Summary Background Quality improvement methods can identify solutions and make dramatic improvements in patient safety during daily clinical care. The science of quality improvement in healthcare is still a very new concept in developing countries like China. Aims We initiated a quality improvement project to minimize adverse respiratory events in our postanesthesia care unit with the guidance of an experienced quality improvement expert from Cincinnati Children's Hospital Medical Center. Methods We set up a quality improvement team that included anesthesia safety team members at Shanghai Children's Medical Center, and a quality improvement expert in pediatric anesthesia from Cincinnati Children's Hospital Medical Center. Data from the previous year were reviewed. After using Failure Mode and Effect Analysis to access risks associated with the current process, a Key Driver Diagram and a Smart Aim were developed. Key drivers included establishing a safety culture, resource allocation to meet needs, education and training, standardization of care, improved communication and handoff, and enhanced detection, recognition, and response to adverse events. Using Plan‐Do‐Study‐Act cycles of the improvement model, interventions were conducted to improve the process. The primary outcome was the percentage of postoperative respiratory adverse events in the postanesthesia care unit, and we calculated the average recovery time as a balancing measure. Data were collected and analyzed using a run chart and control chart. Results The median percentage of respiratory adverse events in postanesthesia care unit decreased from 2.8% to 1.4%. Respiratory adverse events were reduced by over 30% compared to the previous period with no significant change in mean recovery time. Conclusion Using quality improvement methods, we successfully reduced the percentage of respiratory adverse events in the postanesthesia care unit. This helped to establish a safety culture among the anesthesia staff. Quality and safety improvement can be successfully implemented in developing countries like China with collaboration with quality improvement experts from more experienced institutions.

In order to encourage residents to go to primary care facilities, China has set up differentiated basic medical insurance reimbursement ratios. The study aims to use the dynamic point of view of longitudinal data to examine the changes in the impact of basic medical insurance on primary care. The data for this study comes from the Chinese Family Panel Study (CFPS) in 2010, 2012, 2014, 2016, and 2018. We adopted Hierarchal Age-period-cohort-Cross-Classified Random Effects Models (HAPC-CCREM) to examine the changes in the impact of basic medical insurance on primary care. Compared with non-insured groups, participants of the New Rural Cooperative Medical System (coefficient = 0.730) have a relatively high incidence of primary care seeks, while Urban Residents' Basic Medical Insurance (coefficient = −0.482) and Urban Employees' Basic Medical Insurance (coefficient = −0.663) are lower, respectively. Age, period over time and cohort have a more obvious moderating effect on primary care seeks. The study of primary care behavior is an important direction for the construction of a hierarchical medical system. As basic medical insurance is the source of power for the hierarchical medical system, we can provide certain direction for policy formulation on the changes of basic medical insurance in primary care behavior.