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The aging world population requires a sustainable and high-quality healthcaresystem. To examine the efficiency of medical cooperation, medical provider andphysician networks were constructed using patient claims data. Previous studieshave shown that these networks contain information on medical cooperation.However, the usage patterns of multiple medical providers in a series ofmedical services have not been considered. In addition, these studies used onlygeneral network features to represent medical cooperation, but their expressiveability was low. To overcome these limitations, we analyzed the medicalprovider network to examine its overall contribution to the quality ofhealthcare provided by cooperation between medical providers in a series ofmedical services. This study focused on: i) the method of feature extractionfrom the network, ii) incorporation of the usage pattern of medical providers,and iii) expressive ability of the statistical model. Femoral neck fractureswere selected as the target disease. To build the medical provider networks, weanalyzed the patient claims data from a single prefecture in Japan betweenJanuary 1, 2014 and December 31, 2019. We considered four types of models: amodel using node strength and linear regression to a model using featurerepresentation by node2vec and regression tree ensemble, which is a machinelearning method. The results showed that a stronger medical provider reducesthe duration of hospital stay. The overall contribution of the medicalcooperation to the duration of hospital stay extracted from the medicalprovider network using node2vec is approximately 20%, which is approximately 20times higher than the model using strength.

Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan