Clinical Trials Directory

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UnknownNCT02942719

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

Status
Unknown
Phase
Study type
Observational
Enrollment
15,000 (estimated)
Sponsor
Shanghai First Maternity and Infant Hospital · Academic / Other
Sex
Female
Age
18 Years
Healthy volunteers
Accepted

Summary

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.

Detailed 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.

Conditions

Timeline

Start date
2016-01-01
Primary completion
2018-12-01
Completion
2018-12-01
First posted
2016-10-24
Last updated
2016-10-24

Locations

1 site across 1 country: China

Source: ClinicalTrials.gov record NCT02942719. Inclusion in this directory is not an endorsement.