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An Analysis of the Mode of Delivery, Risk Factors, and Subgroups with High Caesarean Birth Rates Using Robson
Gulifeiya Abuduxike1, Sanda Cali2, Songül Acar Vaizoğlu2
1Department of Public Health, Faculty of Medicine, Near East University, Near East Boulevard, 99138, Nicosia, Northern Cyprus. gulpiya1@gmail.com.
Insights
This study found a high cesarean section (CS) rate of 50.2% and poor obstetric data quality. Implementing the Robson classification system is recommended to improve data and monitor CS rates effectively.
Area of Science:
- Obstetrics and Gynecology
- Public Health
- Medical Informatics
Background:
- Cesarean section (CS) rates are a global health concern.
- Evaluating CS rates and associated risk factors is crucial for maternal and infant health.
- The Robson classification system offers a standardized method for analyzing CS data.
Purpose of the Study:
- To analyze the mode of delivery and identify risk factors for cesarean sections.
- To apply the Robson classification system for data quality assessment and CS rate analysis in subgroups.
- To evaluate the contribution of different Robson groups to the overall CS rate.
Main Methods:
- Retrospective descriptive study of 797 deliveries in 2019.
- Data extracted from medical records using a developed proforma.
- Women categorized into Robson groups based on six obstetric parameters.
Main Results:
- Overall CS rate was 50.2% (401/797).
- Risk factors for CS included advanced maternal age, Turkish Cypriot ethnicity, preterm birth, previous CS, multiple fetuses, and abnormal fetal presentation.
- Robson Group 5 was the largest contributor to CS (50.7%), followed by Group 10 (25.3%) and Group 8 (9.0%).
Conclusions:
- Substandard obstetric data quality and a high CS rate were identified.
- Improving medical record quality is a top priority.
- The Robson classification system should be implemented as standard practice to enhance data quality and monitor CS rates.
Objective:
We aimed to understand the utilization of the mode of delivery and related risk factors. Further aimed to apply the Robson classification system to evaluate the data quality and analyze the CS rates in subgroups.
Methods:
We conducted a retrospective descriptive study by reviewing the medical records of all women who delivered at the State Hospital in 2019. A proforma was developed for extracting data from patient records. All women with six obstetric parameters were categorized into Robson groups to determine the absolute and relative contributions of each group to the overall CS rate.
Results:
Of 797 deliveries, 401 (50.2%) were CSs. Being older, being Turkish Cypriot, having preterm births, previous CS, multiple fetuses, and having breech or transverse fetal presentations were related to having higher risks of CS. The most common medical indication for CSs (52.3%) was a history of previous CSs. Robson Group 5 contributed the most (50.7%) to the overall CS rate, with the highest absolute contribution of 21.8%. Group 10 and Group 8 were the second and third highest contributors to the overall CS rate, with relative contributions of 25.3% and 9.0%, respectively.
Conclusions:
Findings revealed the substandard quality of obstetric data and a noticeably high overall CS rate. The top priority should be given to improving the quality of medical records. It underscored the necessity of implementing the Robson classification system as a standard clinical practice to enhance data quality, which helps to effectively evaluate and monitor the CS rates in obstetric populations.
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