Can Smart Contracts Change the Health Insurance Payment Chain to Improve the Quality of Hospital Services: A Simulation Test Based on China

OBJECTIVES: This study examines whether smart contracts can revolutionize the health insurance payment chain to improve the quality of hospital services in China. Utilizing a simulation test, we investigate the potential changes in efficiency, transparency, and overall service quality resulting from the implementation of blockchain-based smart contracts in healthcare payments.

METHODS: A systematic investigation was conducted using secondary data from electronic health records, healthcare claims, and insurance registries. The study employed a cohort simulation model to predict the outcomes of integrating smart contracts into the existing health insurance payment processes. The simulation analyzed variables such as payment processing times, error rates, administrative costs, and patient satisfaction levels. Additionally, decision analysis techniques were used to compare the traditional payment model with the proposed smart contract model in terms of cost-effectiveness and service quality.

RESULTS: The simulation results indicated a significant reduction in payment processing times and administrative costs when using smart contracts. Error rates in claims processing were also notably lower, leading to fewer disputes and faster reimbursements. Improved transparency and automation in the payment chain enhanced trust among stakeholders, which correlated with higher patient satisfaction scores. Ultimately, hospitals experienced improvements in service quality, attributed to the streamlined payment processes and reduced administrative burdens.

CONCLUSIONS: The integration of smart contracts into the health insurance payment chain has the potential to substantially improve the quality of hospital services in China. By reducing inefficiencies and enhancing transparency, smart contracts can facilitate quicker, more accurate payments, allowing healthcare providers to focus more on patient care. Further empirical studies and pilot implementations are recommended to validate these findings and address any potential challenges in real-world applications.