The Establishment and Application of the New Labor Progress Centered System of Reducing Cesarean Section Rates in China

Shanghai First Maternity and Infant Hospital

Status: Unknown

Conditions: Pregnancy Complications; Postpartum Hemorrhage

Study type: Observational

Funder types: Other

Identifiers

NCT02942719

FMIH Duan

Details and patient eligibility

About

1. To describe the average labor curve and establish new labor progression standards.
2. Cesarean section rates: Based on big data, the investigator will introduce the international advanced Robson class method and identify the appropriate level of cesarean section rate for each type population.
3. Establishment of "Chinese maternal-fetal medical collaboration network" and APP to promote natural childbirth.

Full description

1. To describe the average labor curve and establish new labor progression standards. The investigator will investigate the current characteristics of obstetric population and the labor progression with obstetric intervention in China. The investigator compare the different effects of traditional labor progression management model, new labor progression management model and active labor progression management model on labor outcomes. Based on the best outcomes of maternity and infants, the investigator will establish and modify new labor progression which is suitable for Chinese.
2. Cesarean section rates: Based on big data, the investigator will introduce the international advanced Robson class method and identify the appropriate level of cesarean section rate for each type population.the investigator compare cesarean section rates of different level hospitals and evaluate the effects of reducing cesarean section rates. The investigator also analyze the risk factors of cesarean section rates of the ten Robson classification, which will provide basis for reducing cesarean section rates under the new strategy.
3. Establishment of "Chinese maternal-fetal medical collaboration network" and mobile application software (APP) to promote natural childbirth: The investigator establish perinatal data center using the hospital information system (HIS) system of hospital. The investigator predict the cesarean section rates and relative factors using the Robson classification method, and propose the new strategy of reducing cesarean section rates. Meanwhile, the investigator develop the quality management system toolkit which can help clinicians standardize behavior and improve obstetric safety.

Enrollment: 15,000 estimated patients

Sex: Female

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

1. Chinese pregnant women
2. singleton
3. head position
4. 37 weeks + 0 day - 41weeks + 6 days
5. primipara
6. low-risk pregnancy
7. vaginal delivery willingness
8. vaginal cervix <7 cm after labor

Exclusion criteria

1. multiple pregnancy
2. non-head position
3. stillbirth
4. selective cesarean section
5. prenatal cesarean section
6. age <18 years
7. previous childbirth history
8. pregnancy complications
9. important fetal malformations.

Trial design

15,000 participants in 20 patient groups

Shanghai First Maternity and Infant Hospital

Dalian Maternity and Child Health Hospital

Beijing Obstetrics and Gynecology Hospital

Shijiazhuang Obstetrics and Gynecology Hospital

The Children and Women's Healthcare of Laiwu City

Suzhou Municipal Hospital

Wenling Women's and Children's Hospital

First Affiliated Hospital of Kunming Medical University

Changsha Hospital for Maternal and Child Health Care

Xinxiang Maternity and Child Health Hospital

Yanshi People's Hospital

The Maternal and Child Health Hospital of Guangxi

Northwest Women and Children's Hospital

Suining Central Hospital

Inner Mongolia Maternity and Child Health Hospital

Fujian Province Maternity and Child Health Hospital

Qinghai Red Cross Hospital

Xinjiang Maternity and Child Health Hospital

Jiangmen Maternity and Child Health Care Hospital

Gansu Provincial Maternity and Child-care Hospital