage in peripheral areas, while transport infrastructure mainly acted as a background condition. Conclusion: Unequal healthcare access in Shanghai reflects a mismatch between fixed healthcare provision and healthcare-seeking flows across urban space. Improving a multilevel medical security system requires not only formal coverage, but also stronger primary care, better connectivity across provider tiers, and place-specific governance in core, peri-urban, and outer suburban areas

Health care · Healthcare system · Medical home · Per capita · Population · Global Health Care Issues · Healthcare Policy and Management · Healthcare Systems and Reforms

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