Objective: The paper attempts to investigate the configurational pathways of provincial-level medical insurance fund fraud risk exposure and provide policy implications for classified supervision and precise governance of medical insurance funds. Methods: Based on 2023 cross-sectional data from 31 provincial-level administrative regions in China, this study selected five condition variables: economic development level, aging population level, fund expenditure pressure, information infrastructure level, and complexity of healthcare service supply. Drawing on Routine Activity Theory, this study constructed an analytical framework and employed fuzzy-set qualitative comparative analysis (fsQCA) to identify configurational paths. The outcome variable was measured as the number of investigated and confirmed violators per 100000 insured persons, reflecting the provincial-level verified exposure level of medical insurance violations after regulatory identification, investigation, and recording. Results: No single condition or its negation constitutes a necessary condition for medical insurance fund fraud risk exposure. Three configurational paths for provincial high-risk exposure were identified: "high foundation-high pressure-high IT infrastructure type", "low foundation-high pressure-low IT infrastructure type", and "low foundation-aging-complex service supply type". Conclusions: Medical insurance fund fraud risk exposure is characterized by multi-condition conjunctive causation and path heterogeneity. Higher levels of information infrastructure may enhance the traceability of medical service utilization and billing, facilitating the detection and verification of fraudulent behaviors. The supervision of medical insurance funds should adopt classified governance based on the risk exposure mechanisms specific to different regions.
Key words
medical insurance fund fraud /
risk exposure /
medical insurance fund governance /
Routine Activity Theory /
fsQCA
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