The national maternal near miss surveillance in China: A facility-based surveillance system covered 30 provinces

To introduce the National Maternal Near Miss Surveillance System (NMNMSS) in detail and to report the composition of maternal near miss (MNM) in China. The NMNMSS was established by the National Health Commission at the end of 2010, covered over 400 health facilities from 30 provinces in China. The NMNMSS was designed to collect individual information for every pregnant woman admitted to obstetric department in the sampled health facilities. Cross tabulations and correlations were used to describe the distribution of population and sampled facilities in the NMNMSS, and to calculate the MNM mortality ratio for different complications and organ dysfunctions. The individual survey forms of 9,051,638 pregnant women were collected in the NMNMSS between 2012 and 2017. Compared with urban areas, there are very few well-quality medical resources in rural areas. Most women with pregnancy complications in rural areas can only be treated in Level 2 and lower hospitals. MNM in women with indirect obstetric complications received treatment more frequently in Level 3 hospital. The most common maternal complications in severe maternal outcomes (including maternal near miss and maternal death) are obstetrics hemorrhage (58.7%), hypertension disorder (28.0%), and severe anemia (20.6%). The overall MNM mortality ratio is 38:1. The MNM mortality ratios are lowest in amniotic fluid embolism, HIV/AIDS, heart disease, thrombophlebitis, and sepsis. For different organ dysfunctions, the ranks of the MNM mortality ratio from low to high are renal dysfunction, respiratory dysfunction, cardiovascular dysfunction, hepatic dysfunction, neurologic dysfunction, uterine dysfunction, coagulation dysfunction. The NMNMSS is a well-established hospital-based surveillance system for maternal complications in China. It can identify the maternal complications that need to improve health care immediately in China through a powerful longitudinal real-world evidence.