Literature DB >> 29208502

Rate of caesarean sections according to the Robson classification: Analysis in a French perinatal network - Interest and limitations of the French medico-administrative data (PMSI).

A-S Lafitte1, P Dolley2, X Le Coutour3, G Benoist4, L Prime5, P Thibon5, M Dreyfus4.   

Abstract

INTRODUCTION: The objective of our study was to determine, in accordance with WHO recommendations, the rates of Caesarean sections in a French perinatal network according to the Robson classification and determine the benefit of the medico-administrative data (PMSI) to collect this indicator. This study aimed to identify the main groups contributing to local variations in the rates of Caesarean sections.
MATERIAL AND METHODS: A descriptive multicentric study was conducted in 13 maternity units of a French perinatal network. The rates of Caesarean sections and the contribution of each group of the Robson classification were calculated for all Caesarean sections performed in 2014. The agreement of the classification of Caesarean sections according to Robson using medico-administrative data and data collected in the patient records was measured by the Kappa index. We also analysed a 6 groups simplified Robson classification only using data from PMSI, which do not inform about parity and onset of labour.
RESULTS: The rate of Caesarean sections was 19% (14.5-33.2) in 2014 (2924 out of 15413 deliveries). The most important contributors to the total rates were groups 1, 2 and 5, representing respectively 14.3%, 16.7% and 32.1% of the Caesarean sections. The rates were significantly different in level 1, 2b and 3 maternity units in groups 1 to 4, level 2a maternity units in group 5, and level 3 maternity units in groups 6 and 7. The agreement between the simplified Robson classification produced using the medical records and the medico-administrative data was excellent, with a Kappa index of 0.985 (0.980-0.990).
CONCLUSION: To reduce the rates of Caesarean sections, audits should be conducted on groups 1, 2 and 5 and local protocols developed. Simply by collecting the parity data, the excellent metrological quality of the medico-administrative data would allow systematisation of the Robson classification for each hospital.
Copyright © 2017. Published by Elsevier Masson SAS.

Entities:  

Keywords:  Medico-administrative data; Obstetrics; Rate of Caesarean sections; Robson classification

Mesh:

Year:  2017        PMID: 29208502     DOI: 10.1016/j.jogoh.2017.11.012

Source DB:  PubMed          Journal:  J Gynecol Obstet Hum Reprod        ISSN: 2468-7847


  5 in total

1.  Cesarean rates according to the Robson classification: analysis in a municipal maternity in São Paulo.

Authors:  Gabriela Guimarães Franco Ramos; Eduardo Zlotnik; Adolfo Wenjaw Liao
Journal:  Einstein (Sao Paulo)       Date:  2022-07-13

2.  Caesarean section in Palestine using the Robson Ten Group Classification System: a population-based birth cohort study.

Authors:  Mohammed Walid Zimmo; Katariina Laine; Sahar Hassan; Bettina Bottcher; Erik Fosse; Hadil Ali-Masri; Kaled Zimmo; Ragnhild Sørum Falk; Marit Lieng; Åse Vikanes
Journal:  BMJ Open       Date:  2018-10-24       Impact factor: 2.692

3.  Implementation of the WHO manual for Robson classification: an example from Sri Lanka using a local database for developing quality improvement recommendations.

Authors:  Hemantha Senanayake; Monica Piccoli; Emanuelle Pessa Valente; Caterina Businelli; Rishard Mohamed; Roshini Fernando; Anshumalie Sakalasuriya; Fathima Reshma Ihsan; Benedetta Covi; Humphrey Wanzira; Marzia Lazzerini
Journal:  BMJ Open       Date:  2019-02-19       Impact factor: 3.006

4.  A 10 year comparative study of caesarean deliveries using the Robson 10 group classification system in a university hospital in Austria.

Authors:  Taja Bracic; Isabella Pfniß; Nadja Taumberger; Kaltrina Kutllovci-Hasani; Daniela Ulrich; Wolfgang Schöll; Philipp Reif
Journal:  PLoS One       Date:  2020-10-16       Impact factor: 3.240

5.  Congenital haemangiomas: a single-centre retrospective review.

Authors:  Victoire Braun; Sorilla Prey; Carlotta Gurioli; Franck Boralevi; Alain Taieb; Nicolas Grenier; Maya Loot; Marie-Laure Jullie; Christine Léauté-Labrèze
Journal:  BMJ Paediatr Open       Date:  2020-12-07
  5 in total

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