Understanding caesarean section rate in a tertiary centre using the Robson classification system; a one-year retrospective study in Ghana

Although caesarean section (CS) has been shown to improve birth outcomes significantly, CS rates have risen globally to the point of becoming a public health concern. To identify major drivers of rising CS rates using the Robson Classification System and determine category-specific contributions to inform targeted interventions. This cross-sectional retrospective study systematically reviewed all deliveries that took place (January– December, 2019) at the Obstetrics and Gynaecology Directorate, Komfo Anokye Teaching Hospital, Ghana. The delivery records were stratified based on the Robson 10-Groups Classification System. A total of 6814 deliveries were conducted with an overall CS rate of 44.51%. Of the total number of deliveries, 6431 folders representing 94.38% were available for data extraction. The top three contributors to the overall CS rate in descending order were as follows: Group 5 (Previous CS, single cephalic, > 37 weeks), group 10 (all single cephalic, < 36 weeks (including previous CS) and Group 1 (Nulliparous, single cephalic, > 37 weeks in spontaneous labour); these three groups cumulatively made a relative contribution of 60.85% to the overall CS rate. Group 9 (All abnormal lies (including previous CS) contributing the least value of 0.42%. Furthermore, 8.37% (538/6431) of extracted data had missing information in the patient medical records and could not be classified into a Robson group. Missing information on gestational age was the major contributor (89.13%) to the missing data. TOLAC Promotion: Implement RCOG-aligned protocols for trial of labour in eligible women with previous CS. Data Quality: Introduce electronic checklist tools at admission to capture Robson parameters.

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Publication Details

Journal
Discover Medicine
Published
2025-09-24
DOI
https://doi.org/10.1007/s44337-025-00417-3
Primary Topic
Maternal and Perinatal Health Interventions
Type
article
Field-Weighted Citation Impact
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article

Understanding caesarean section rate in a tertiary centre using the Robson classification system; a one-year retrospective study in Ghana

Emmanuel Kusi Sarpong, Yaw Owusu, Michael Amoah, Gerald Owusu Asubonteng et al.
Discover Medicine
Maternal and Perinatal Health Interventions
article

Understanding caesarean section rate in a tertiary centre using the Robson classification system; a one-year retrospective study in Ghana

Emmanuel Kusi Sarpong, Yaw Owusu, Michael Amoah, Gerald Owusu Asubonteng, Eric Lartey Quarshie, H.-H. Adam, Emmanuel Opoku, Adamtey Ababio, Adelaide Sarkodie
article en

Abstract

Although caesarean section (CS) has been shown to improve birth outcomes significantly, CS rates have risen globally to the point of becoming a public health concern. To identify major drivers of rising CS rates using the Robson Classification System and determine category-specific contributions to inform targeted interventions. This cross-sectional retrospective study systematically reviewed all deliveries that took place (January– December, 2019) at the Obstetrics and Gynaecology Directorate, Komfo Anokye Teaching Hospital, Ghana. The delivery records were stratified based on the Robson 10-Groups Classification System. A total of 6814 deliveries were conducted with an overall CS rate of 44.51%. Of the total number of deliveries, 6431 folders representing 94.38% were available for data extraction. The top three contributors to the overall CS rate in descending order were as follows: Group 5 (Previous CS, single cephalic, > 37 weeks), group 10 (all single cephalic, < 36 weeks (including previous CS) and Group 1 (Nulliparous, single cephalic, > 37 weeks in spontaneous labour); these three groups cumulatively made a relative contribution of 60.85% to the overall CS rate. Group 9 (All abnormal lies (including previous CS) contributing the least value of 0.42%. Furthermore, 8.37% (538/6431) of extracted data had missing information in the patient medical records and could not be classified into a Robson group. Missing information on gestational age was the major contributor (89.13%) to the missing data. TOLAC Promotion: Implement RCOG-aligned protocols for trial of labour in eligible women with previous CS. Data Quality: Introduce electronic checklist tools at admission to capture Robson parameters.

Discover MedicineVol. 2(1)
Komfo Anokye Teaching Hospital (GH), Kwame Nkrumah University of Science and Technology (GH)
Openalex Percentile: Top 68%
Maternal and Perinatal Health Interventions
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