Demonstration of the application of the global cesarean section rate model (C-Model) and the Robson Classification to estimate and characterize excess numbers of institutional c-sections

• Published in: Revista colombiana de obstetricia y ginecología 2021-12, Vol.72 (4), p.396
• Main Author: Zuleta-Tobón, John Jairo
• Format: Article
• Language: eng ; spa
• Subjects: Cesarean Section; Colombia; Female; Health Facilities; Hospitals; Humans; Male; Pregnancy
• ISSN: 2463-0225; 2463-0225
• DOI: 10.18597/rcog.3649

To carry out an academic exercise based on real local data regarding the application of the C-Model v1.0 to determine how data are gathered and used to generate the model, how the model is applied in order to identify potential excess numbers of cesarean sections in an institution, and when identified, how the model is applied to distribute deliveries according to the Robson Classification system and explain excess numbers. The standardized ratio and absolute difference between the observed proportion and the expected probability of c-sections according to the C-Model v1.0 were estimated for each institution using real databases of five hospitals in Colombia. Convenience selection was used to meet the objectives. Based on the assumptions underpinning group distributions according to the Robson classification, proposed explanations for excess numbers and differences among institutions are presented. Applying the C-Model, the c-section standardized ratio identified different excess numbers of the procedure in the presence of similar institutional c-section proportions. Important variability was found in the proportion of c-sections among women with similar clinical and obstetric characteristics, which might explain the excess numbers identified. The C-Model allows to estimate expected c-section proportions according to the specific characteristics of the women seen at each institution; their distribution according to the Robson Classification is a way to explore the origin and particulars of those differences.