Analysis of medical costs and two-model prediction for patients with severe mental disorders in Gansu Province, China

Outpatient costs continued to decline, while inpatient costs increased significantly. In predicting outpatient costs, the Bayesian regression model based on Gaussian processes performed relatively well but its overall predictive capability remained limited; the Random Forest model demonstrated superior performance in predicting inpatient costs. The study suggests that in underdeveloped regions, data-driven cost analysis should be prioritized to optimize the allocation of mental health resources and alleviate the economic burden.