Trials / Unknown
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.